Choose Report Type
Publication Date
Report Upload
Download
(6.07 MB)
vertical
Energy
PDF Text
SECTORAL INSIGHTS:
AGRICULTURE
SCENARIOS TOWARDS VIKSIT BHARAT AND NET ZERO
(VOL. 6) SCENARIOS TOWARDS
VIKSIT BHARAT AND NET ZERO
SECTORAL INSIGHTS:
AGRICULTURE
(VOL. 6) Copyright © NITI Aayog, 2026
NITI Aayog
Government of India,
Sansad Marg, New Delhi–110001, India
Suggested Citation
NITI Aayog. (2026). Scenarios Towards Viksit Bharat and Net Zero -
Agriculture (Vol. 6)
Available at: https://niti.gov.in/publications/division-reports
Disclaimer
1. This document is not a statement of policy by the National Institution for
Transforming India (hereinafter referred to as NITI Aayog). It has been prepared
by the Green Transition, Energy, Climate, and Environment Division of NITI Aayog
under various Inter-Ministerial Working Groups (IMWGs) constituted to develop Net
Zero pathways for India.
2. Unless otherwise stated, NITI Aayog, in this regard, has not made any representation
or warranty, express or implied, as to the completeness or reliability of the
information, data, findings, or methodology presented in this document. While due
care has been taken by the author(s) in the preparation of this publication, the
content is based on independently procured information and analysis available at
the time of writing and may not reflect the most current policy developments or
datasets.
3. The assertions, interpretations, and conclusions expressed in this report are those
of the author(s) and do not necessarily reflect the views of NITI Aayog or the
Government of India, unless otherwise mentioned. As such, NITI Aayog does not
endorse or validate any of the specific views or policy suggestions made herein by
the author(s).
4. NITI Aayog shall not be liable under any circumstances, in law or equity, for any
loss, damage, liability, or expense incurred or suffered as a result of the use of or
reliance upon the contents of this document. Any reference to specific organisations,
products, services, or data sources does not constitute or imply an endorsement
by NITI Aayog. Readers are encouraged to independently verify the data and
conduct their analysis before forming conclusions or taking any policy, academic,
or commercial decisions. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture v Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture vii
Working group members
and Authors
Chairperson
Prof. Ramesh Chand
Member, NITI Aayog
Leadership
Sh. Suman Berry
Vice chairman, NITI Aayog
Sh. B.V.R. Subrahmanyam
CEO, NITI Aayog
Dr. Anshu Bhardwaj
Programme Director, Green Transition and
Climate Change Division
Sh. Amit Verma
Former Director, Green Transition and Climate
Change, NITI Aayog;
Joint Secretary, Ministry of Commerce and
Industry
Authors
NITI Aayog
Dr. Anjali Jain
Consultant, NITI Aayog
Sh. Nitin Bajpai
Consultant, NITI Aayog
Dr. Priyanka Sarkar
Consultant, NITI Aayog
Sh. Venugopal Mothkoor
Energy and Climate Modelling Specialist,
NITI Aayog
Council on Energy, Environment
and Water (CEEW)
Dr. Chandan Jha
Programme Lead, CEEW
Ms. Nikhitha Jagadeesh
Programme Associate, CEEW
Sh. Apoorve Khandelwal
Fellow, Sustainable Food Systems,CEEW
Ms. Aastha Bafna
Research Analyst, CEEW
Sh. Abhishek Jain
Director and Fellow, Green Economy and
Impact Innovations, CEEW
Ms. Kumari Amisha Patel
Research Analyst, CEEW
Dr. Joy Rajbhanshi,
Programme Lead, CEEW
Ms. Mani Deshmukh
Research Analyst, CEEW
Sh. Gursimer Singh Gulati
Research Analyst, CEEW
Dr. Vaibhav Chaturvedi
Senior Fellow, CEEW Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture viii
Working group members and Authors
Core Modelling Team
NITI Aayog
Dr. Anjali Jain
Consultant, NITI Aayog
Sh. Nitin Bajpai
Consultant, NITI Aayog
Dr. Priyanka Sarkar
Consultant, NITI Aayog
Sh. Venugopal Mothkoor
Energy and Climate Modelling Specialist,
NITI Aayog
Council on Energy, Environment
and Water (CEEW) - Lead
Dr. Chandan Jha
Programme Lead, CEEW
Ms. Nikhitha Jagadeesh
Programme Associate, CEEW
Ms. Aastha Bafna
Research Analyst, CEEW
Peer Reviewer
Dr. Sivendra Kumar Srivastava
Senior Scientist, ICAR-NIAP
Working Group Coordinators
Dr. Priyanka Sarkar
Consultant, NITI Aayog
Ms. Diana Datta
Young professional, NITI Aayog
Ms. Aastha Singh
Young professional, NITI Aayog
Working Group Members
Sh. Franklin L. Khobung
Joint Secretary, Ministry of Agriculture and
Family Welfare (MoAFW)
Sh. N.K. Shah
Joint Secretary, Ministry of Environment,
Forest and Climate Change (MoEFCC)
Sh. Raman Mathur
Ministry of Rural Development (MoRD)
Sh. Rakesh Kumar Verma
Additional Secretary, Ministry of Jal Shakti
(MoJS)
Dr. Faiz Ahmed Kidwai
Former Chief Executive Officer (CEO),
National Rainfed Agriculture Authority
(NRAA)
Sh. Dhura Ram
Additional Commissioner (NRM/RFS),
Department of Agriculture and Farmer
Welfare (DoAFW)
Sh. Bhushan Tyagi
Joint Commissioner, Department of Animal
Husbandry and Dairying (DAHD)
Sh. Ajay Raghava
Deputy Director,
Ministry of Environment, Forest and Climate
Change (MoEFCC)
Dr. Zoya Rizvi
Deputy Commissioner at National Health
Mission, Ministry of Health and Family
Welfare (MoHFW)
Sh. Sharath Kumar Pallerla
Scientist G, Ministry of Environment, Forest
and Climate Change (MoEFCC)
Sh. Manoj Kumar
Director General, PPAC, Ministry of Petroleum
and Natural Gas (MoPNG)
Dr. Suresh Kumar Chaudhary
Former Deputy Director General (NRM), ICAR
Dr. Raghavendra Bhatta
Deputy Director General (Animal Science),
Indian Council of Agricultural Research (ICAR) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture ix
Working group members and Authors
Dr. Shyam Narayan Jha
Deputy Director General (Agricultural
Engineering), Indian Council of Agricultural
Research (ICAR)
Dr. A. Velmurugan
Assistant Director General (Soil and Water
Management), Indian Council of Agricultural
Research (ICAR)
Dr. Pratap S. Birthal
Director, National Institute of Agricultural
Economics and Policy Research (ICAR-NIAP)
Dr. Nitin Tyagi
Principal Scientist, National Dairy Resarch
Institute (ICAR-NDRI)
Dr. Goutam Mondal
Scientist, National Dairy Resarch Institute
(ICAR-NDRI)
Dr. Sunil Kumar
Director, Indian Institute of Farming Systems
Research (ICAR-IIFSR)
Dr. Vasu D
Scientist, National Bureau of Soil Survey and
Land Use Planning (ICAR -NBSS & LUP)
Dr. Pradeep Kumar Malik
Senior Scientist, National Institute of Animal
Nutrition and Physiology (ICAR - NIANP)
Dr. Pradeep Dogra
Principal Scientist, Indian Institute of Soil and
Water Conservation (ICAR - IISWC)
Dr. Pankaj Kaushal
Former Director, Indian Grassland and Fodder
Research Institute (ICAR-IGFRI)
Dr. Purushottam Sharma
Principal Scientist, Indian Grassland and
Fodder Research Institute (ICAR-IGFRI)
Dr. S.P. Datta,
Former Director, Indian Institute of Soil
Science (ICAR-IISS)
Dr. Ayyandar Arunchalam
Director, Central Agroforestry Research
Institute (ICAR-CAFRI)
Dr. Vinod Kumar Singh
Director, Central Research Institute for
Dryland Agriculture (ICAR - CRIDA)
Dr. Hemalatha N
Former Director, ICMR-National Institute of
Nutrition (NIN)
Dr. Vineeta Kumari
Deputy Director, MANAGE
Sh. Kamal Pandey
Deputy Director, Forest Survey of India
Dr. Indu K Murthy
Sector Head, Center for Study of Science,
Technology and Policy (CSTEP)
Sh. Kaveri Ashok
Research Scientist, Center for Study of
Science, Technology and Policy (CSTEP)
Dr. Ruchika Singh
Executive Programme Director, World
Resources Institute (WRI)
Dr. Chandrashekhar Biradar
Former Country Director, Centre for
International Forestry Research (CIFOR -
ICRAF)
Dr. Kavi Kumar
Professor, Madras School of Economics
(MSE)
Collaborators/Expert Consultants
Dr. Sivendra Kumar Srivastava
Senior Scientist, National Institute of
Agricultural Economics and Policy Research
(ICAR-NIAP)
Dr. Sivaramane N
Senior Scientist, National Academy of
Agricultural Research Management (ICAR-
NAARM) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture x
Working group members and Authors
Dr. Ranjit Kumar Paul
Senior Scientist, Indian Agricultural Statistics
Research Institute(ICAR-IASRI)
Dr. Niveta Jain
Principal Scientist, Indian Agricultural
Research Institute (ICAR-IARI)
Dr. Arti Bhatia
Principal Scientist, Indian Agricultural
Research Institute (ICAR-IARI)
Dr. V. Ramamurthy
Principal Scientist, National Bureau of Soil
Survey and Land Use Planning (ICAR -NBSS
& LUP)
Dr. Ram Kanwar Malik
India Country Coordinator and senior
agronomist at CIMMYT
Dr. Raman Meenakshi Sundaram
Director, Indian Institute of Science Research
(ICAR-IIRR)
Dr. Vasu D
Scientist, National Bureau of Soil Survey and
Land Use Planning (ICAR -NBSS & LUP)
Sh. V.P. Singh
Director(AHS), Department of Animal
Husbandry and Dairying (DAHD)
N. Ravishankar
Project Coordinator and Principal Scientist,
Indian Institute of Farming Systems Research
(IIFSR)
Editor
Ms. Aastha Manocha
Editor and Communication Consultant
Communication and Research &
Networking Division, NITI Aayog
Ms. Anna Roy
Programme Director, Research & Networking
Sh. Yugal Kishore Joshi
Lead, Communication
Ms. Keerti Tiwari
Director, Communication
Dr. Banusri Velpandian
Senior Specialist, Research & Networking
Ms. Sonia Sachdeva Sharma
Consultant, Communication
Sh. Souvik Chongder
Young Professional, Communication
NITI Design Team
NITI Maps & Charts Team Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xi
Contents
List of Figures xii
List of Tables xiv
List of Abbreviations xv
Executive Summary xix
Background xxvi
1. Introduction.....................................................................................................................................1
1.1. Historical trends in agricultural production and growth 2
1.2. Climate change, agriculture vulnerability and emissions profile 4
1.3. Historical trends in non-energy emissions from agriculture sector 6
2. Methodology.................................................................................................................................11
2.1 Approach to Estimating Mitigation Co-Benefits of Non-Energy Agricultural pathways 12
2.2 Energy demand estimations for agriculture 23
3. Results...........................................................................................................................................27
3.1 Non-Energy Emissions Pathways in Agriculture 28
3.2 Energy Emissions Pathways in Agriculture 37
4. Key Challenges and suggestions..............................................................................................41
4.1 Key Challenges 42
4.2 Suggestions for Sustainable Long-Term Pathways for Agriculture and Allied Sectors 44
Annexures............................................................................................................................................49
Annexure I: Country-Specific Emission Factors for the Study 50
Annexure II: Policy Typologies 52
Annexure III: Emissions in Sustainable Rice Systems 54
Annexure IV: Energy Demand Projections of Irrigation Pumping 56
Annexure V: Energy Demand Projections of Land Preparation 58
Annexure VI: Scenario Rationale 60
References...........................................................................................................................................65 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xii
List of Figures
Figure E.1: Overall agriculture (non-energy) emissions in Current Policy Scenario
and Net Zero Scenario (2019-2070) xxi
Figure E.2: Livestock sub-sector emissions in Current Policy Scenario and Net Zero Scenario
(2019-2070) xxii
Figure E.3: Crop sub-sector emissions in Current Policy Scenario and Net Zero Scenario
(2019-2070) xxii
Figure E.4: Overall energy consumption (Mtoe) in Agriculture Sector (2020-2070) xxiii
Figure 1.1: Historical trends in rice acreage (2011-2019) 2
Figure 1.2: Historical trends in rice yields (2011-2019) 3
Figure 1.3: Historical trends in rice production (2011-2019) 3
Figure 1.4: Historical trend of milk productivity (2011-2019) 4
Figure 1.5: Trends in share of female bovines in total herd composition (2003 – 2019) 4
Figure 1.6: India’s historical trends of agriculture non-energy emissions (AR2) (2011-2019) 5
Figure 1.7: Historical trends of emissions from rice cultivation (AR2) (2011-2019) 7
Figure 1.8: Trends of cropping intensity (2011-2019) 7
Figure 1.9: Total nitrogen fertiliser consumption (2011-2019) 8
Figure 1.10: Emissions from agricultural soils (AR2) (2011-2019) 8
Figure 1.11: Historical milk production (2011-2019) 9
Figure 1.12: Historical livestock emissions (AR2) (2011-2019) 10
Figure 2.1: Agriculture emission modelling methodology 12
Figure 2.2: Irrigation module for energy demand projections 24
Figure 2.3: Land preparation module for energy demand projections 24
Figure 3.1: Gross cropped area projection (2000 to 2070) 28
Figure 3.2: Production projections of bovine milk (2000-2070) 29
Figure 3.3: Projected agriculture emission under Current Policy Scenario
and Net Zero Scenario (2019-2070) 30
Figure 3.4: Overall emissions – Livestock sub-sector (2019-2070) 30
Figure 3.5: Overall emissions – Crop sub-sector (2019-2070) 31
Figure 3.6: Rice cultivation emission trends in Current Policy Scenario and Net Zero Scenario
(2019-2070) 32 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xiii
List of Figures
Figure 3.7: Area under rice cultivation in Current Policy Scenario (2019-2070) 32
Figure 3.8: Area under rice cultivation in Net Zero Scenario (2019-2070) 33
Figure 3.9: Rice production from 2019 to 2070 under Current Policy Scenario
and Net Zero Scenario Rice area (2019-2070) 33
Figure 3.10: Agricultural soil emission trends in Current Policy Scenario and Net Zero Scenario
(2019-2070) 34
Figure 3.11: Cropping intensity in Current Policy Scenario and Net Zero Scenario (2019-2070) 34
Figure 3.12: Nitrogen fertiliser consumption per ha in Current Policy Scenario
and Net Zero Scenario (2019-2070) 35
Figure 3.13: Area under Natural and Chemical-free farming Current Policy Scenario
and Net Zero Scenario 35
Figure 3.14: Emissions from livestock sector in Current Policy Scenario
and Net Zero Scenario (2019-2070) 36
Figure 3.15: Milk yield trends in Current Policy Scenario and Net Zero Scenario (2019-2070) 37
Figure 3.16: Share of in-milk bovine population in the total bovine population (2019-2070) 37
Figure 3.17: Overall energy consumption in Agriculture Sector (2020-2070) 38
Figure 3.18a: Energy demand and fuel mix in agricultural pumping under Current Policy Scenario
(CPS) and Net Zero Scenario (NZS) by 2050 and 2070 38
Figure 3.18b: Energy demand and fuel mix in land preparation under Current Policy Scenario
(CPS) and Net Zero Scenario (NZS) by 2050 and 2070 39
Figure Annex VI.1: State distribution map based on rice area and yield trends 60
Figure Annex VI.2: Crop diversification opportunities from rice to nutri-cereals for India 61
Figure AnnexVI.3: Motivations of farmers to adopt Natural Farming 62
Figure AnnexVI.4: Biostimulant adoption in different agro-climatic zones in Andhra Pradesh 63 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xiv
Table E.1: Long-term (non-energy) pathways and assumptions for the agriculture sector xx
Table E.2: Long-term energy transition pathways and assumptions for the agriculture sector xx
Table E.3: Key drivers for achieving 26% of mitigation co-benefits in 2070 xxiii
Table 1.1: Description of agricultural emissions categories and their sources 6
Table 2.1: Emission estimation methodology for various categories considered for the
agriculture sector (MoEFCC, 2021) 14
Table 2.2: Emission estimation methodology for various categories considered
for the agriculture sector 14
Table 2.3: Policy typologies mapped against their potential mitigation co-benefits 15
Table 2.4: Key assumptions for 2047 and 2070 17
Table 2.4a: Assumptions of cropping intensity in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 18
Table 2.4b: Assumptions of area-based crop diversification in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 19
Table 2.4c: Assumptions of sustainable yield intensification in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 20
Table 2.4d: Assumptions of chemical-free farming in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 21
Table 2.4e: Assumptions of fertiliser uptake in Current Policy Scenario and Net Zero Scenario
(from Table 2.4) 21
Table 2.4f: Assumptions of sustainable rice cultivation practices in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 22
Table 2.4g: Assumptions of enhanced in- milk bovine productivity in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 22
Table 2.4h: Assumptions of increasing share of the in-milk population in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 23
Table 2.4i: Assumptions of reduced burning of crop residue in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 23
Table 2.5: Assumptions for estimating energy consumption for irrigation under
Current Policy Scenario and Net Zero Scenario 25
Table 2.6: Assumptions for estimating energy demand for land preparation under
Current Policy Scenario and Net Zero Scenario 26
Table 3.1: Agriculture emission trends across crop and livestock sub-sectors (2019 to 2070) 30
List of Tables Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xv
List of Abbreviations
AFOLU Agriculture, Forestry, and Other Land Use
AIBPAccelerated Irrigation Benefits Programme
ANNArtificial Neural Network
APCNF Andhra Pradesh Community Managed Natural Farming
APYArea, Production, and Yield
AR5Fifth Assessment Report
ARIMA Autoregressive Integrated Moving Average
AWBAgricultural Waste Burning
AWDAlternate Wetting and Drying
BGREI Bringing Green Revolution to Eastern India
BioE3 Biotechnology for Economy, Environment and Employment
BPKPBharatiya Prakritik Krishi Paddhati
BRCBiodiversity Resource Centres
BUR4Fourth Biennial Update Report
CAGRCompound Annual Growth Rate
CBGCompressed Biogas
CDPCrop Diversification Programme
CGIAR Consultative Group on International Agricultural Research
CHCCustom Hiring Centres
CPSCurrent Policy Scenario
CRMCrop Residue Management
CRPCommunity Resource Person
DAHDDepartment of Animal Husbandry and Dairying
DIDrip Irrigation
DSRDirect Seeded Rice
FAIFertiliser Association of India
FAOFood and Agriculture Organization
FPOsFarmer Producer Organisations
FUEFertiliser uptake/use efficiency
GCAGross Cropped Area
GDPGross Domestic Product
GHGGreenhouse Gas
GoIGovernment of India
GPGram Panchayat
GWPGlobal Warming Potential Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xvi
HYVHigh-Yielding Varieties
IAMIntegrated Assessment Modelling
ICARIndian Council of Agricultural Research
ICDSIntegrated Child Development Services
IGFRI ICAR-Indian Grassland and Fodder Research Institute
INMIntegrated Nutrient Management
IPCCIntergovernmental Panel on Climate Change
IVFIn-Vitro Fertilisation
LT-LEDS Long-Term Low-Carbon Development Strategy
MhaMillion Hectares
MMManure Management
MoAFW Ministry of Agriculture & Farmers’ Welfare
MoEFCC Ministry of Environment, Forest and Climate Change
MTMillion Tonnes
MtCO
2
e Millions Tonnes of Carbon Dioxide equivalent
NAASNational Academy of Agricultural Sciences
NDCNationally Determined Contributions
NFNatural Farming
NFSANational Food Security Act
NFSMNational Food Security Mission
NICRA National Innovations in Climate Resilient Agriculture
NITI Aayog National Institution for Transforming India Aayog
NMMNational Millet Mission
NMNF National Mission on Natural Farming
NMSA National Mission for Sustainable Agriculture
NPOP National Programme for Organic Production
NRLM National Rural Livelihood Mission
NSA Net Sown Area
NUE Nitrogen Use Efficiency
NZSNet Zero Scenario
OECD Organisation for Economic Co-operation and Development
PDS Public Distribution System
PGS Participatory Guarantee System
PIB Press Information Bureau
PKVY Paramparagat Krishi Vikas Yojana
PM POSHAN Pradhan Mantri Poshan Shakti Nirman
PMDDKY PM Dhan Dhanya Krishi Yojana
PMGKAY Pradhan Mantri Garib Kalyan Anna Yojana
PMKSY Pradhan Mantri Krishi Sinchayee Yojana
PMKSY-MI Pradhan Mantri Krishi Sinchayee Yojana - Micro Irrigation
PMO Prime Minister’s Office
List of Abbreviations Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xvii
PM-PRANAM
Programme for Restoration, Awareness Generation, Nourishment, and Amelioration
of Mother-Earth
R&D Research & Development
RBP Ration Balancing Programme
RKVY Rashtriya Krishi Vikas Yojana
SATAT Sustainable Alternative Towards Affordable Transportation
SDG 17 Sustainable Development Goal 17
SHC Soil Health Card
SHGs Self-Help Groups
SHM Soil Health Management
SI Subsurface Irrigation
SMAM Sub-Mission on Agricultural Mechanisation
SOC Soil Organic Carbon
SRC Sustainable Rice Cultivation
SRI System of Rice Intensification
SYI Sustainable Yield Intensification
UN-DESA United Nations Department of Economic and Social Affairs
List of Abbreviations Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xix
Executive Summary
Context and Purpose
Agriculture sits at the complex intersection of India’s Viksit Bharat aspirations and its Net Zero
ambition. As the anchor of India’s rural economy, the sector supports 46% of the workforce
and ensures national food security while contributing ~14% to Gross Value Added (GVA) (MoF,
2025). However, this foundational role characterised by the dominance of small and marginal
farmers, is increasingly threatened by climate change, soil degradation, and acute water stress.
The sector also faces a dual challenge: it must meet escalating demands for food, fiber, and bio-
energy while grappling with a heavy environmental and resource footprint. Agriculture currently
accounts for ~14% of national Greenhouse Gas (GHG) emissions, driven by methane from enteric
fermentation and rice cultivation and nitrous oxide from agricultural soils (MoEFCC, 2024).
Furthermore, the sector consumes ~18% of national electricity (275 TWh) (CEA 2024), primarily
to power groundwater irrigation and expanding mechanisation.
Given the structural constrains and socio-economic salience, the sector’s long-term planning
requires a differentiated approach that prioritizes adaptation interventions while actively
delivering mitigation co-benefits. Recognising this imperative, NITI Aayog has constituted a
multi-ministerial Working Group on the Agriculture Sector. This 42-member inter-disciplinary
group operates with the objective:
“To develop and analyse various options/pathways to achieve long-term resilience, farmers’
incomes, food and nutritional security that deliver mitigation co-benefits, considering the
impacts of technology, policy, investment, ecology-based farming systems, and others.”
The Exercise and Scenarios
The study adopts an “adaptation-first” approach, assessing how pathways aimed at improving
resilience, farmers income, productivity and resource efficiency can also deliver mitigation co-
benefits. This mirrors India’s agricultural policy landscape, where initiatives such as the National
Mission on Sustainable Agriculture (NMSA), Crop Diversification Programme (CDP), National
Livestock Mission (NLM) already demonstrate the inherent synergy between adaptation and
mitigation outcomes (MoEFCC 2024).
The study applies supply-side modelling to assess long-term mitigation and on-farm energy-
efficiency co-benefits of various pathways (Table E.1 & E.2). Using 2019 as the baseline,
agricultural production projections for major crops and milk are aligned with NITI Aayog’s
“Crop Husbandry, Agriculture Inputs, Demand and Supply” for 2019–2047 and extrapolated to
2070. Any pathway-induced changes in production are translated into corresponding mitigation Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xx
Executive Summary
co-benefits using IPCC Tier-2 methods and into achieving on-farm energy efficiency. These
outcomes are assessed under two stakeholder-driven scenarios: The Current Policy Scenario
and an accelerated Net Zero Scenario. The two scenarios capture both existing and accelerated
policy adoption through stakeholder-driven assumptions for 2047 and 2070. Tables E.1 and E.2
below summarises the long-term stakeholder-driven assumptions considered in the analysis.
Table E.1: Long-term (non-energy) pathways and assumptions for the agriculture sector
Sl.
No
ScenariosUnit2019
(Baseline)
2070
(Current
Policy
Scenario)
2070
(Net Zero
Scenario)
1Cropping intensity % (Gross Cropped
Area/Net Sown Area)
151 165 180
2Crop diversification
(away from rice, wheat,
sugarcane)
% area shifting from
rice, wheat, sugarcane
0.23 15 20
3Sustainable Yield
Intensification (SYI)
% reduction in yield
gap
66% yield
gap
20 70
4Natural and Chemical-free
farming
% Net Sown Area <5% 20 25
5Fertiliser Uptake Efficiency
(FUE)
% nutrient uptake per
kg fertiliser applied
33 40 50
6Sustainable Rice
Cultivation (SRC) practices
% of area under rice 0.25 20 25
7Enhanced in-milk bovine
productivity
kg/head/day5.27 12 15
8Share of in-milk population% of total bovine
population
30 45 55
9Reduced crop residue
burning
% reduction0 30 60
Table E.2: Long-term energy transition pathways and assumptions for the agriculture sector
Sl.
No
Levers20202070
(Current Policy
Scenario)
2070
(Net Zero
Scenario)
1Irrigated share of Gross Cropped Area 53%65%60%
2Groundwater/ Pumping share65%65%60%
3Water Productivity Improvement-10%25%
4Share of Solar Pumps2%40%60%
5Share of Electric Pumps70%60%40%
6Pump efficiency (Solar & Electric) 36%40%50%
7Pumping Head (metre)285035 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxi
Executive Summary
Sl.
No
Levers20202070
(Current Policy
Scenario)
2070
(Net Zero
Scenario)
8Mechanisation level47%100%100%
9Tractor:tiller split95:5 70:3050:50
10Energy intensity per ha (MJ/ha)
(% reduction in energy intensity)
Tractors:880
Tillers: 960
–20%–40%
11Fuel Consumption in Land Preparation 100% diesel 9% diesel, 8%
CNG, 83% electric
99% Electric,
1% CNG/
Compressed
Biogas (CBG)
Modelling Insights
Modelling for non-energy pathways and mitigation co-benefits
Strategic scaling of nine (9) pathways (Table E.1) could unlock up to ~26% of the sector’s
mitigation co-benefits in the Net Zero Scenario (NZS) against the Current Policy Scenario
(CPS).
Under the Current Policy Scenario (CPS), agricultural emissions (non-energy) are expected to
rise from ~506 MtCO₂e in 2019 to ~531 MtCO₂e in 2070 (Figure E.1). This is driven by a ~20%
increase in livestock sub-sector and a ~21% decline in crop sub-sector (Figure E.2 and E.3).
Contrarily, Net Zero Scenario (NZS) is expected to deliver total emissions of ~399 MtCO₂e in
2070, with ~44% of decline in crop sub-sector and ~8% from livestock sub-sector (Figure E.2
and E.3). As a result, Net Zero Scenario could deliver ~25% mitigation co-benefits relative to
the CPS (Figure E.1). Table E.3 highlights key drivers of such substantial mitigation co-benefits.
Current Policy Scenario Net Zero ScenarioBaseline
Overall non-energy emissions from Agriculture sector (MtCO
2
e) (2019-2070)
600
400
200
0
Emissions (in MtCO
2
e)
Year
201920502070
506
535531
402399
~25%
Figure E.1: Overall agriculture (non-energy) emissions in Current Policy Scenario and Net Zero
Scenario (2019-2070) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxii
Executive Summary
Emissions (in MtCO
2
e)
Current Policy Scenario Net Zero ScenarioBaseline
Livestock sub-sector emissions (MtCO
2
e) (2019-2070)
Year
400
300
200
100
0
201920502070
322
379
286
386
297
Figure E.2: Livestock sub-sector emissions in Current Policy Scenario and Net Zero Scenario
(2019-2070)
Current Policy Scenario Net Zero ScenarioBaseline
Overall emissions from Crop sub-sector (MtCO
2
e) (2019-2070)
Year
250
200
150
100
50
0
183
156
145
116
102
201920502070
Emissions (in MtCO
2
e)
Figure E.3: Crop sub-sector emissions in Current Policy Scenario and Net Zero Scenario (2019-2070) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxiii
Executive Summary
Table E.3: Key drivers for achieving 26% of mitigation co-benefits in 2070
RiceAgriculture soilsLivestock
Three-pronged approach to
counter resource-intensive rice
cropping systems:
1. Crop diversification in areas
away from rice, wheat, and
sugarcane towards horticulture,
pulses, nutri-cereals etc.
2. Sustainable Yield Intensification
through technological (for
example high yielding varieties
etc.) interventions.
3. Adoption of sustainable rice
cultivation practices that
enhance water-use efficiency.
For example: alternate wetting
and drying (AWD), system of
rice intensification (SRI), direct
seeded rice (DSR), etc.
Two-pronged approach for
soil health enhancement
amidst the rising cropping
intensity:
1. Improving Fertiliser Use
Efficiency (FUE) through
informed and optimised
fertiliser use through Soil
Health Cards (SHCs),
adoption of neem-coated
urea.
2. Adoption of Natural and
Chemical-free farming
via National Mission on
Natural Farming (NMNF),
Paramparagat Krishi Vikas
Yojana (PKVY) etc.
Two-pronged approach for
enhancing the overall efficiency
of the livestock sector:
1. Enhancement of the
productivity of in-milk
bovine animals through
animal nutrition interventions
through dedicated
programmes on fodder and
also breed improvements.
2. Improving the share of
in-milk bovines in the
total livestock population
through animal health-
related programmes under
the National Livestock
Mission (NLM) (For example:
Veterinary services).
Modelling Energy Transition Pathways
Scaling eleven (11) pathways (Table E.2) could deliver ~30% energy savings in Net Zero
Scenario against Current Policy Scenario
Land Preparation Pumping
60
50
40
30
20
10
0
Mtoe
2020202520502070
Current Policy
Scenario
Current Policy
Scenario
Net Zero
Scenario
Net Zero
Scenario
Energy Consumption in the Agriculture Sector (Mtoe) (2020-2070)
2343
2124
38
31
51
36
33
23
27
42
34
54
39
Figure E.4: Overall energy consumption (Mtoe) in Agriculture Sector (2020-2070) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxiv
Executive Summary
In 2020, India’s agriculture consumed ~23 Mtoe, dominated by irrigation pumping. By 2070,
under the Current Policy Scenario, total demand rises to ~56 Mtoe, driven by expanding
irrigation, high groundwater use, and mechanisation. Pumping dominates with ~52.5 Mtoe
(mostly grid electricity, diesel, and 40% solar) followed by land preparation at ~3.7 Mtoe.
Under Net Zero Scenario, energy stabilises at ~39 Mtoe, with pumping plateauing at ~36.8 Mtoe
(60% solar, 40% grid) and land preparation at ~2.7 Mtoe, powered by electric tractors (~2.23
Mtoe) and Compressed Biogas (CBG) (~0.29 Mtoe) (Figure E.4). Efficiency gains, drip/sprinkler
irrigation, aquifer recharge, and technology shifts decouple energy use from rising production,
while Compressed Biogas (CBG) supported by Sustainable Alternative Towards Affordable
Transportation (SATAT) scheme, reduces residue burning, and generates rural income.
Key Suggestions
1. Develop intervention specific, targeted roadmaps: To maximise mitigation and energy-
efficiency co-benefits, policymakers must adopt a risk-calibrated, evidence-based approach
that integrates both supply and demand-side levers. Supply-side, adaptation-centric
pathways alone deliver ~25% of total mitigation co-benefits by 2070 (Figures E.1 & E.4),
underscoring the necessity of complementary demand-side shifts. On the demand side,
this includes rationalising energy use in agriculture and enabling dietary transitions towards
less resource-intensive, nutritionally dense foods. For instance, shifting consumption from
water and energy intensive rice towards climate-resilient millets can reduce emissions
while strengthening resilience. This could be supported by behaviour-change initiatives
such as the Eat Right Movement and National Millet Mission (NMM). To ensure that such
transitions scale without compromising farmer incomes or food and nutritional security, the
government must deploy phased, spatially targeted, and socio-economically differentiated
roadmaps, particularly for scaling natural and chemical-free farming interventions.
2. Institutionalize an integrated “agri-food” systems framework: No single intervention can
independently deliver meaningful mitigation or energy-efficiency co-benefits. Achieving
these outcomes requires an integrated approach that coordinates production systems,
dietary patterns, value chains, and environmental objectives across land, energy, food,
health, biodiversity and water systems. The Pradhan Mantri Dhan-Dhaanya Krishi Yojana
(PMDDKY) exemplifies the potential of such integration by converging multiple objectives
and programmes, including crop diversification, rural livelihoods, and access to credit,
across 100 low-productivity districts. Scaling similar initiatives using a whole-of-government
approach, with alignment across the Ministries of Agriculture, Energy, Water, and Health,
can embed clean energy, healthy diets and other low-emissions interventions directly into
agricultural development strategies. Such coordination enables coherent policy design,
reducing trade-offs and preventing fragmented interventions that risk generating competing
or counterproductive outcomes.
3. Conduct Integrated Assessment Modelling (IAM) to guide ambition setting and long-term
planning: Forward looking planning to achieve mitigation co-benefits by 2070 requires
evidence generation to evaluate trade-offs and synergies across farmer livelihoods, food and
nutritional security, and long-term resilience. Integrated Assessment Models (IAMs) provide
a data-driven framework to systematically link socio-economic trajectories, climate risks,
and policy levers such as carbon pricing and subsidy reform. When deployed effectively,
integrated assessment frameworks can inform policy design and implementation across Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxv
Executive Summary
national, state, and local levels of government, enabling the evaluation of both direct
impacts and second-order outcomes across land, energy, food, water and other systems.
4. Implement an “Efficiency-first + clean energy solutions” strategy to achieve maximum
efficiency within the sector: The energy demand, dominated by irrigation, must be managed
through an adaptation-first, agriculture-led approach, with energy interventions sequenced
subsequently to avoid energy-intensive lock-ins. An efficiency-first strategy should prioritise
resource-efficient practices such as micro-irrigation, sustainable crop management, and
rationalised input subsidies to strengthen resilience and reduce input intensity. Building on
these adaptation gains, energy interventions, including renewable adoption, electrification,
and Compressed Biogas (CBG), can then be deployed to decouple productivity growth
from energy use. Leveraging Custom Hiring Centres (CHCs) to expand access to clean
mechanisation for smallholders ensures that productivity gains translate into mitigation and
energy efficiency co-benefits without embedding high energy requirements. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxvi
Background
As India advances towards its Viksit Bharat vision by 2047 (PMO, 2023) and Net Zero
emissions by 2070 (MoEFCC, 2022), agriculture occupies a critical position at the intersection
of economic transformation, food security, and climate change. The sector supports nearly
46% of the population, and is dominated by small and marginal landholders. Despite facing
multiple shocks, including the COVID-19 pandemic and global geopolitical disruptions, Indian
agriculture has demonstrated resilience. Between 2017–18 and 2024–25, the sector sustained an
average annual growth rate of 5.22%, reinforcing its importance as a stabilising force within the
broader economy (MoF, 2025). However, this performance masks deep structural challenges
that threaten long-term sustainability and climate resilience.
Indian agriculture operates under rising climate risks, with small and marginal holders bearing
a disproportionate share of the burden. These pressures jeopardise farm livelihoods, weaken
production systems, and push households into deeper vulnerability. The challenge is further
intensified by widespread resource degradation, notably declining soil health and escalating
water stress.
However, agriculture sector also have substantial environmental footprint. It contributes about
~14% of India’s total greenhouse gas (GHG) emissions (MoEFCC, 2024), primarily from non-CO₂
gases and remains energy-intensive, accounting for 18–20% of national electricity consumption
and ranking second in diesel use (CEA, 2024).
Looking ahead, the sector’s vulnerability is likely to intensify due to rising heat stress, increasing
rainfall variability, and growing pressure on land and water resources, compounded by structural
constraints such as small and fragmented landholdings, high dependence on climate-sensitive
livelihoods, and limited adaptive capacity among smallholders. For instance, groundwater-
dependent irrigation systems heighten exposure to droughts and energy price shocks.
The sector faces high climate vulnerability and deep structural constraints, given its role in
livelihoods and food security. By 2070, the sector must feed billions, respond to evolving dietary
preferences and meet rising bioeconomy demands for feed, fibre, and bioenergy.
Consequently, agriculture in India cannot be approached through a narrow mitigation-centric
lens. For India, the priority is safeguarding productivity, farmers’ income and food and nutritional
security. This shall require focus on measures to build resilience to climate change. A mitigation-
focused approach risks exacerbating rural distress and undermining development outcomes.
Therefore, this report has taken a “differentiated” approach than what is adopted in other
sectoral reports in this series. It focuses on adaptation-first pathways
1
that support livelihoods
and food and nutritional security, and assesses their corresponding abilities in generating
1 Find strategies with their adaptation and mitigation outcomes in Table 2.3 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxvii
Background
mitigation co-benefits. For instance, diversification away from water-intensive cereals towards
pulses, oilseeds, and millets strengthens drought resilience and income stability, while mitigation
benefits arise through lower input use, reduced energy demand, and improved soil carbon,
leading to lower emissions intensity.
India has already initiated such multi-benefit approaches through programmes including the
National Mission on Sustainable Agriculture (NMSA), Crop Diversification Programme (CDP),
National Mission on Natural Farming (NMNF), National Millet Mission (NMM) among others.
These initiatives demonstrate how resilience enhancement, and resource conservation can also
contribute to lower emission intensity (MoF, 2025;MoEFCC, 2024).
Recognising this imperative, NITI Aayog has constituted a multi-ministerial Working Group on
the Agriculture Sector. This 42-member inter-disciplinary group operates with the objective:
To develop and analyse various options/pathways to achieve long-term resilience, farmers’
incomes, and food and nutritional security that deliver mitigation co-benefits, considering the
impacts of technology, policy, investment, ecology-based farming systems, and others.
The Terms of Reference (ToR) of the Working Group are:
1. To provide a comprehensive understanding of future trends in agricultural production of
major food commodities, including milk, through 2050 and 2070
2. To project non-energy emissions and energy demand through 2070 in India’s current policy
framework
3. To identify and develop long-term pathways that ensure farmers’ income, ensure resilience
and food and nutritional security that could deliver mitigation co-benefits.
4. To estimate overall mitigation co-benefits associated with the proposed pathways and
evaluate their effectiveness in supporting India’s climate goals.
Box 1: Scope of the Working Group
The Agriculture, Forestry, and Land Use (AFOLU) sector in India has exhibited a
net-negative emissions trend since 2018, primarily due to land-use-related carbon
sequestration offsetting agricultural emissions (MoEFCC, 2024). However, the focus
of this study is on understanding gross emissions from the agriculture sector (not
accounting sequestration). The study aims to provide a detailed assessment of various
adaptation-centric interventions with mitigation co-benefits in the agriculture sector
from non-energy use. 1
INTRODUCTION Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 2
Introduction
1
1.1. HISTORICAL TRENDS IN AGRICULTURAL PRODUCTION AND
GROWTH
India’s agricultural growth trajectory over the past five decades has been shaped by sustained
gains in productivity. In the pursuit of food security, the country more than doubled its food
grain production between 1970 and 2010, rising from ~108 to ~244 million tonnes (Agriculture
Statistics, 2023). Over the same period, milk production increased nearly fivefold, from ~22 to
~122 million tonnes, positioning India as the world’s largest producer. These achievements were
driven by transformative interventions under the Green Revolution and the White Revolution,
which expanded access to improved seed varieties, irrigation, fertilisers, veterinary services and
institutional support (John and Babu, 2021).
The momentum in agricultural output has continued in the last decade, reflecting improvements
in agricultural productivity and policy support. Between 2011 and 2019, food grain production
increased to ~285 million tonnes and further to ~332 million tonnes in 2023-24 (PIB,2011; PIB,2019;
Agriculture Statistics, 2023), while milk production rose sharply to ~198 million tonnes (DAHD,
2023). Such production gains were largely achieved through productivity improvements over
area or herd size expansion.
For example, rice yields increased by ~14% between 2011 and 2019, from ~2.3 to ~2.7 tonnes
per hectare, while the area under rice cultivation remained broadly stable at around 44 million
hectares (Agriculture Statistics, 2023) (Figure 1.1 & 1.2). As a result, rice production increased
from ~105 in 2011 to ~119 million tonnes in 2019 (Figure 1.3). This reflects the widespread adoption
of high-yielding varieties supported by expanded irrigation coverage under the Pradhan Mantri
Krishi Sinchayee Yojana (PMKSY).
44 43 44 44 44 44 44 44 44
75
50
25
0
Area (million hectares)
Year
20112013201520172012201420162018 2019
Area under rice cultivation (million hectares) (2011-2019)
Figure 1.1: Historical trends in rice acreage (2011-2019) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 3
Introduction
2.42.42.4
2.6
2.52.5
2.4
2.6
2.7
4
3
2
1
0
Yields (tonnes/hectare)
Year
20112013201520172012201420162018 2019
Rice yields (tonnes/hectare) (2011-2019)
Figure 1.2: Historical trends in rice yields (2011-2019)
Year
20112013201520172012201420162018 2019
200
150
100
50
0
Production (million tonnes)
Rice production (million tonnes) (2011-2019)
107 105 104
110
113
116
119
105 105
Figure 1.3: Historical trends in rice production (2011-2019)
Similarly, the livestock sector witnessed strong productivity gains. Average milk yield per in-
milk bovine increased by ~28.5%, from 4.10 kg/day in 2011 to 5.27 kg/day in 2019 (DAHD 2023),
supported by policy initiatives such as the National Dairy Plan and the National Livestock
Mission (Figure 1.4). Structural changes in herd composition further reinforced these gains.
Between 2012 and 2019, the share of female bovines increased from 72% to 81% (DAHD 2019),
alongside a gradual shift from low-yielding to higher-yielding and crossbred animals (Figure
1.5). These trends enabled rapid growth in milk output while maintaining relative stability in
the overall bovine population. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 4
Introduction
Aggregate milk productivity of in-milk bovines (kg/day/head) (2011-2019)
8
6
4
2
0
Milk productivity (kg/day/head)
Year
20112013201520172012201420162018 2019
4.1
4.34.2
4.5
4.7 4.8 4.9
4.1
5.3
Figure 1.4: Historical trend of milk productivity (2011-2019) (DAHD, 2018, 2019)
100
75
50
25
0
% composition
2003201220072019
Year
Feminisation of bovine animals (2003-2019)
Females (%) Males (%)
3534
28
19
6566
72
81
Figure 1.5: Trends in share of female bovines in total herd composition
(2003 – 2019) (DAHD, 2019)
Taken together, these historical trends highlight a defining feature of Indian agriculture: output
growth driven predominantly by productivity improvements, supported by public investment,
technology adoption and institutional reforms. This foundation is critical for understanding how
the sector now intersects with emerging climate-related challenges.
1.2. CLIMATE CHANGE, AGRICULTURE VULNERABILITY AND
EMISSIONS PROFILE
Agriculture in India is acutely exposed to climate risks. Frequent dry spells (Chuphal et.al, 2024)
and extreme rainfall events (Prabhu and Chitale, 2024) have been disrupting yields. Rising
temperatures and shifting precipitation patterns are projected to reduce crop productivities by Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 5
Introduction
8–12% by 2099 (MoF, 2025). These climate impacts are compounded by resource degradation:
declining soil organic carbon, unsustainable fertiliser use, and water stress linked to input-
intensive cropping systems (Birthal et al, 2014; MoEFCC, 2022). Together, these pressures are
jeopardising farmer livelihoods and weakening resilience by elevating costs and risks.
At the same time, the agriculture and allied sectors currently contribute ~13.7% to India’s
Greenhouse Gas (GHG) emissions (MoEFCC, 2024), predominantly from non-CO₂ GHGs such
as methane (CH₄) and nitrous oxide (N₂O). These gases have global warming potentials (GWP)
of 28 and 265 times that of CO₂ over 100 years (IPCC, 2014). Currently, it is responsible for ~75%
of India’s CH₄ and ~73% of its N₂O emissions, driven by enteric fermentation from livestock, rice
cultivation, and synthetic fertiliser use (Table 1.1) (Patange et al, 2024; MoEFCC, 2021).
In 2019, livestock emissions dominated agricultural emissions at ~60%, through enteric fermentation
(~53%) and manure management (~7%). This is followed by emissions from agricultural soils
(~21%) and methane from rice cultivation (~17%). Historical data indicates that agricultural non-
energy emissions increased marginally by ~3% from ~409 MtCO₂e in 2011 to ~421 MtCO₂e in
2019 (Figure 1.6) (MoEFCC, 2021). This is despite a ~19% growth in food grain production and
a ~55% growth in milk production, over the same period (Agriculture Statistics, 2023; DAHD
2023). This stabilisation of emissions in the last decade against significant production gains is
primarily due to:
a. Rice yield improvements by ~14% from 2.39 to 2.72 tonnes per hectare on a relatively
constant rice acreage of 44 million hectare (Agriculture Statistics, 2023).
b. Relatively stable livestock population as a result of 22% rise in productivity, due to the
following factors of herd restructuring:
i. Transition from low-yielding to high-yielding animals (NITI Aayog, 2024);
ii. Replacement of male bovines with female bovines, increasing the share of female
animals in the overall population
Agricultural
Waste Burning
Agricultural Soils
Rice Cultivation
Manure Management
Enteric Fermentation.
Total emissions
500
400
300
200
100
0
Emissions (MtCO
2
e)
Year
2011 2013 2015 20172012 2014 2016 2018 2019
Historical Agricultural Emissions (MtCO
2
e) (2011-2019)
219 222 224 227 222 223 223 223 223
28
73
88
421
28
74
84
417
28
74
81
411
27
71
78
408
27
72
80
410
28
73
81
417
28
73
80
414
27
71
80
408
27
73
82
409
Figure 1.6: India’s historical trends of agriculture non-energy emissions (AR2) (2011-2019)
(MoEFCC, 2021) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 6
Introduction
In addition, the sector is a major energy consumer, accounting for ~18% of national electricity
consumption and ranking second in diesel use (CEA, 2025). The emissions from diesel and
other fossil-fuel consumption in land-preparation and pumping are accounted as agriculture
energy emissions. In this study, the emissions from the electricity use in the agriculture sector
are accounted for in power sector emissions. Table 1.1 summarises the detailed description of
agriculture sector’s energy and non-energy emission sources.
As shown in Figure 1.6, in 2019, livestock emissions dominated agricultural emissions at ~60%,
through enteric fermentation (~53%) and manure management (~7%). This is followed by
emissions from agricultural soils (~21%) and methane from rice cultivation (~17%) (MoEFCC
2021).
Understanding the major drivers of agricultural emissions is critical for interpreting historical
trends, projecting future emission trajectories, and evaluating the effectiveness of policy
interventions. The following section examines historical drivers in detail.
Table 1.1: Description of agricultural emissions categories and their sources
SourceDescription of emission sources
Rice cultivation
Methane (CH₄) is produced in flooded rice fields through anaerobic
decomposition of organic matter.
Agricultural soils
Nitrous Oxide (N
2
O) is emitted from soils due to nitrogen inputs such as
fertilisers and manure, through microbial processes including nitrification and
denitrification.
Agricultural waste
burning
Both CH
4
and N
2
O are released during burning of crop residues, primarily
due to incomplete combustion of biomass and nitrogen-containing plant
material.
Enteric fermentation
CH
4
is generated in the digestive system of ruminant livestock as microbes
break down feed, and is mostly expelled via belching.
Manure management
CH4 and N
2
O are emitted during storage and treatment of manure, where
anaerobic conditions produce methane, and microbial processes release
nitrous oxide from nitrogen compounds.
Land preparation
and Pumping
Emissions (CO
2
e) due to fossil fuel consumption for land preparation and
pumping.
1.3. HISTORICAL TRENDS IN NON-ENERGY EMISSIONS FROM
AGRICULTURE SECTOR
Methane Emissions from Rice Cultivation
Methane (CH₄) emissions from rice cultivation is due to methanogenesis, driven by anaerobic
soil conditions and flooded water regimes. As a result, overall rice emissions in India are driven
by two factors: the spatial extent (acreage) of rice cultivation and the rice water-management
regimes (MoEFCC, 2022). While rice production increased between 2011 and 2019, emissions Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 7
Introduction
from rice cultivation remained broadly stable (Figure 1.7). This stabilisation reflects consistent
water management practices with potential shifts in space. While conventional flooded systems
persist in states such as Punjab, Haryana, West Bengal and Rajasthan, water-scarce states such
as Tamil Nadu and Karnataka have increasingly adopted Alternate Wetting and Drying (AWD)
and aerobic rice systems. These sustainable rice cultivation practices reduce methane emissions
by ~48% (Annexure III) per hectare (emission intensity) offsetting emission pressures from
productivity-led intensification.
Emissions (MtCO
2
e)
Historical rice emissions (MtCO
2
e) (2011-2019)
150
100
50
0
Year
20112013201520172012201420162018 2019
7373 73 72 71 74 74 7371
Figure 1.7: Historical trends of emissions from rice cultivation (AR2) (2011-2019) (MoEFCC, 2022)
Nitrous Oxide (N2O) Emission from Agricultural Soils
N
2
O emissions from agricultural soils in India are primarily driven by two factors: nitrogen
application rates
2
per cropping cycle (kg/ha) – including both synthetic fertilisers and organic
inputs – and cropping intensity (number of cropping cycles per year – GCA/NSA), which
determines how frequently nitrogen is applied per hectare in a year (IPCC, 2014).
1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.5
1.5
3.0
2.0
1.0
0.0
Cropping intensity (GCA/NSA)
Year
Cropping intensity (GCA/NSA) (2011-2019)
2011 2012 2013 2014 2015 2016 2017 2018 2019
Figure 1.8: Trends of cropping intensity (2011-2019)
2 Rate of application of nitrogen refers to the amount of nitrogen inputs applied per ha (kg/ha). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 8
Introduction
25
20
15
10
5
0
Nitrogen consumption
(in million tonnes)
Nitrogen fertiliser consumption (million tonnes) (2011-2019)
17.3
16.8 16.8 16.9
17.4
16.7 17.0
17.6
19.1
Year
20112013201520172012201420162018 2019
Figure 1.9: Total nitrogen fertiliser consumption (2011-2019)
Emissions from agricultural soils (MtCO
2
e) (2011-2019)
200
150
100
50
0
20112013201520172012201420162018 2019
Emissions (MtCO
2
e)
Year
82
80 80 81 80 78
81 84
88
Figure 1.10: Emissions from agricultural soils (AR2) (2011-2019)
India is one of the world’s largest consumers of synthetic fertilisers with an average application
rate of ~140 kg of total nutrients (N + P
2
O
5
+ K
2
O) per hectare per cropping cycle (FAI, 2024).
However, nutrient application is heavily skewed toward nitrogen, with an N:P:K ratio of 10.9:4.4:1
indicating significant overuse of nitrogen relative to others (FAI, 2024). As a result, agricultural
soils emissions in India rose by ~7% from 82 to 88 MtCO
2
e between 2011 and 2019 (Figure 1.10).
This was in parallel to a 10.4% increase in overall fertiliser consumption from ~17 to 19 million
tonnes (FAI, 2024) (Figure 1.9). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 9
Introduction
The rise in fertiliser consumption can be attributed to two main factors. First, cropping intensity
increased from ~139% to ~151% between 2011 and 2019 Figure 1.8), driven by expanded irrigation
under Pradhan Mantri Krishi Sinchai Yojna (PMKSY). Second, declining Nitrogen Use Efficiency
(NUE) (Singh, 2023) led to higher per-hectare nitrogen application, which rose from ~88.5
to ~90.4 kg/ha over the same period (FAI, 2024). Nitrogen use from organic sources also
grew by ~1.44%, further increasing soil emissions. While programs like the Paramparagat Krishi
Vikas Yojana (PKVY) and the National Mission on Natural Farming (NMNF) promote organic
alternatives that reduce emissions, their adoption remains limited (<3% of cropland) (NITI
Aayog, 2024), suggesting that these emission trends may persist.
Livestock Emissions: Enteric fermentation (CH₄) and Manure Management (N
2
O + CH₄)
The emissions in the livestock sector are driven by methane from enteric fermentation and by
methane and nitrous oxide from manure management. Bovine animals, cattle and buffaloes,
are the dominant source of livestock emissions, accounting for ~82%
3
of livestock emissions in
2019. Given this dominance of bovine animal emissions in the livestock sub-sector, this analysis
focuses specifically on bovine-related emissions.
Milk production rose by ~55% between 2011 and 2019, growing from ~128 million tonnes to ~198
million tonnes (Figure 1.11). However, emissions from the livestock sector showed a moderate
growth of only 2.23%, from ~246 MtCO
2
e to ~251 MtCO
2
e (Figure 1.12).
200
150
100
50
0
Historical milk production (million tonnes) (2011-2019)
Year
20112013201520172012201420162018 2019
Total Milk (million tonnes)
128
132
138
146
155
165
176
188
198
Figure 1.11: Historical milk production (DAHD, 2018, 2019, 2023)
3 (Authors’ analysis based on MoEFCC 2021) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 10
Introduction
Historical emissions from livestock sub-sector (MtCO
2
e) (2011-2019)
Year
20112013201520172012201420162018 2019
Livestock emissions (MtCO
2
e)
300
200
100
0
246 249
252 255
250 250 250 251 251
Figure 1.12: Historical livestock emissions (AR2) (2011-2019) (MoEFCC, 2021)
Such stabilisation trends in livestock emissions are primarily driven by (i) an increase in bovine
productivity (Figure 1.4) and (ii) the displacement of male animals by and with the increasing
female population, keeping the total bovine population stable so far (Figure 1.5). 2
METHODOLOGY Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 12
2
Methodology
aa
2.1 APPROACH TO ESTIMATING MITIGATION CO-BENEFITS OF
NON-ENERGY AGRICULTURAL PATHWAYS
As mentioned in the Background, this report has taken a “differentiated” approach than what
is adopted in other sectoral reports in this series. It focuses on adaptation-first pathways that
support livelihoods and food and nutritional security, and assesses their corresponding abilities
in generating mitigation co-benefits. However, this requires integrated frameworks that address
synergies and trade-offs across different time scales (IPCC 2019). This analysis is limited to
supply-side, production-oriented, scenario-based modelling of agricultural emissions.
This section details the report’s approach followed to:
1. Production projections: Compile historical and baseline (2019) production data for
crops and livestock, and project production trajectories for eight major crops and milk
through 2070.
2. Emissions assessment: Estimate sectoral greenhouse gas emissions from crops and
livestock through 2070, based on projected production pathways.
3. Policy pathway analysis: Develop two long-term policy pathways—the Current Policy
Scenario and the Net Zero Scenario—aligned with resilience, farmer incomes, and food
and nutritional security, and assess and quantify associated mitigation co-benefits
Figure 2.1 shows the methodology for estimating future emissions from non-energy use. It
uses 2019 as the baseline year and employs an annual time-step model
4
to project emissions
trajectories from 2020 to 2070, with intermediary milestones of 2047
5
.
Figure 2.1: Agriculture emission modelling methodology
4 An annual time-step model projects year-by-year changes by updating key variables and recalculating emissions each year.
5 India’s timeline to become a developed nation,Viksit Bharat, on the occasion of centenary year of Independence
Step 1Step 2Step 3
Production
projections
Emission
estimations
Development of Current policy
scenarios and Alternative pathways
Crop Husbandry,
Agriculture Inputs,
Demand and Supply
2047 report,
2019-2047
Projections
extended from
2047-2070
Country specilic
emission factors from
IRCC tier 1 and tier 2
methodologies
Policy
identification
Policy typology
development
Scenario
identification
Participatory
scenario
development Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 13
Methodology
Step 1: Compiling historical and baseline (2019) production data for crops and
livestock and projecting future production for 8 major crops and milk.
Consistent with the supply-side scope of this analysis, agricultural emissions are modelled using
production projections of nine key food commodities - for 8 major crops
6
and milk.
a. For the period 2021–2047, production projections are directly adopted from NITI
Aayog’s “Crop Husbandry, Agriculture Inputs, Demand and Supply” (2024), which
applies a time-series methodology grounded in historical area, production and yield
trajectories (see Box 2).
b. For the period 2048–2070, production projections are extended from the 2047
endpoints using the methodology adopted in the NITI Aayog (2024) report, ensuring
continuity and methodological consistency through 2070.
Box 2: Methodology followed for Forecasting the Production
of Food Commodities
The Working Group Report on Crop Husbandry, Agriculture Inputs, Demand and Supply,
Report of 2024 of NITI Aayog assess trends in demand and supply of food commodities,
inputs, and feasible levels of exports through 2047. The report uses four forecasting
methods for projecting supply/production based on historical trends of change. They
are: a) Autoregressive Integrated Moving Average (ARIMA), b) Artificial Neural Network
(ANN), c) Holt’s smoothing, and d) the exponential growth rate model (based on the
past 10 years).
Step 2: Emission estimations through 2070
Emissions are estimated using the IPCC Tier 1
7
and Tier 2
8
methodologies (Table 2.1). These
estimates incorporate country-specific emission factors across five emission categories within
the agricultural sector (Table 2.2). Methane (CH₄) and nitrous oxide (N₂O) are the dominant
greenhouse gases in this sector; their emissions are therefore expressed in carbon dioxide
equivalents (CO₂e) using 100-year Global Warming Potential (GWP) values of 28 for CH₄ and
265 for N₂O, as reported in the IPCC’s Fifth Assessment Report (AR5). The baseline year for
emissions projections is 2019, consistent with emissions reported in India’s Third National
Communication. To ensure methodological consistency across the analysis, historical 2019
emissions were converted from AR2 to AR5 GWP values.
6 Major eight crops are considered as they contribute directly to GHG emissions from the sector. These are: Rice,
Wheat, Cotton, Jute, Rapeseed and Mustard, Maize, Sugarcane and Nutri-cereals
7 Tier 1 methodology uses IPCC default emission factors and general activity data; suitable for countries with limited
data
8 Tier 2 methodology uses country-specific emission factors and detailed activity data. It requires better-quality
national information and captures local conditions more effectively (India mostly uses Tier 2) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 14
Methodology
Table 2.1: Emission estimation methodology for various categories considered for the
agriculture sector (MoEFCC, 2021)
Sector/CategoryGas Method Used Emission Factor
Enteric FermentationCH
4
T1, T2D, CS
Manure Management
CH
4
T1D
N
2
OT1D
Rice CultivationCH
4
T2CS
Agricultural SoilsN
2
OT2CS
Field Burning of Agricultural Residues
CH
4
T1D
N
2
OT1D
Notation/Legend: T1: Tier 1; T2–Tier 2; CS–Country specific emission factors; D–IPCC Default emission factors
Table 2.2: Emission estimation methodology for various categories considered for the
agriculture sector
Emission
Category
GHG Emission
Type
Emission Estimation Methodology
Livestock
emissions
Enteric
fermentation
(CH
4
)
To estimate livestock emissions from 2020 to 2070, bovine
populations were projected (82% of total livestock emissions in
2019) using milk production projections. In-milk and non-in-
milk animal numbers were derived from productivity trends and
historical trends of herd composition. Emissions were computed
by applying country-specific emission factors to these population
categories (species type and dairy and non-dairy cattle based
on their ages) as indicated in Annexure I. Given the limited
contributions of the non-bovine animals, these emissions are
assumed to remain constant at 2019 levels through 2070.
Manure
Management
(N
2
O, CH
4
)
Rice
emissions
Methane
emissions (CH
4
)
Between 2011 and 2019, rice cultivation in India maintained a stable
emission intensity of 2.11 MtCO
2
e/ha over 44 million hectares,
reflecting consistent aggregate water management practices
(Annexure I). Future emissions are projected by applying this
emissions intensity to anticipated rice cultivation areas, assuming
aggregate water regimes remain unchanged unless specified.
Agricultural
soil
emissions
Nitrous oxide
emission (N
2
O)
based on soil
activity
Agricultural soil (N
2
O) emissions, categorised as direct and indirect,
are estimated based on projections of total nitrogen consumption
from both synthetic and organic fertilisers. Appropriate emission
factors are applied to estimate emissions from agriculture soils are
estimated by summing direct and indirect emissions (Annexure I)
Agricultural
Waste
Biomass
(AWB)
Emissions from
crop residue
burning (N
2
O,
CH
4
)
Crop residue burning represents a source of CH₄ and N
2
O
emissions and which is estimated based on the amount of crop
residue burnt. Crop residue burnt is estimated using residue crop
ratios, dry matter content, and combustion efficiency
9
for each of
the eight major crops. CH₄ and N
2
O emission factors were applied
to the estimated biomass burnt to compute agricultural waste
burning (AWB) emissions from 2020 to 2070 (Annexure I).
Note: The Annexure I provides detailed country-specific emission factors used across the five categories of emissions.
9 Median state-level combustion efficiency was used for rice, while national average values were applied for other crops Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 15
Methodology
Step 3: Development of Current Policy Scenario (CPS) and Net Zero Scenario (NZS)
Two policy pathways: the Current Policy Scenario and the Net Zero Scenario—were developed
to generate long-term emissions projections for India’s agriculture and allied sectors. These
pathways are structured around four food system based policy typologies and nine key
interventions as in Table 2.3 & 2.4 and Annexure II.
Current Policy Scenario: This scenario considers the effective implementation of
prevailing/current agricultural policies in India. It assumes policy implementation rates
across various interventions that help to achieve the intended ambitions of existing
government policies.
Net Zero Scenario: This scenario envisions a transformative outcomes characterized by
accelerated adoption of existing and new agricultural policies beyond the Current Policy
Scenario. Consequently, the pathway is framed around to identify those interventions
which will improve farmers’ income, farm productivity and strengthen climate change
resilience with potential mitigation co-benefits.
The list of various such possible interventions and their corresponding mitigation co-benefits
is provided in Table 2.3. Assumptions underpinning both scenarios (Table 2.4), were developed
through an iterative, multi-stakeholder consultation process involving over 30 experts. These
assumptions reflect historical rates of policy penetration, the ambition embedded within the
current policy framework, and desirable future pathways. Any pathway-induced changes in
production are translated into corresponding mitigation co-benefits.
The list of various such possible interventions is provided in Table 2.3.
Table 2.3: Policy typologies mapped against their potential mitigation co-benefits
Sl.
No
Implementation
pathway
Relevant schemes Parameter of
change
Primary outcomes
achieved
Potential
impacts
on GHG
emissions
Sustainable agricultural production
1Sustainable
yield
intensification
Pradhan Mantri
Krishi Sinchai
Yojna (PMKSY);
Micro Irrigation
Fund; Sub-mission
On Agriculture
Mechanisation
(SMAM); Rainfed
Area Development
Enhance output per
ha (kg/ha)
1. Farmer livelihood
through
enhanced farm
incomes
2. Enhance food
security
3. Building adaptive
capacity of
farmers against
the impacts of
climate shocks
Reduced
emission
intensity per
ha (CO
2
e/ha)
2Crop
diversification
Crop Diversification
Programme
(CDP)
10
;
Horticulture
Mission; Mission on
Edible oils, Pulses
and Nutri-cereals
(millets)
1. Input efficiency
(kg/ha or lt/ha)
2. Soil health
enhancement
3. Climate resilience
4. Diversified
plate (kcal
restructuring)
1. Farm resilience
against climate
and market
shocks
2. Farm profitability
3. Food and
Nutritional
Security of India
Reduced
emission
intensity per
ha (CO
2
e/ha)
10 Rashtriya Krishi Vikas Yojna (RKVY) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 16
Methodology
Sl.
No
Implementation
pathway
Relevant schemes Parameter of
change
Primary outcomes
achieved
Potential
impacts
on GHG
emissions
3Cropping
intensity
Pradhan Mantri
Krishi Sinchayee
Yojna (PMKSY-
MI); Accelerated
Irrigation Benefits
Programme (AIBP)
Enhanced output
(kg/ha/year)
1. Farmer livelihood
through
enhanced due
unlocking more
cropping cycles
2. Food security
3. No net increase
in Net sown area
Reduced
emissions per
output (CO
2
e/
kg)
Sustainable Livestock Production
4Sustainable
Yield
Intensification
(SYI)
National Livestock
Mission (NLM);
Ration Balancing
Programme (RBP)
Enhanced milk
output per animal
per day (lt/day/
animal)
Feed efficiency
improvement
(kgfeed/lt)
1. Enhanced
income
2. Food and
nutritional
security
3. Adaptive
capacity of
farmers against
shocks
4. Reduced
overall animal
population
(millions)
Reduced
emission
intensity
(CO
2
e/ animal/
day)
5Livestock health
management
National Livestock
Mission (NLM);
Rashtriya Gokul
Mission (RGM)
1. Enhanced
reproductive
health of
livestock
2. Climate resilience
(Singh et al,
2017)
1. Reduced costs
of livestock
maintenance at
the farmer level,
enhancing the
profitability per
herd
Reduced
overall
emissions
from livestock
Sustainable Agricultural Practices
6Natural and
Chemical-free
farming
National Mission
on Natural
Farming (NMNF);
Paramparagat
Krishi Vikas Yojna
(PKVY); Soil health
card scheme; PM–
PRANAM; Green
credits; Neem-
coated urea
1. Input efficiency
(kg/ha of L/ha)
2. Soil health (SOC)
3. Climate resilience
4. Agro-biodiversity
1. Long-term yield
sustainability
2. Long-term
livelihood
security
4. Farm resilience
5. Nutritional
security
Reduced
nitrous oxide
emissions from
the reduction
in application
of chemical
fertilisers
7Enhance Fertiliser
uptake/use
efficiency (FUE)
Neam-coated urea;
Integrated Nutrient
Management (INM)
1. Input efficiency
(kg input/ kg
output)
2. Soil health
protection
3. Overall reduction
in the use of
fertiliser
1. Long-term yield
sustainability
2. Food security
Reduced
nitrous oxide
emissions per
kg output,
improving
the emission
intensity of
production Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 17
Methodology
Sl.
No
Implementation
pathway
Relevant schemes Parameter of
change
Primary outcomes
achieved
Potential
impacts
on GHG
emissions
8Sustainable Rice
Cultivation (SRC)
practices
Bringing Green
Revolution to
Eastern India
(BGREI)
1. Water use
efficiency (lt/ha)
2. Water stress
management
3. Climate resilience
1. Farm income
stability
2. Climate resilience
Up to 59%
reduction
in methane
emissions from
rice fields
(Annexure III)
Circular Bioeconomy
9Agriculture Waste
Burning
Crop residue
management
under RKVY
9
;
BioE3 Policy
1. Diversified farm
incomes
2. Climate action
3. Soil health
management
4. Enhanced
bioeconomy
1. Farmer
livelihoods
2. Reduced air
pollution
Reduced
methane and
nitrous oxide
emissions from
the burning of
biomass
Table 2.4: Key assumptions for 2047 and 2070
Policy
typology
Scenarios
Number
Interventions Unit Current
status
for the
baseline of
2019
Current
Policy
Scenario
Net Zero
Scenario
2047207020472070
1. Sustainable
agriculture
production
1.1
Cropping
intensity
% GCA
(ha)/ NSA
(ha)
151 160 165170180
1.2
Crop
diversification
away from rice,
wheat and
sugarcane
% area
shifting
from rice,
wheat and
sugarcane
0.23
(2019)
10 15 15 20
1.3
Sustainable
Yield
Intensification
(SYI)
% reduction
in yield
gap
11
0 (66%
yield gap)
15 20 40 70
2. Sustainable
agriculture
practices
2.1
Natural and
Chemical-free
farming
% net sown
area6 15 20 20 25
2.2
Fertiliser uptake
efficiency (FUE)
% of kg of
nutrient
uptake /kg
of fertiliser
applied
33 38 40 45 50
2.3
Sustainable
Rice Cultivation
(SRC) practices
% of area
under rice 0.25 10 20 18 25
11 Yield gap for crops is defined as the difference between the current attainable yield and the average yield achieved
in India. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 18
Methodology
Policy
typology
Scenarios
Number
Interventions Unit Current
status
for the
baseline of
2019
Current
Policy
Scenario
Net Zero
Scenario
2047207020472070
3. Sustainable
livestock
production
3.1
Enhanced in-
milk bovine
productivity
kg/head/
day5.27 8 12 12 15
3.2
Share of the In-
milk population
% in-milk in
total bovine
population
30 40 45 45 55
4. Circular
bio-
economy
4.1
Reduced
burning of crop
residue
% reduction
in crop
residue
burnt
0 20 30 40 60
Note: Annexure II contains a detailed policy mapping and assumptions behind the Scenarios presented
in the above table.
Each parameter shown in the table is described subsequently.
Scenario 1.1: Cropping Intensity
Cropping intensity refers to the number of crops grown on the same field during one
agricultural year. Recent data shows that the national average cropping intensity in India is
~155% (Agriculture Statistics, 2023), meaning cropland is cultivated approximately 1.55 times
annually. This represents a gradual increase from ~140% in the early 2010s (Sharma, 2023) due
to the implementation of Pradhan Mantri Krishi Sinchayee Yojana (PMKSY) and Rashtriya Krishi
Vikas Yojana (RKVY) since 2015.
Increasing cropping intensity boosts food production per unit area, increases farm incomes,
and potentially reduces agriculture land expansion. Concurrent scaling of agroecology and soil
management practices through National Mission on Natural Farming (NMNF), Soil Health Cards
(SHC), and Pradhan Mantri Krishi Vikas Yojna (PKVY) is crucial to prevent risks of unsustainable
intensification, notably soil degradation through over-fertilisation and water table depletion
from over-extraction. Increasing cropping intensity is expected to lead to higher GHG emissions
per hectare, but lower GHG emissions per output.
In the Current Policy Scenario, cropping intensity is projected to increase to 160% in 2047 and
165% in 2070. In Net Zero Scenario, it is projected to increase to 170% in 2047 and 180% in
2070 (Table 2.4a).
Table 2.4a: Assumptions of cropping intensity in Current Policy Scenario and Net Zero
Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Cropping intensity % GCA / NSA
(in ha)
151 160 165 170 180 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 19
Methodology
Scenario 1.2: Crop diversification
Mitigation “co-benefits” from the GoI’s Crop Diversification Programme (CDP) under Rashtriya
Krishi Vikas Yojana (RKVY), which has led to diversification of 1.02 lakh ha (0.102 Mha) away
from water-intensive crops (rice and tobacco), stood at 0.214 MtCO2e between 2019-24
(MoEFCC, 2024).
Crop diversification is a strategy in which farmers shift away from rice, wheat, or sugarcane-
dominated monoculture systems toward high-value crops (horticulture, oilseeds etc) or nutri-
cereals crops as a climate adaptation strategy. This transition can enhance farm incomes by
reducing risk and increasing value per hectare and enhance nutritional security (Barman et
al, 2022). This transition also yields relative mitigation co-benefits, as Greenhouse Gas (GHG)
emissions per hectare decline when farmers shift from input-intensive monoculture systems to
more diversified cropping systems.
Crop diversification pathways must consider implications for food security and farm incomes,
in both the short and long term. The analytical snapshot, given in Annexure VI, evaluates the
feasibility of diversifying away from rice to nutri-cereals as an example, identifies potential
leading states and outlines a short-term roadmap to facilitate this transition.
In the Current Policy Scenario, ~10% of the cropped area is assumed to be diverted from rice,
wheat and sugarcane by 2047 and ~15% by 2070%. In Net Zero Scenario, the corresponding
numbers are ~15% by 2047 and ~20% by 2070 (Table 2.4b).
Table 2.4b: Assumptions of area-based crop diversification in Current Policy Scenario and
Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero Scenario
2047 2070 2047 2070
Area-based crop
diversification away
from rice, wheat and
sugarcane
% area shifting
from rice, wheat
and sugarcane
0.23
(2019)
10 15 15 20
Scenario 1.3: Sustainable Yield Intensification
Sustainable Yield Intensification (SYI) refers to enhancing crop productivity per unit of arable land
through agronomic, ecological, and technological interventions without degrading environmental
quality or depleting natural resources. In this report, Sustainable Yield Intensification (SYI) focuses
on narrowing yield gaps relative to current realisable yields through technological upgrades and
resource-efficient practices, including site-specific nutrient management and climate and stress-
tolerant, high-yielding crop varieties promoted and developed under the National Innovations
in Climate Resilient Agriculture (NICRA), among others. Given that yield gaps for major crops
such as rice, wheat, maize, and sugarcane range between 66% and 75%, narrowing these gaps
is critical to meeting rising food and biomass demands while addressing the “land squeeze”
from competing uses such as bioenergy and fiber production. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 20
Methodology
In the Current Policy Scenario, ~20% yield gap will be bridged by 2070. In Net Zero Scenario,
the corresponding scenarios are 70% by 2070 (Table 2.4c).
Table 2.4c: Assumptions of sustainable yield intensification in Current Policy Scenario and
Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Sustainable yield
intensification (SYI)
% reduction in
yield gap
12
0 (66%
yield gap)
15 20 40 70
Scenario 2.1: Natural and Chemical-free farming
Natural and Chemical-free farming encompasses agroecological practices that eliminate or
replace synthetic chemical inputs with bio-based alternatives, relying on ecological processes
to maintain soil fertility, manage pests, and sustain crop productivity. This report explores
long- term scenarios for scaling the adoption of natural and chemical-free farming, focusing
on natural
13
and organic farming systems
14
, which currently cover 6% of India’s Net Sown Area
(NSA)
15
. The analysis is situated within key policy initiatives, including the Paramparagat Krishi
Vikas Yojana (PMKY) and the National Mission on Sustainable Agriculture (NMSA). In light of
recent policy momentum with the announcement of the National Mission on Natural Farming
(NMNF), which aims to scale natural farming to ~7.5 lakh hectares of net sown area, Annexure
VI (Part 2) presents a framework for scaling chemical-free practices. While large-scale adoption
of natural farming and agroecological practices offers significant long-term environmental and
cost benefits, perceived short-term yield risks under certain conditions may constrain adoption
and must be carefully managed to safeguard food security (Kumar et al, 2020). As a result,
under the Current Policy Scenario, natural and chemical-free farming, currently covering less
than 5% of the net sown area, is assumed to expand to 20% by 2070, increasing further to 25%
under the Net Zero Scenario by 2070) (Table 2.4d).
12 Yield gap for crops is defined as the difference between the current attainable yield and the average yield achieved
in India.
13 Natural Farming is a system rooted in agroecological principles that integrates crops, trees and livestock with
functional biodiversity. It is largely based on on-farm biomass recycling with major stress on biomass mulching, use
of on-farm cow dung-urine formulations; maintaining soil aeration and exclusion of all synthetic chemical inputs.
Natural farming is expected to reduce dependency on purchased inputs. It is considered as a cost- effective farming
practice with scope for increasing employment and rural development.
14 Organic farming systems’ focus is on using naturally available resources as inputs, such as organic wastes (crop,
animal and farm wastes, aquatic wastes) and other biological materials along with beneficial microbes (biofertilisers/
bio control agents) to release nutrients to crops and protect them from insect pest and diseases for increased
agricultural production.
15 Stakeholder consultations Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 21
Methodology
Table 2.4d: Assumptions of chemical-free farming in Current Policy Scenario and Net Zero
Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Natural and Chemical-
free farming
% net sown area 6 15 20 20 25
Scenario 2.2: Fertiliser Uptake Efficiency
Mitigation “co-benefits” achieved through adoption of 134.05Mt neem-coated urea as a
measure to improve FUE stood at 26.81 MtCO2e between 2019-24 (MoEFCC, 2024).
Fertiliser Uptake Efficiency (FUE) measures how effectively crops utilise applied fertilisers, and
is calculated as the ratio of crop output to fertiliser used. In India, FUE has declined, with
Nitrogen Use Efficiency (NUE) having dropped from 48% in the 1960s to 35% in 2018 (Singh,
2023) due to increased reliance on synthetic fertilisers. This report explores long-term scenarios
for the likely effects of initiatives like Soil Health Management (SHM) and the mandate for 100%
neem-coated urea to improve FUE. As a result, Fertiliser use efficiency is assumed to increase
to 40% by 2070 in Current Policy Scenario and 50% by 2070 in Net Zero Scenario (Table 2.4e).
Table 2.4e: Assumptions of fertiliser uptake in Current Policy Scenario and Net Zero
Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Fertiliser uptake % of kg of nutrient
uptake/kg of
fertiliser applied
33 38 40 45 50
Scenario 2.3: Sustainable Rice Cultivation Practices
Mitigation “co-benefits” of the adoption of System of Rice Intensification (SRI) and Direct
Seeded Rice (DSR) rice cultivation practices across 1.11 lakh ha (0.11 Mha) stood at 0.19
MtCO2e between 2019-24 (MoEFCC, 2024).
Sustainable Rice Cultivation (SRC) refers to agronomic practices that can enhance water
efficiency and reduce input costs in paddy cultivation, which accounts for 40% of India’s
irrigation water use. Key techniques like Alternate Wetting and Drying (AWD), System of
Rice Intensification (SRI), Subsurface Irrigation (SI), and Drip Irrigation (DI) can reduce water
use by 30–40% while maintaining or improving yields. These practices also promote aerobic
conditions in the paddy fields, reducing the methane emissions. This report models long-term
scenarios for scaling Sustainable Rice Cultivation (SRC) given its strong water-saving potential
and climate mitigation co- benefits. Annexure III contains the mitigation potentials of various
SRCs in different states of India. Under the Current Policy Scenario, sustainable rice cultivation
practices is assumed to increase to 20% of rice area by 2070 and under the Net Zero scenario
the same will increase to 25% of rice area by 2070 (Table 2.4f). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 22
Methodology
Table 2.4f: Assumptions of sustainable rice cultivation practices in Current Policy Scenario
and Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Sustainable rice
cultivation practices
% of area under
rice
0.25 10 20 18 25
Scenario 3.1: Milk Productivity in Bovine Animals
Mitigation “co-benefits” of the adoption of the Ration Balancing Programme (RBP) stood at
0.0205 MtCO2e during 2019-24 for 1.63 lakh/163 thousand animals (MoEFCC, 2024)
Milk productivity refers to the average daily milk output of lactating animals. It is influenced
by several interrelated factors such as quality and quantity of feed and fodder, genetic
potential of the breed, animal health status, and regional agro-climatic conditions. Enhancing
milk productivity is critical for growing milk production without a proportional increase in the
bovine population. This, in turn, would moderate the sector’s greenhouse gas emissions. Recent
policy initiatives on animal health and nutrition, such as the Ration Balancing Programme (RBP),
Rashtriya Gokul Mission (RGM) and the adoption of innovative feed additives like Harit Dhara,
exhibit the potential to significantly increase milk yields across breeds.
Under the Current Policy Scenario, bovine productivity is assumed to increase from 5.27 to 12
kg/head/day by 2070 and 15 kg/head/day by 2070 in Net Zero Scenario (Table 2.4g).
Table 2.4g: Assumptions of enhanced in- milk bovine productivity in Current Policy
Scenario and Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Enhanced in- milk
bovine productivity
kg/head/day 5.27 8 12 12 15
Scenario 3.2: Share of In-Milk Population
In-milk adult female bovine animals refer to those cows and buffaloes that are actively lactating
and producing milk. The share of in-milk animals increases with a higher proportion of female
bovines in the herd and, within this group, a greater proportion of animals in lactation. For the
former, techniques like sex-sorted semen, which increase the probability of getting a female calf,
can be explored. For the latter, enhancing animal breed quality, nutrition, and health can extend
lactation periods, thereby improving the proportion of in-milk animals. Practices like deworming
can further improve nutrient absorption and reproductive health, while regular vaccination can
prevent reproductive infections (NAAS, 2013). Estrus detection and synchronisation techniques
to ensure timely insemination significantly improve conception rates and reduce calving intervals
(Mishra and Tiwari, 2014). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 23
Methodology
Under the Current Policy Scenario, in-milk bovine population is to assumed to increase in share
from 30% in 2019 to 45% by 2070 and 55% by 2070 in Net Zero Scenario (Table 2.4h).
Table 2.4h: Assumptions of increasing share of the in-milk population in Current Policy
Scenario and Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Share of the In- milk
population
% in-milk in
total bovine
population
30 40 45 45 55
Scenario 4.1: Reduced Crop Residue Burning
Mitigation “co-benefits” of the Crop Residue Management scheme (CRM) implemented under
Rashtriya Krishi Vikas Yojana (RKVY) aimed to reduce crop residue burning through ex-situ
management stood at 1.447 MtCO2e between 2019-24 (MoEFCC, 2024).
Crop residue refers to plant material, such as straw and stubble, that is left after harvesting.
In some parts of the country, for certain crops, some of this residue is burned to quickly clear
fields cost-effectively. This exacerbates air pollution and greenhouse gas emissions while wasting
valuable biomass. India generates around 140 tonnes of surplus crop residue annually, of which
92 tonnes are burnt (Bhuvaneshwari,2019). This report estimates the percentage reduction in
residue burning in the backdrop of the Crop Residue Management (CRM) scheme, exploring
long-term scenarios for significant reductions by 2050 and near elimination by 2070.
Under the Current Policy Scenario, crop residue burning is to assumed to decrease by 30% in
2070 and 60% by 2070 in Net Zero Scenario (Table 2.4i).
Table 2.4i: Assumptions of reduced burning of crop residue in Current Policy Scenario and
Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Reduced burning of
crop residue
% reduction in
crop residue
burnt
0 20 30 40 60
2.2 ENERGY DEMAND ESTIMATIONS FOR AGRICULTURE
The energy demand modelling framework consists of two modules: (i) irrigation pumping and
(ii) land preparation, tracing the pathway from key drivers to final energy use based on the
crop production projections.
1. Irrigation Module: estimates energy demand for pumping by linking crop demand
projections with irrigation water requirements, pump stock and efficiency parameters
As shown in Figure 2.2, the methodology starts with projected demand for major Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 24
Methodology
crops, which is converted into total cultivated area and then split into irrigated and
rainfed portions.
Irrigated crop area is transformed into irrigation water requirement using crop-specific
water productivity (kg/m³). In this study, only the pump-dependent share of this water
is carried forward to estimate total energy demand for irrigation water pumping.
Pumped water demand is converted into pump stock and finally into energy demand
using assumptions on pump discharge, operating hours, dynamic head, technology
mix, and pump efficiency,.estimates pumping energy demand by linking crop demand
projections with irrigation water requirements, pump stock and efficiency parameters
(Figure 2.2). A detailed methodology is given in Annexure IV.
Crop Demand
(million
tonnes)
Rice
Wheat
Maize
Arhar
Gram
Groundnut
Rapeseed &
Mustard
Sugarcane
Cotton
Share of
Irrigation
Irrigated
Crop
Demand
Water
Coefficient
(kg/m
3
)
Pumping
Water
Demand
Number of
Pumps
Pumping
Energy
Demand
Water Coefficient
*kg/m
3
)
Share of
Pumping
Average Discharge rate,
Dynamic Head, and
Funcitoning Hours
Technology Share of
Water Pumped +
Efficiency of Pumps
Figure 2.2: Irrigation module for energy demand projections
2. Land Preparation Module: As shown in Figure 2.3, Land-preparation energy demand
is estimated by projecting Gross Cropped Area (GCA) and applying the assumed
mechanisation rate to derive the area prepared using tractors and power tillers.
This mechanised area is allocated between tractors and tillers using a conservative
equivalent land-coverage assumption (tractor:tiller contribution based on operating-
capacity conversion). Finally, specific energy intensity factors (operating hours/ha ×
fuel use/hour) are applied to each area segment and aggregated to obtain total final
energy demand. A detailed methodology is given in Annexure V.
Gross
Cropped Area
Level of
Mechanisation
Land prepared
through
tractors and
tillers
Fuel
Consumption
Parameters
Final Energy
Demand
Figure 2.3: Land preparation module for energy demand projections Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 25
Methodology
To analyse the long-term energy demand of India’s agriculture sector, two alternate pathways
are assessed up to 2070: Current Policy Scenario and Net Zero Scenario. Both scenarios assume
the same crop production trajectories as developed in Figure 3.1, but differ in how this demand
is met in terms of energy use.
Assumptions for Irrigation Energy Consumption
Irrigation is the dominant source of agricultural energy use. Under the Current Policy Scenario,
irrigated share of cropped area rises steadily, groundwater dependence deepens, and diesel
pumps decline only gradually. Pump efficiency improves slowly, and solar adoption remains
limited. Under the Net Zero Scenario, in contrast, efficient irrigation practices (drip, sprinkler)
reduce water demand substantially, diesel pumps are phased out by 2035, and solar pumps
dominate by 2070 with much higher efficiencies (Table 2.5).
Table 2.5: Assumptions for estimating energy consumption for irrigation under Current
Policy Scenario and Net Zero Scenario
Scenarios 2020 Current
Policy
Scenario
(2070)
Net Zero
Scenario
(2070)
Notes
Irrigated share of
Gross Cropped
Area
53% 65% 60%
FAO (2021) notes that India already
leads globally in irrigated area;
future increases constrained by
water stress.
Groundwater/
Pumping share
65% 65% 60%
India remains heavily groundwater-
dependent in comparison to the
US (15%) and China (40%). Net
Zero Scenario assumes investments
in canal systems and recharge.
Water
Productivity
Improvement
+10 +25%
Net Zero Scenario assumes large-
scale drip/sprinkler adoption
(Sharma et al, 2018) assuming that
drip can halve water needs for
sugarcane/vegetables.
Share of Solar
Pumps
2% 40% 60% Diesel pump phase out by 2040
in Current Policy Scenario and by
2035 in Net Zero Scenario.
Share of Electric
Pumps
70% 60% 40%
Pump efficiency
(Solar & Electric)
36% 40% 50% Reflects best practices (EMC
2018).
Pumping Head
(metre)
28 50 35 Net Zero Scenario assumes aquifer
recharge and efficiency to prevent
sharp rise. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 26
Methodology
Assumptions for Land Preparation Energy Demand
Both scenarios assume full mechanisation by 2047, driven by rising rural wages and declining
farm labour. Differences lie in the energy profile: under the Current Policy Scenario, electric
tractors and tillers dominate with small amount of diesel and Compressed Natural Gas (CNG)
even by 2070. While in the Net Zero Scenario, there is almost 100% shift toward electric
tractors and tiller with higher share of tillers in land preparation compared to Current Policy
Scenario. (Table 2.6).
Table 2.6: Assumptions for estimating energy demand for land preparation under Current
Policy Scenario and Net Zero Scenario
Scenarios 2019
2070
Current Policy
Scenario
2070
Net Zero
Scenario
Notes
Mechanisation level 47% 100% 100% Tillers gain share as
smallholder mechanisation
expands.Tractor:tiller split 95:5 70:30 50:50
Energy intensity
per ha (MJ/ha) (%
reduction in energy
intensity)
Tractors:880
Tillers: 960
–20% by
2070
–40%
Fuel Consumption
in Land Preparation100% diesel
9% diesel,
8% CNG,
83% electric
99% electric,
1% Compressed
Natural Gas
(CNG)/
Compressed
Biogas (CBG)
Net Zero Scenario assumes
large-scale adoption of
e-tractors and clean fuel
tech. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 27
Methodology
3
RESULTS Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 28
Results
As discussed in the Background, this section presents mitigation co-benefits and energy
demand for the agriculture sector against the policy pathways. The chapter is organised into
two sections: (i) non-energy emissions pathways and (ii) energy transition pathways. The non-
energy emissions pathways cover crop and milk production projections, the resulting emissions
trajectories and mitigation co-benefits. The energy transition pathways present the projected
trends in energy consumption and demand for on-farm operations through 2070 under the
Current Policy Scenarios (CPS) and the Net Zero Scenarios (NZS).
3.1 NON-ENERGY EMISSIONS PATHWAYS IN AGRICULTURE
This section presents long-term emissions trajectories for the agriculture sector, with a particular
focus on emissions from rice cultivation, agricultural soils, and livestock (enteric fermentation
and manure management). As outlined earlier, the analysis adopts a supply-side, production-
linked modelling framework with 2019 as the baseline and assesses mitigation co-benefits under
the Current Policy Scenario (CPS) and the Net Zero Scenario (NZS) for 2047 and 2070.
Accordingly, rice production is expected to increase from about ~121 million tonnes to 184 million
tonnes (52%), while wheat to rise from ~109 million tonnes to ~178 million tonnest (63%). Maize
is expected to record the fastest growth, expanding from ~30 million tonnes to ~106 million
tonnes (~250%).
400
300
200
100
0
Gross cropped area (million hectares)
201020002020 2030 2040 2050 2060 2070
Year
185
198
216
225
233
239 240 240
Gross cropped area (million hectares) (2000 - 2070)
ProjectedHistorical
Figure 3.1: Gross cropped area projection (2000 to 2070)
3 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 29
Results
In this analysis, food production projections do not directly determine land-use outcomes.
Accordingly, Gross Cropped Area (GCA) projections are derived from historical trends (Figure
3.1). These two inputs are combined to derive overall fertiliser demand. Projections for organic
nitrogen inputs similarly follow historical trends, consistent with India’s submissions to the
UNFCCC (MoEFCC, 2022).
Figure 3.2: Production projections of bovine milk (2000-2070)
Figure 3.2 provide projections for milk that are based on trend-based approach, extrapolating
historical trajectories from 2000 to 2070. This excludes goat milk, which accounts for
approximately 4-5% of total milk output. Overall bovine milk is projected to increase from ~201
to ~694 million tonnes. This represents an increase of ~493 million tonnes, equivalent to a ~245%
rise over the period, indicating more than a threefold expansion.
Long-term non-energy emissions pathways
Under the Current Policy Scenario (CPS), agricultural emissions are projected to increase
modestly from ~506 in 2019 to ~531 MtCO₂e by 2070. This aggregate trend masks diverging
sub-sectoral trajectories. In the crop sub-sector, emissions (agricultural soils, rice cultivation,
and residue burning) are expected to decline by ~21% from ~183 to ~145 MtCO₂e (Figure 3.5).
In contrast, livestock sub-sector emissions (enteric fermentation and manure management)
are expected to rise by ~20% from ~322 to ~386 MtCO₂e (Figure 3.4). Consequently, the crop
sector’s share of agricultural emissions falls from ~36% in 2019 to ~27% in 2070, while livestock’s
share increases from ~64% to ~73% by 2070 (Table 3.1).
In contrast to the Current Policy Scenario (CPS), under the Net Zero Scenario (NZS) total
agricultural emissions are expected to decline to ~399 MtCO₂e by 2070. This reduction is driven
by a ~44% decline in crop sub-sector emissions and a modest decline ~8% decline in livestock
sub-sector emissions. Overall, NZS delivers a ~25% mitigation co-benefit relative to CPS by 2070
(Figure 3.3; Table 3.1).
Overall and bovine milk production (million tonnes) (2000-2070)
Production (million tonnes)
Bovine milk (million tonnes) Total milk (million tonnes)
2000 2010 2020 2030205020402060 2070
Year
800
600
400
200
0
NITI Report, 2024ProjectedHistorical
76
81
117
122
201
207
308
408
507
608
708
300
398
495
595
694 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 30
Results
Note: In 2019, agricultural emissions were at 421 MtCO₂e (AR2) which equals to 506 MtCO₂e
(AR5)
16
.
Table 3.1: Agriculture emission trends across crop and livestock sub-sectors (2019 to 2070)
Year Emission in Current Policy Scenario
(MtCO
2
e)
Emission in Net Zero Scenario
(MtCO
2
e)
Crop sub-
sector
Livestock
sub-sector
Total Crop sub-
sector
Livestock
sub-sector
Total
2019183 322 506 183 322 506
2050156 379 535 116 286 402
2070145 386 531 102 297 399
Current Policy Scenario Net Zero ScenarioBaseline
Overall agricultural emissions (non-energy) (MtCO
2
e) (2019-2070)
600
400
200
0
Emissions (in MtCO
2
e)
Year
201920502070
506
535531
402399
~25%
Figure 3.3: Projected agriculture emission under Current Policy Scenario and Net Zero Scenario
(2019-2070)
Current Policy Scenario Net Zero ScenarioBaseline
Overall livestock sub-sector (MtCO
2
e) (2019-2070)
Year
400
300
200
100
0
201920202070
322
379
286
386
297
Emissions (in MtCO
2
e)
Figure 3.4: Overall emissions – Livestock sub-sector (2019-2070)
16 As per authors’ analysis based on MoEFCC, 2021. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 31
Results
Current Policy Scenario Net Zero ScenarioBaseline
Overall emissions from crop sub-sector (MtCO
2
e) (2019-2070)
Year
250
200
150
100
50
0
183
156
145
116
102
201920502070
Emissions (in MtCO
2
e)
Figure 3.5: Overall emissions – Crop sub-sector (2019-2070)
The subsequent sections examine the key drivers of agricultural emission trajectories and their
associated mitigation co-benefits. Understanding these drivers is crucial to identifying pathways
that maximise mitigation co-benefits while delivering adaptation outcomes.
Methane emission from rice cultivation
The geographical concentration of rice mono-cropping in major producing regions such as
Punjab, Haryana, and Western Uttar Pradesh has intensified water stress and degraded soil
health. These regions also witness plateaued yields thereby, limiting farm profitability over the
past two decades (NFSM, 2014). As Section 1.3 highlights, water-management practices have
persisted in recent years. Key interventions to improve of rice cultivation in India include:
1. Crop diversification away from rice toward nutrient-dense, high-value alternatives.
2. Sustainable yield intensification through technological innovations, including high-
yielding varieties.
3. Adoption of sustainable rice cultivation practices such as alternate wetting and drying
(AWD), system of rice intensification (SRI), and direct-seeded rice (DSR).
Considering a coordinated scale-up of the above three interventions, the Net Zero Scenario
(NZS) is projected to deliver ~47% mitigation co-benefits against that of the Current Policy
Scenario (CPS) in 2070. Under the CPS, methane emissions from rice cultivation are projected
to decline by ~30%, from ~98 MtCO₂e in 2019 to ~69 MtCO₂e by 2070. In the NZS, emissions
decrease further to ~37 MtCO₂e, corresponding to a ~62% decline from 2019 (Figure 3.6). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 32
Results
Emissions from rice cultivation MtCO
2
e) (2019-2070)
125
100
75
50
25
0
Emissions (in MtCO
2
e)
201920502070
Year
98
79
50
69
37
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.6: Rice cultivation emission trends in Current Policy Scenario and Net Zero
Scenari (2019-2070)
Under Current Policy Scenario (CPS), rice acreage is expected to decline from ~44 to ~37 million
hectares, by 2070. Almost ~20% area is expected to adopt sustainable rice cultivation (SRC)
practices in the same period (Figure 3.7). Diversifying ~15% of the area and closing ~20% of the
yield gap raises average yields from 2.7 t/ha to 3.8 t/ha, allowing production to increase from
119 million tonnes to ~133 million tonnes (Figure 3.9) despite a ~16% reduction in cultivated area
(Figure 3.9).
Rice area under Current Policy Scenario (2070)
20%
80%
Figure 3.7: Area under rice cultivation in Current Policy Scenario (2019-2070)
Conventional rice cultivation
Sustainable rice cultivation Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 33
Results
Rice area under Net Zero Scenario (2070)
25%
75%
Figure 3.8: Area under rice cultivation in Net Zero Scenario (2019-2070)
Under the Net Zero Scenario (NZS), interventions are more ambitious. Rice acreage is expected
to decline to ~20 million hectares, with sustainable rice cultivation (SRC) practices covering
25% of rice area (Figure 3.8) by 2070. Diversifying ~20% of the area and closing ~70% of the
yield gap
17
, will sustain production at ~126 million tonnes (Figure 3.9). The modest production
increase mirrors India’s population increase and the declining per capita rice consumption,
consistent with broader dietary diversification (FAO, 2024). Together, these measures account
for the significant mitigation co-benefits under both the scenarios without comprising on food
security of India (Figure 3.9).
Production of rice (million tonnes) (2019-2070)
200
150
100
50
0
Production (million tonnes)
201920502070
Year
119
135134
126128
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.9: Rice production from 2019 to 2070 under Current Policy Scenario and Net Zero Scenario
Rice area (2019-2070)
17 Projected yield in 2070 is ~7.6 t/ha.
Conventional rice cultivation
Sustainable rice cultivation Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 34
Results
Nitrous oxide emissions from Agricultural soils
Higher fertiliser application rates increase manufacturing demand, contribute to rising import
dependence, and impose a fiscal burden of subsidies exceeding `2 lakh crore, while also
degrading soil health (Singh, 2023). To address these challenges, India has implemented
interventions to improve fertiliser use efficiency (FUE) through reduced application, soil health
management, promotion of sustainable agricultural practices among others. At the same time,
policies aimed at increasing cropping intensity and enabling additional cropping cycles are
expected to raise aggregate nitrogen fertiliser consumption, partially offsetting the gains.
Under both the Current Policy Scenario and the Net Zero Scenario, these interacting dynamics:
improvements in FUE reflected in lower per-hectare application rates, adoption of sustainable
practices such as natural farming/organic farming (chemical-free farming), and the countervailing
effects of higher cropping intensity, are jointly modelled to assess long-term agricultural soil
emission trajectories.
Emissions from agricultural soils (MtCO
2
e) (2019-2070)
80
60
40
20
0
Emissions (MtCO
2
e)
201920502070
Year
76
68
62
67
60
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.10: Agricultural soil emission trends in Current Policy Scenario and Net Zero Scenario
(2019-2070)
Cropping intensity (GCA/NSA) (2019 - 2070)
2.0
1.5
1.0
0.5
0.0Cropping intensity (GCA/NSA)
201920502070
Year
1.5
1.6
1.71.7
1.8
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.11: Cropping intensity in Current Policy Scenario and Net Zero Scenario (2019-2070) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 35
Results
Nitrogen fertiliser consumption (kg/ha) (2019-2070)
100
75
50
25
0
Fertiliser consumption (kg/ha)
201920502070
Year
90
83
72
80
66
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.12: Nitrogen fertiliser consumption per ha in Current Policy Scenario and Net Zero Scenario
(2019-2070)
Under the Current Policy Scenario (CPS), these measures are projected to deliver ~11% mitigation
co-benefits, reducing emissions from ~76 MtCO₂e in 2019 to ~67 MtCO₂e by 2070 (Figure 3.10).
This outcome reflects improvements in fertiliser use efficiency, which lower nitrogen application
rates from 90 kg/ha in 2019 to 80 kg/ha by 2070 (Figure 3.12). At the same time, the expansion
of natural and chemical-free farming is projected to increase to 28 million hectares (20% of
NSA) (Figure 3.13). This reduces total nitrogen fertiliser demand in India from 19 million tonnes
in 2019 to 15 million tonnes in 2070, even as cropping intensity increases (Figure 3.11).
Similarly, under the Net Zero Scenario, emissions from fertiliser use are expected to decline
further to 60 MtCO₂e by 2070 (~20% reduction), providing an additional 10% of mitigation co-
benefit relative to Current Policy Scenario (Figure 3.10). This is achieved through wider adoption
of natural and chemical-free farming practices upto 25% of Net Sown Area (Figure 3.13), lowering
nitrogen application rates due to improved fertiliser use efficiency (~50% by 2070).
40
30
20
10
0
Area (million hectares)
20502070
Year
22
2928
35
Area under Chemical-free farming (million hectares) (2019 - 2070)
Current Policy Scenario Net Zero Scenario
Figure 3.13: Area under Natural and Chemical-free farming Current Policy Scenario and Net Zero
Scenario
Note: Agricultural soil emissions are also sensitive to crop diversification, particularly shifts from rice to high-input
crops like horticulture. Currently, nitrogen use per hectare is estimated at the aggregate level, but integrating crop-wise
fertiliser data from the All-India Input Survey 2016–17 could improve future sensitivity analyses. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 36
Results
Realising the Net Zero Scenario (NZS) requires careful, calibrated scaling of key interventions.
Integrated Nutrient Management (INM) under the National Mission for Sustainable Agriculture
(NMSA) and digital Soil Health Cards optimize nutrient application and maintain soil health.
Mandatory consumption of 100% neem-coated urea reduces nitrogen volatilisation losses.
Scaling chemical-free farming under National Mission on Natural Farming (NMNF) and Pradhan
Mantri Krishi Vikas Yojna (PMKVY) must be implemented strategically to protect food security
and farmer incomes, while transitioning millions of hectares to low-input, sustainable cultivation.
Livestock emissions
India is the world’s largest producer of milk and contributes to ~25% of global milk output (PIB
2024). Milk production is projected to grow to ~467 million tonnes in 2050 and ~693 million
tonnes in 2070, cumulatively rising by ~245% since 2020.
Emissions from livestock sub-sector (MtCO
2
e) (2019-2070)
400
300
200
100
0
Emissions (in MtCO
2
e)
201920502070
Year
322
379
286
386
297
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.14: Emissions from livestock sector in Current Policy Scenario and Net Zero Scenario
(2019-2070)
Under the Current Policy Scenario (CPS), livestock emissions are projected to rise from ~322
MtCO₂e in 2019 to ~386 MtCO₂e by 2070 (~20% increase) (Figure 3.14), with average in-milk
productivity expected to reach 12 kg/day per animal (Figure 3.15). In contrast, the Net Zero
Scenario (NZS) reduces emissions to ~297 MtCO₂e by 2070 (~8% below 2019 levels) (Figure
3.14), while boosting productivity to 15 kg/day per animal (Figure 3.15). Within the herd, the
proportion of in-milk animals rises from 35% in 2019 to 50% in 2070, supporting higher milk
yields (Figure 3.16).
The Net Zero Scenario achieves ~23% mitigation co-benefits in the livestock sector through
technological and management interventions. Yield improvements are driven by breed and
genetic enhancements via programs like the Nationwide Artificial Insemination Programme
(NAIP), alongside advanced breeding technologies, including in-vitro fertilisation (IVF).
Additionally better nutrition through the Ration Balancing Programme (RBP), and year-round
availability of green fodder using silage and roughage technologies further help to enhance
productivity. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 37
Results
Productivity of in-milk bovines (kg/day/head) (2019-2070)
201920502070
Year
20
15
10
5
0
Productivity (kg/day/head)
Current Policy Scenario Net Zero ScenarioBaseline
5
9
13
12
15
Figure 3.15: Milk yield trends in Current Policy Scenario and Net Zero Scenario (2019-2070)
Current Policy Scenario Net zero ScenarioBaseline
In-milk bovine population (million) (2019-2070)
200
150
100
50
0
In-milk bovine population (in million)201920502070
Year
100
154
108
157
127
Figure 3.16: Share of in-milk bovine population in the total bovine population (2019-2070)
3.2 ENERGY EMISSIONS PATHWAYS IN AGRICULTURE
In 2020 India’s agriculture consumed ~23 Mtoe of direct energy, 21 Mtoe for pumping (mostly
electricity and diesel) and 2.1 Mtoe for land preparation (primarily diesel for tractors and
tillers) (CEA, 2022). Under Current Policy Scenario (CPS), the total energy consumption in
agriculture is expected to increase to 42 Mtoe by 2050 and 54 Mtoe by 2070. Under the Net
Zero Scenario (NZS) also, the total energy use increases to 35 Mtoe by 2050 and 39 Mtoe
by 2070. However, the total energy use in NZS is lower than the corresponding numbers for
CPS. During the corresponding period, the agricultural output has nearly doubled. This shows
that efficiency gains and technology shifts can decouple energy demand from agricultural
output (Figure 3.17). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 38
Results
Land Preparation Pumping
60
50
40
30
20
10
0
Mtoe
2020202520502070
Current Policy
Scenario
Current Policy
Scenario
Net Zero
Scenario
Net Zero
Scenario
Energy Consumption in the Agriculture Sector (Mtoe) (2020-2070)
23
4
3
2124
38
31
51
36
33
Figure 3.17: Overall energy consumption in Agriculture Sector (2020-2070)
Energy consumption in irrigation
Under Current Policy Scenario, energy demand rises from 21 Mtoe in 2020 to 38 Mtoe in 2050
and 51 Mtoe by 2070, driven by expanding irrigation (from 53% to 65% of GCA) and higher
groundwater reliance (Figure 3.18a). Diesel pumps decline slowly, while grid electricity remains
primary, complemented by solar pumps (40% of energy by 2070). Modest efficiency gains
(40%) and deeper pumping heads (50 m) sustain high energy demand.
In Net Zero Scenario, pumping rises more moderately from 21 to 32 Mtoe by 2050, plateauing
at 36 Mtoe in 2070 (Figure 3.18a). Efficiency improvements, adoption of drip/sprinkler irrigation,
aquifer recharge, and better management limit energy growth. Diesel pumps are phased out by
2035, with 40% grid electricity and 60% solar supplying pumping energy by 2070 (22 Mtoe).
Energy Consumption in Pumping (Mtoe) (2020-2070)
60
50
40
30
20
10
0
Mtoe
2020
1.9 1.3
18.9 21.2
28.6
20
14.2
30.3
0.2
21
23.5
37.9
31
50.6
35.5
0.9
9.2
11
21.3
20.2
202520502070
Current Policy
Scenario
Current Policy
Scenario
Net Zero
Scenario
Net Zero
Scenario
Diesel Electricity Solar
Figure 3.18a: Energy demand and fuel mix in agricultural pumping under Current Policy Scenario
(CPS) and Net Zero Scenario (NZS) by 2050 and 2070
23
27
42
34
54
39 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 39
Results
Diesel CNG/CBG Electricity
Energy Consumption in Land Preparation (Mtoe) (2020-2070)
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Mtoe
2020 202520502070
Current Policy
Scenario
Current Policy
Scenario
Net Zero
Scenario
Net Zero
Scenario
2
2.5
1.7
1.0
0.3
2.5
0.2
0.3
2.7
1.9
0.3
1.7
Figure 3.18b: Energy demand and fuel mix in land preparation under Current Policy Scenario
(CPS) and Net Zero Scenario (NZS) by 2050 and 2070
Energy consumption in land preparation
Under the Current Policy Scenario (CPS), energy demand rises from 2.1 Mtoe in 2020 to 3.8
Mtoe in 2050 and 3.3 Mtoe by 2070, with 9% comming from diesel and 8% from CNG by
2070 (Figure 3.18b). Efficiency gains and precision agriculture reduce per-hectare fuel use, but
expanding mechanisation drives overall demand.
Under Net Zero Scenario, total energy stabilises at ~2.5 Mtoe by 2070 despite full mechanisation
(Figure 3.18b). Diesel is fully phased out by 2070, replaced by electric tractors and tillers (~2.5
Mtoe) with just 1% Compressed Biogas (CBG), sourced from crop residues and animal waste, acts
as a transitional fuel in the 2040s, supporting India’s Sustainable Alternative Towards Affordable
Transportation (SATAT) initiative, reducing residue burning, and generating rural income. In the
later decades, electric tractors dominate, offering ~30% higher efficiency and integration with
a decarbonised grid and solar charging.
2
2.5
3.8
3.2
3.3
2.5 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 40
Results
Box 3: State-Level Transitions in Practice
Gujarat – The Suryashakti Kisan Yojana (SKY) has shown how decentralized solar pumps
connected to the grid can displace diesel, reduce subsidy costs, and even create new
income streams as farmers sell surplus electricity. Farmers in Dhundi village, for example,
have eliminated dozens of diesel pumps and now treat solar power as a secondary crop.
Rajasthan – In Rajasthan, drip irrigation coupled with solar pumps has enabled farmers
to sustain yields while cutting water and energy use by 30–50%. This exemplifies the
water–energy efficiency nexus modeled in the Net Zero Scenario.
Maharashtra – Maharashtra’s feeder solarization programme demonstrates how
centralized solar generation can deliver daytime electricity to thousands of pumps
simultaneously. By 2025, the state targets 30% solarized feeders, reducing dependence
on coal-based power. Taken together, these cases illustrate that the modeled Net Zero
Scenario is not abstract.
The combination of efficiency (Rajasthan), decentralized solar (Gujarat), and feeder-
level solarization (Maharashtra) shows how India can achieve plateauing energy demand
despite rising output, while lowering fiscal and environmental costs. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 41
Results
4
KEY CHALLENGES AND
SUGGESTIONS Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 42
4
Key Challenges and
Suggestions
4.1 KEY CHALLENGES
The transition of India’s agriculture and allied sectors from the Current Policy Scenario (CPS) to
ambitious Net Zero Scenario (NZS) faces complex, interconnected structural challenges, despite
the NZS offering a ~25% mitigation co-benefit by 2070 compared to the CPS trajectory. As a
result, achieving the mitigation co-benefits in NZS require addressing many issues:
1. Effectively managing trade-offs while harnessing synergies across livelihoods,
resilience, and food security is critical to implementing Net Zero Scenario pathways:
For instance, adopting chemical-free practices, such as Natural Farming, can increase
the availability of diverse and nutrient-rich foods, improving both public health and
environmental quality by reducing agrochemical runoff and soil degradation. On the
other hand, it may lower yields in the green revolution regions in the short term while
possibly increasing them in the rainfed regions. The scaling up thus needs to be well
planned to keep the food grain supply stable for India’s food security. Balancing these
competing and complementary objectives is critical. Hence, developing evidence-
backed long-term strategic roadmaps is critical for a risk-calibrated approach to
implementing the Net Zero Scenario (NZS) pathways.
Driving the intervention identified under the Net Zero and Current Policy Scenarios
feasibly needs comprehensive, long-term scaling strategies that are context-specific,
targeted, and phased to capture synergies and balance trade-offs. For instance, as
exemplified in Annexure VI (Part-1), scaling crop diversification requires a phased
approach that targets states based on yields, biophysical suitability, and the capacity
of public procurement channels, while safeguarding national food and nutrition
security. Scaling animal health and nutrition interventions to boost milk productivity
must account for contextual realities, such as state-specific breed composition, feed
consumption patterns among various breeds, socioeconomic drivers of bovine rearing,
and climate resilience of the whole bovine economy.
2. Inherent affordability and access barriers for scaling adoption: Agri-food systems
face constrained adoption of technologies, mechanisation, particularly among small
and marginal producers who struggle with affordability and last-mile access. These
constraints are compounded by under capacitated support services, across extension,
credit, insurance, market linkages, and post-harvest systems, that fail to enable a
smooth transition to resilient and diversified practices. Further, significant gaps in
timely, reliable, and localised data limit evidence-based decision-making for producers,
value-chain actors, and policymakers alike. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 43
Key Challenges and Suggestions
Addressing these barriers requires a systemic overhaul of the enabling ecosystem
that connects farmers and consumers. This includes stronger investments in research
and development, deeper technology penetration, and the creation of targeted,
responsive, and dynamic Krishi Decision Support Systems such as being done through
the Agri-Stack. Improved market intelligence and transparent, well-designed incentive
disbursement mechanisms will be essential to drive widespread adoption of sustainable
agri-food practices.
This exercise of supply-side modelling that has generated pathways, is a critical first step
towards informing long-term planning for the agriculture sector. However, translating
the emission pathways into policy and planning frameworks requires feasible and
targeted roadmaps. An agri-food systems approach delivers this required integrated
perspective, which is essential for maximising agriculture’s contribution to long-term
livelihoods development, nutrition and health enhancement, resilience-building, as well
as climate mitigation co-benefits.
3. Managing trade-offs and leveraging land–energy–water synergies: The Net Zero
Scenario implementation must balance food security, water sustainability, clean energy
deployment, and fiscal outcomes. Mechanisation and electrification without subsidy and
groundwater reforms risk increasing power demand and utility stress, while large-scale
solar raises land-use competition. Integrated approaches, combining solar irrigation,
micro-irrigation, electric machinery, and agrivoltaics offer strong synergies but require
coordinated, cross-sectoral planning. Institutional silos and fragmented governance
must be resolved.
4. Rising energy demand from irrigation pumping and groundwater dependence:
Irrigation energy demand continues to grow due to increasing cropping intensity,
deeper groundwater tables, and climate-induced variability in rainfall. Even with
solarisation, pumping loads may rise if water use remains unmanaged, limiting net
energy savings. Weak regulation of groundwater extraction and limited adoption of
efficient irrigation technologies compound this challenge. Managing pumping demand
is therefore central to achieving durable mitigation outcomes.
5. Energy-intensive land preparation and slow transition from diesel equipment: Land
preparation remains heavily reliant on diesel-powered tractors and tillage equipment,
contributing significantly to on-farm energy use and emissions. While electric and
Compressed Biogas (CBG)-based alternatives are emerging, adoption is constrained by
high costs, limited charging or fuel infrastructure, and concerns over reliability during
peak seasons. Without targeted support and shared-access models, diesel lock-in in
land preparation risks persisting well into the transition period.
6. Behavioural Inertia Across Producers and Consumers: Deep-rooted production and
consumption habits limit shifts toward diversified, nutritious, and sustainable food
systems. Producers remain anchored to familiar cropping patterns due to risk aversion
and market uncertainties, while consumers continue to prefer staple-heavy diets despite
the availability of healthier alternatives. This is exacerbated by the absence of strong,
integrated demand–production signals. Currently, fragmented many incentives work at
cross-purposes. This reinforces existing production patterns and slows the transition
to diversified, sustainable production systems. Addressing demand-side drivers and Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 44
Key Challenges and Suggestions
barriers is far more critical: fostering dietary diversification (demand) enables shifts in
cropping patterns (supply) and unlocks greater mitigation potential than pure supply-
side measures (Jha et al., 2023; Patange et al., 2024).
For instance, mainstreaming millet consumption through public procurement channels
(e.g., the Public Distribution System) and high-visibility initiatives like the International
Year of Millets and India’s Millet Mission can stimulate consumer demand, incentivising
farmers to shift cultivation away from emission-intensive crops like rice. In addition,
unlocking market potential, both domestic and global, is crucial to sustaining the
production trajectory. For instance, milk exports have expanded notably over the past
decade, yet boosting global competitiveness remains a challenge, constrained by
quality standards, trade barriers, and logistical inefficiencies.
4.2 SUGGESTIONS FOR SUSTAINABLE LONG-TERM PATHWAYS FOR
AGRICULTURE AND ALLIED SECTORS
This analysis demonstrates that the proposed Net Zero Scenario yields a ~25% mitigation co-
benefit against the Current Policy Scenario. The finding is based on nine key interventions
developed under multi-benefit centered, policy-driven assumptions. Interventions refined
through rigorous, multi-stakeholder consultations highlight that there is both the need and
feasibility of a systemic transformation within the sector that also comes with significant
mitigation co-benefits. As a result, the following framework is proposed to accelerate an agri-
food systems transformation for resilience, farmers’ incomes and food security that deliver
mitigation co-benefits:
1. Develop long-term and short-term strategies to scale multi-benefit interventions:
Realising mitigation co-benefits requires ambitious yet feasible, risk-calibrated scaling
of multiple interventions. This calls for a careful assessment of opportunities, trade-offs,
social acceptance, and financial viability to avoid negative spillovers while safeguarding
food security and livelihoods. This report therefore suggest intervention-specific
roadmaps to maximise co-benefits and minimise trade-offs, as outlined in the following
section:
a) Crop diversification: India’s crop diversification programme under Rashtriya Krishi
Vikas Yojna (RKVY) has promoted shifts from water-intensive rice cultivation in
Green Revolution states since 2015. Yet these regions still dominate national rice
production. Achieving a 20% reduction in rice cultivation area by 2070 demands
pragmatic interventions (technological, economic, and institutional) supported
by geographically sensitive and temporally phased roadmaps that strategically
enable:
i. Supply-side diversification: Promote diversification through crop alternatives,
such as pulses, millets, oilseeds, and horticultural crops, leveraging the
Government of India’s flagship missions.
ii. Demand-side linkages and diet diversification: Ensure production shifts are
complemented by strong demand signals. This includes integrating pulses Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 45
Key Challenges and Suggestions
and millets into the Public Distribution System (PDS), to create assured
market linkages that drive consumption shifts. These efforts, as they enable
integrated production- consumption shifts, must be guided by socio-economic
assessments that align geographical diversification priorities with household-
level nutrition and affordability considerations.
As outlined in Annexure VI (Part-1), strategically bundling and sequencing
the above supply and demand side interventions will be critical to realising
crop diversification, without undermining the food system security or farmer
livelihoods.
b) Natural and Chemical-free farming: India has initiated several efforts to promote
natural and chemical-free farming, including the National Mission on Natural
Farming (NMNF), Paramparagat Krishi Vikas Yojana (PKVY), and Bharatiya Prakritik
Krishi Paddhati (BPKP). These programs have laid a foundational framework for
agroecological transitions by focusing on policy support, certification mechanisms,
and capacity-building initiatives. The pace of adoption needs to be accelerated.
Achieving the target of bringing 25% of agricultural land under natural and
chemical-free farming by 2070 will therefore require a combination of technological
and institutional interventions, supported by implementation strategies tailored to
agro-climatic suitability and local farming systems.
As explained in Annexure VI (Part-2), targeting should integrate agronomic
(productivity, fertiliser use), biophysical (soil, rainfall, elevation), and socio-
economic (community institutions like SHGs) parameters to secure long-term
nutrition and environmental sustainability. Natural Farming can be applied both
to rainfed areas (boosting yields, profitability, and nutrition) and Green Revolution
hotspots addressing water stress and soil degradation.
c) Enhancement of aggregate livestock productivity: Requires converging
production and demand-side strategies across milk, feed, and fodder value chains,
to ensure food security, climate resilience, and reduced emissions intensity. State-
wise bovine breed analysis, feed needs, and fodder shortage mapping will help to
boost output while optimising land use. To balance the trade-off, there is a need
for:
i. Breed improvement: Breed improvements may be facilitated through
technological interventions, such as artificial insemination and in-vitro
fertilisation, guided by agro-climatic and socio-economic suitability of the
breeds.
ii. Improve animal nutrition and health: Breed improvements impact feed and
fodder demand that could constrain fodder availability in India. As a result,
it is imperative to assess the future feed requirements of different breeds.
Developing institutional mechanisms for channeling fodder from surplus
to deficit states can address spatial imbalances. To overcome temporal
shortages, particularly in green fodder, practices such as silage-making should
be promoted in fodder-surplus regions. The improvement in animal nutrition
would potentially also improve animal health and productivity. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 46
Key Challenges and Suggestions
iii. Feed efficiency: Improve overall feed quality with high-protein options to
boost livestock productivity, thereby reducing land pressure as enhanced
efficiency lowers total fodder demand.
The increase in livestock productivity would require a dedicated focus on animal
nutrition and adequate availability of fodder, increasing the pressure on land. This will
potentially necessitate an increase in India’s cropping intensity even more.
2. Adopt an integrated “agri-food” systems approach: India’s agricultural transition
requires coordinated policy action across land, energy, and water systems; isolated
interventions, such as solar irrigation without groundwater governance, electrification
without subsidy reform, or renewable deployment without land-use planning, risk
inefficiencies, fiscal stress, and competition with food production. Our analysis indicates
that no single intervention can independently deliver meaningful mitigation or energy-
efficiency co-benefits by 2070; whether focused on crop diversification, natural and
chemical-free farming, or yield intensification, interventions scaled in isolation risk
unintended trade-offs, as illustrated by the Green Revolution, which addressed food
security but undermined long-term soil health and ecosystem resilience (John and Babu,
2021). Achieving durable outcomes, therefore, requires an agri-food systems approach
that aligns production systems, dietary patterns, value chains, and environmental
objectives across land, energy, food, health, biodiversity, and water systems (FAO,
2024). Initiatives such as the Pradhan Mantri Dhan-Dhaanya Krishi Yojana (PMDDKY)
demonstrate the potential of such integration by converging crop diversification,
rural livelihoods, and access to credit across 100 low-productivity districts. Scaling
similar efforts through a whole-of-government approach-ensuring alignment across
the Ministries of Agriculture, Energy, Water, and Health-can embed clean energy,
micro-irrigation, electric farm machinery, healthy diets, and dual-use solutions such as
agrivoltaics (Gómez-Casanovas et al., 2023) directly within agricultural development
strategies.
3. Conduct integrated assessment of the agri-food system for long-term planning
and ambition setting: Conduct integrated assessment of the agri-food system for
long-term planning and ambition setting: To scale integrated interventions effectively,
ambition setting must be future-sensitive, underpinned by robust scenario analyses
and periodic reviews for adaptive governance, while accounting for socio-economic
and climatic uncertainties. Maximising mitigation co-benefits from the agriculture
sector by 2070 while balancing economic development requires a fundamental shift
away from siloed, short-term planning approaches. Integrated Assessment Modelling
(IAM) is essential for generating data-driven insights that support decision-making and
navigate the complex interdependencies of climate, agriculture, and socio-economic
systems (IPCC, 2014). For example, Jha et al. (2022) highlight that dietary shifts
towards healthy diets could reduce India’s emissions by ~60 % compare to baseline.
Similarly, a robust IAM assessment, calibrated to India’s national context, can integrate
supply-side interventions with demand-side dynamics (e.g., rising incomes, urban
dietary shifts), while quantifying trade-offs such as land-use competition between
food security, afforestation goals and goals of other land requiring economic sectors. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 47
Key Challenges and Suggestions
Critically, it can assess how macroeconomic levers impact farm profitability and rural
livelihoods, ensuring no population is marginalised in the transition. By embedding
climate projections (e.g., monsoon variability, heat stress). This could be vital to align
India’s dual goals of becoming a Viksit Bharat by 2047 and a net-zero economy by
2070, while ensuring food systems transformation strengthens, rather than strains, the
livelihoods of those who feed the nation.
4. Implement an “Efficiency-first + clean energy solutions” strategy to achieve maximum
efficiency within the sector: The agricultural energy transition, driven primarily by
irrigation demand, must follow an adaptation-first, agriculture-led sequencing to avoid
energy-intensive lock-ins. Energy demand projections (Figure 3.17) indicate that simply
substituting diesel and grid-connected pumps with solar pumps lowers emissions but
does not curb total energy demand, as irrigation volumes and groundwater dependence
continue to rise. An efficiency-first strategy is therefore essential, prioritising resource-
efficient practices such as micro-irrigation, precision and daytime irrigation scheduling,
sustainable practices, and rationalised input usage to reduce both water and energy
intensity while strengthening climate resilience. Evidence from Box 3, demonstrates
that solarisation, when explicitly linked to efficient water use, can induce behavioural
change and deliver up to 30% reductions in water and energy consumption.
Building on these efficiency and adaptation gains, clean energy interventions, including
renewable adoption, electrification of farm operations, and the use of clean fuels such
as Compressed Biogas (CBG), can then be scaled to decouple productivity growth
from energy use. Mechanisation, which is inevitable by mid-century, need not lock in
emissions if the transition is directed towards electric and clean-fuel-based machinery,
as reflected in the net-zero pathway. Custom Hiring Centres (CHCs) will be central to
this transition, lowering upfront costs, improving the utilisation of clean machinery, and
extending access to smallholders who cultivate farms averaging less than 1.1 hectares,
thereby ensuring that mechanisation delivers productivity, energy-efficiency, and
mitigation co-benefits in a resource- and fiscally sustainable manner. ANNEXURES Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 50
Annexure I:
Country-Specific Emission
Factors for the Study
Table Annex. I.1: Country-specific emission factors for Rice cultivation
Region/EcosystemWater Regime Emission Factor (kg CH
4
/ha)
Irrigated
Continuously Flooded159.74
Single Aeration66.2
Multiple Aeration19.3
RainfedDrought Prone68.84
Flood Prone189
Deep WaterDeep Water190
Source: MoEFCC, 2018 (BUR 4 emission factors are unavailable)
Table Annex. I.2: Agriculture soil emissions: Emission factors
ParameterCountry-specific emission coefficients/
factors (% of N converted to N2O)
EF1 (N
2
O emission from applied fertiliser)0.55
EF4 (N
2
O emission from volatilized N from fertiliser
and manure)
0.50
EF5 (N
2
O emission from leached and run-off N from
fertiliser and manure)
0.50
FracGASF (Gas loss through volatilisation from
inorganic fertiliser)
20
FracGASF-AM (Gas loss through volatilisation from
manure)
20
Fracleach (Leaching loss of N from applied fertiliser
and manure)
10
Source: MoEFCC, 2023
Table Annex. I.3: AWB: Emission factors (CH
4
and N
2
O)
GHG Gas typeEmission Factor (kg GHG/kg biomass burnt)
CH
4
0.0027
N
2
O0.00007
Source: BUR 2, 2019 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 51
Annexure I: Country-Specific Emission Factors for the Study
Table Annex. I.4: Livestock: Emission factors (CH
4
and N
2
O)
Category Sub-Category Age Group Methane Emission Factor Nitrous Oxide
Enteric
Fermentation
(kg CH
4
/
head/ year)
Manure
Management
(kg CH
4
/
head/ year)
Manure
Management
(kg N
2
O/head/
year)
Indigenous
Cattle
Dairy Cattle Indigenous 283.5 0.0006
Non-Dairy Cattle
(indigenous)
0–1 year 91.2 0.0004
1–3 years 232.8 0.0004
Adult 322.9 0.0004
Crossbred
Cattle
Dairy Cattle Cross-bred 433.8 0.0006
Non-Dairy Cattle
(cross-bred)
0–1 year 111.1 0.0004
1–3 years 262.3 0.0004
Adult 332.5 0.0004
Buffalo Dairy Buffalo504.4 0.0006
Non-Dairy
Buffalo
0–1 year 81.8 0.0004
1–3 years 223.4 0.0004
Adult 444 0.0004
Source: MoEFCC, 2004 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 52
Annexure II:
Policy Typologies
Table Annex. II.1: Policy mapping and assumptions behind scenarios
ScenariosAssumptions
Cropping intensity Pradhan Mantri Krishi Sinchayee Yojana–Micro Irrigation (PMKSY-MI) and
the Accelerated Irrigation Benefits Programme (AIBP) are expected to
enhance cropping intensity, though overall increase may be limited by
small landholdings and gradual labour shift away from agriculture.
Crop diversification Policies like the Crop Diversification Programme (CDP) and Mera
Paani Meri Virasat (MPMV) aim to reduce reliance on rice, wheat, and
sugarcane. Coupled with rising income and demand for pulses, millets,
and horticulture, these shifts are likely to make alternative crops more
profitable and widely adopted.
Yield intensification Schemes like Sub-Mission on Agricultural Mechanisation (SMAM) and
Custom Hiring Centres (CHCs) aim to improve access to farm machinery
and enhance cultivation efficiency. Further, Soil Health Card (SHC) and
Integrated Nutrient Management (INM) initiatives aim to improve soil
fertility and support sustainable yield growth.
Natural and Chemical-
free farming
Schemes like National Mission on Natural Farming, Paramparagat Krishi
Vikas Yojana (PKVY), and Bharatiya Prakritik Krishi Paddhati (BPKP) aim
to promote natural and organic farming through targeted support and
awareness. Further Participatory Guarantee Scheme (PGS) and National
Programme on Organic Production (NPOP) certifications encourage
adoption by offering credible certification systems for organic produce.
Fertiliser uptake
efficiency
Fertiliser uptake is expected to improve through interventions like
neem-coated urea, fertigation, micro irrigation, and Integrated Nutrient
Management (INM).
Support measures such as gypsum distribution under the National Mission
for Sustainable Agriculture and upcoming technologies like AI-driven
precision agriculture further enhance nutrient efficiency and application.
Conventional rice
cultivation practices
Policies like the National Food Security Mission (NFSM) and Bringing
Green Revolution to Eastern India (BGREI) promote practices such as
System of Rice Intensification (SRI) and Direct Seeded Rice (DSR), which
help reduce methane emissions from rice cultivation.
Crop residue burning Government initiatives such as crop residue management schemes and the
promotion of equipment like Happy Seeders aim to reduce Agricultural
Waste Burning (AWB).
Bovine productivity An overall increase in livestock productivity is assumed, driven by
government initiatives focused on animal health and nutrition. Programs
such as the National Dairy Plan (NDP), which promotes ration balancing,
and state-wise fodder development efforts led by institutions like Indian
Grassland and Fodder Research Institute (IGFRI), are expected to enhance
per-animal yield (kg/day). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 53
Annexure II: Policy Typologies
Development of Current Policy Scenario and Net Zero Scenario
Long-term strategic pathways were developed through iterative, multi- stakeholder consultations
(with 30+ experts). The process evaluated adoption trajectories of different interventions, and
impact potential is quantified across temporal horizons (2020–2070). The four-phased pathways
development process comprised:
1. Policy identification: Mapping government policies shaping agricultural production systems.
2. Policy typology development: Classification of policies into typologies based on their
primary outcome (productivity enhancement, sustainable agriculture practices, agricultural
intensification, etc.) with their corresponding mitigation co-benefits.
3. Scenario definition: Identifying key variables against the policy typologies.
4. Scenario Building: Consultations for consensus building with stakeholders, experts and
Working Group members to align on differentiated assumptions for scenarios across near-
term (2030), mid-century (2047), and long-term (2070) horizons.
The last step is followed for the development of two pathways: Current Policy Scenario (CPS)
and Net Zero Scenario (NZS). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 54
Annexure III:
Emissions in Sustainable
Rice Systems
Table Annex. III.1: Alternative Rice cultivation strategies and their emission reduction
potentials
StateAlternative
Cultivation Strategy
Emission Reduction
Potential from
Literature (%)
References
AssamSemi-Dry Cultivation 29.0(Gorh and Baruah 2019)
(Gogoi, Baruah, and Gupta
2008)
Andhra Pradesh
(excluded)
SRI + AWD26.8 (Duvvuru and Motkuri 2013)
Bihar
DSR +AWD89.7 (Pathak and Aggarwal 2012)
SRI +AWD71.5
AWD29.5
DI100
Haryana
DSR + AWD89.5 (Pathak and Aggarwal 2012)
SRI +AWD64.0
AWD29.1
DI100
OdishaAWD75.0(Mohanty et al. 2017)
Punjab
DSR +AWD89.5 (Pathak and Aggarwal 2012)
DSR82.0
SRI + AWD64.0
DI100
Tamil Nadu
AWD52.8 (Thanakkan and Selvaraj 2020)
DSR + AWD16.6 (Thanakkan and Selvaraj 2020)
SRI + AWD26.8 (Thanakkan and Selvaraj 2020)
DI68.0 (Thanakkan and Selvaraj 2020)
(Parthasarathi et al. 2019)
TelanganaSRI + AWD23.4(Nirmala et al. 2021) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 55
Annexure III: Emissions in Sustainable Rice Systems
StateAlternative
Cultivation Strategy
Emission Reduction
Potential from
Literature (%)
References
Uttar Pradesh DSR + AWD89.5 (Pathak and Aggarwal 2012)
SRI + AWD64.0
AWD29.1
DI100
West Bengal DSR + AWD89.7 (Pathak and Aggarwal 2012)
SRI + AWD71.5
AWD29.5
DI100
Note: DSR - Direct Seeded Rice
SRI - System of Rice Intensification;
AWD - Alternate Wetting and Drying;
DI: Drip Irrigation Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 56
Annexure IV:
Energy Demand Projections
of Irrigation Pumping
Steps in Figure 2.1 are explained below:
1. Crop demand projections: Demand projections for this study are drawn from NITI Aayog’s
Working Group Report on Crop Husbandry, Agricultural Inputs, and Demand–Supply, which
provides estimates up to 2047. These projections were subsequently extended to 2070 in
collaboration with the scientists and experts from Indian Council of Agricultural Research
(ICAR) The crops considered are rice, wheat, maize, pulses, oilseeds, sugarcane, and cotton.
Together, these account for the majority of India’s irrigated land and water consumption.
2. Water demand estimation: The water demand for pumping is estimated from crop
production requirements. Crop production (in million tonnes) is translated into crop area
using projected yields, with a distinction drawn between rainfed and irrigated shares using
crop specific irrigation intensities. The table below (Table Annex. IV.1) presents the share
of each major crop’s area that was irrigated in 2020.
Table Annex. IV.1: Crop-wise share of irrigation as in 2020- Baseline
CropIrrigated Share (2020)
Rice60.9%
Wheat94.6%
Maize36.7%
Arhar (pigeonpea)4.2%
Gram (chickpea)42.8%
Groundnut29.1%
Rapeseed & Mustard79.9%
Sugarcane96.0%
Cotton35.7%
Multiplying each crop’s irrigated share by its water productivity coefficient (kg crop per m
3
)
yields the total volume of irrigation water demand (Sharma et al, 2018).
Not all irrigation water is lifted by pumps – a portion is supplied by gravity flow in canal
command areas and by tank irrigation. A pumping share factor is applied to reflect the fraction
of irrigation water that requires energy for pumping. Currently, about 60–70% of India’s irrigated Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 57
Annexure IV: Energy Demand Projections of Irrigation Pumping
area is served by groundwater (wells and tube wells) or other lift systems, which implies that
roughly two-thirds of irrigation water is pumped (The remainder from canals may involve minor
lifting at field level, but is largely gravity-fed). A baseline value of 75% is used as the share of
irrigation water that is pumped (MoAFW, 2022). For future scenarios, this factor can change
based on investments in canal infrastructure or micro-irrigation (for instance, expanded surface
irrigation could reduce reliance on pumps, whereas deeper groundwater use could increase
energy needed per unit water).
Energy demand estimations: Energy demand for irrigation is calculated by converting pump-
dependent water requirement into useful energy and then into final energy, accounting for
operating conditions and technology parameters.
1. Pump discharge and utilisation: Based on the 5th Minor Irrigation Census (MIC)
in 2017 (MoJS, 2024) and supporting field studies, an average irrigation pump is
considered to be rated as 5–6 Horsepower (HP), with a discharge rate of 20 m³/h
under a nominal head of 25 metres. Utilisation differs sharply by technology: electric
and solar pumps operate for 750 hours annually, while diesel pumps operate for
250 hours due to higher fuel costs. Using these assumptions, the model reproduces
a base-year pump stock of 20 million electric and 10 million diesel units, consistent
with estimates in MIC 2017.
2. Dynamic head: The average pumping head in 2019 was 28 m, and is a representative
value across shallow and deep groundwater systems reported in MIC 2017 (MoJS,
2024). This is projected to rise to 50 m by 2070 as groundwater tables decline.
3. Pump efficiency: Overall pump–motor efficiency is assumed to be 30% for diesel
and 36% for electric pumps in 2020, improving gradually to 45–55% by 2070 with
technology advances and better maintenance (EMC, 2018). Solar pumps use high-
efficiency electric motors and are assumed to perform comparably to grid-electric
pumps.
4. Energy calculation: Useful energy required for pumping is estimated as:
Useful Energy Demand = E
u
=N
p
× H
p
× A
h
Where,
Ground Water Demand
N
p
= Number of active pumps =
_____________________________________________
Average Discharge Rate
*
Functioning Hours per Year
H
p
= Horsepower of lifting device, assumed to be 5 based on MIC 2017.
A
h
= Annual Hours Usage, assumption based on MIC, IWMI, and consultations.
EU
Final Energy Demand E
f
=
___________, where η is overall efficiency of the pump
n
Modelled outputs are validated against observed consumption: 207 TWh of electricity in
agriculture in 2019-20 (CEA 2024) and about 6-8 MMT of diesel annually (Petroleum Planning
and Analysis Cell (PPAC)). The base-year estimates are within a narrow margin of these reported
values, confirming the robustness of the approach. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 58
Annexure V:
Energy Demand Projections
of Land Preparation
Steps in Figure 2.3 are explained below:
1. Mechanised land preparation area: The starting point is the gross cropped area (GCA) as
per the cropping intensity scenario for Current Policy Scenario in Table 2.4. The extent of
mechanisation determines what share of this area is prepared using machines rather than
manual or animal power. The current level of mechanisation in India is 47%. For the base
year 2019, this translates to 93 Mha prepared by tractors or tillers.
2. Methods of land preparation: Mechanised land preparation in India is dominated by tractors,
but power tillers also play a critical role, especially in smallholder farms. While tractors
are known to form the majority of farm power in absolute numbers, exact and recent
data on the shares of tractors and tillers in mechanised farming has not been consistently
documented. That said, the share of mechanical and electrical power in farm power has
risen markedly from just 7% in 1960–61 to over 87% in 2009–10, replacing animate power
sources like animals and humans (Tiwari et al, 2019). Mechanisation trends suggest that
tractors dominate field-level tillage, yet power tillers remain relevant for small, fragmented
farms. Over 85% of Indian farmers are small or marginal holders (owning under 2 hectares
of land), making full-sized tractors expensive or logistically cumbersome. Power tillers are
more cost- efficient, manoeuvrable, and versatile for such small plots, particularly in paddy
and horticultural systems (Rath et al, 2024).
Given the lack of recent national data on the share of tractors and tillers, this module retains
the conservative assumption that for every two power tillers there is one tractor in terms of
land coverage capacity (the hours required to prepare an equivalent area of land), a conversion
metric commonly used in established technical analyses.
Estimating energy demand: The energy requirement for land preparation is estimated by first
determining the work effort—measured as operating hours per hectare, and the corresponding
fuel consumption rate of each implement type. Literature and field studies provide benchmarks
for both hours per hectare and energy per hour, with tractors generally requiring fewer hours
per hectare but consuming more fuel per hour, and power tillers requiring longer operating
times at lower hourly fuel rates (20 hours compared to 8 hours). However, energy intensity
per hectare is not fixed, it can vary substantially depending on soil type, moisture conditions,
implement depth, and operator skill, which influence the number of passes required and the
effective load on the engine. These variations highlight the need for more detailed, crop- and
region-specific studies to capture the true range of energy use across India’s diverse farming
systems. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 59
Annexure V: Energy Demand Projections of Land Preparation
On the basis of these assumptions, energy intensity per-hectare is obtained for tractors and
tillers. These figures are then applied to their respective areas. The results are aggregated to
arrive at total energy demand for land preparation.
E = GCA * Mechanisation (%) * ∑ (A
*
I
v
)
v
Where, A is the area prepared by implement type, I is the energy intensity per hectare, GCA
is the Gross Cropped Area.
This formulation captures both differences in implement efficiency and variations in operating
practices. In the base year, applying these intensities to the mechanized area yields diesel use
consistent with national estimates of agricultural fuel consumption. This methodology is limited
to tractors and power tillers for estimating energy demand. It does not explicitly account for
other forms of mechanisation such as laser land levellers, seed drills, or the emerging role of
drones and automated machinery in land preparation and field management. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 60
1. Strategic opportunities for diversifying areas away from rice to nutri-
cereals in India
Classifying states: Potential for diversification & Potential for rice expansion
The following figure presents an analytical classification of Indian states based on their current
and decadal trends of area, production, and yield (APY) of rice cultivation. To assess their
potential for diversification away from rice, Indian states have been plotted based on two
composite indicators on area and yield, respectively in Figure Annex VI.1.
How to read the graph:
1. X axis–Area composite score = rice area as (%) of the state’s GCA + rice area growth rate
(CAGR) from 2014 to 2023.
2. Y axis–Yield composite score = current rice yield in the states and yield CAGR from 2014
to 2023.
3. Size of the bubble: % of the State’s contribution to India’s total production.
4. Orange states: States where short-term diversification away from rice is feasible due to
sufficient production
of nutri-cereals. This means that public procurement channels in the
states can replace rice with nutri-cereals without trade-offs.
Area composite score (Rice area as % Gross cropped area of the state and state rice area change CAGR)
0.12
01
00.8
00.6
00.4
00.2
00
0 0.1 0.20.40.60.810.30.50.70.91.1 1.2
Yield (State rice yield change - CAGR and rice yield in state)
Nutri-cereals production surplus states
Quadrant II
India Rice area composite score line
India yield composite score line
Quadrant I
Quadrant IV
Quadrant III
KAKA
KLKL
MHMH
GJGJ
RJRJ
UPUP
APAP
HRHR
MPMP
BHBH
TNTN
WBWB
CGCGTLTL
ODOD
JHJH
ASAS
PBPB
JKJK
01
Figure Annex VI.1: State distribution map based on rice area and yield trends (Authors’ analysis)
Annexure VI:
Scenario Rationale Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 61
Annexure VI: Scenario Rationale
Quadrant I: Taking into account both the current levels and growth rates of rice area and yield,
states like Punjab, Haryana, and Telangana exhibit potential for natural diversification away from
rice in the future. Long-term sustainability of rice production remains a concern for these states,
as biophysical constraints such as groundwater depletion and soil health degradation are likely
to create pressure. Some diversification away from rice in these states is expected to occur
gradually, driven more by ecological necessity than immediate economic incentives.
Quadrant II: States in these quadrants show varied potentials for diversification and rice area
expansion. The trajectory of diversification in states like Andhra Pradesh and Jammu and Kashmir
is defined by declining trends in area under rice cultivation, suggesting natural diversification is
occurring. In contrast, states like Uttar Pradesh, Rajasthan, and Karnataka show positive trends
in rice expansion with smaller area under cultivation and higher yields. These states, unlike
the previous two states, remain at risk of future rice expansion, particularly if irrigation access
improves.
Quadrant III: These states currently have low rice cultivation area and yield, but are experiencing
positive growth rates in both, indicating a potential risk of future rice expansion. Kerala is the
only exception, showing a negative growth rate in both area and yield.
Quadrant IV: This group includes states where yields remain low and rice area expansion exhibits
varying trends. These states present a strong case for diversifying some areas away from rice.
Diversification would offer considerable economic and resilience benefits by shifting to crops
better suited to local conditions. This approach aligns with the primary objectives and outcomes
intended under the recently announced PM Dhan Dhanya Krish Yojana (PIB, 2025 (a)).
While states have been identified for diversification away from rice, it is essential to adopt
a phased approach that accounts for the value chain readiness of alternative crops. In the
following suggestive roadmap in Figure Annex VI.2, we focus on diversification to nutri-cereals,
which received strong support from the GoI in recent years.
Suggestive Roadmap: Supporting Diversification through procurement by Food
Welfare Programmes
CONSUMPTION DIVERSIFICATION
Diversify consumption in states where nutri-cereals are
widely produced and consumed
PRODUCTION DIVERSIFICATION
Diversify production in high potential Quadrant IV states
RAMP UP
Achieve full-scale value chain diversification
6 States
HR, KA, MP, MH, RJ, UP
3 States
AS, JH, OD
All 15 States
with diversified procurement
Leveraging PDS, PM POSHAN, POSHAN 2.0
to mainstream diverse crops, improve public health particularly for states with high malnutrition, and shift farmer incentives
EXPANSION
Diversification expands to Quadrant I, II, III states
YEAR
1 & 2
YEAR 5 & 6
YEAR 3 & 4
YEAR 10
Figure Annex VI.2: Crop diversification opportunities from rice to nutri-cereals for India Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 62
Annexure VI: Scenario Rationale
2. Natural farming: A Scalable Agroecological Pathway for India
Natural farming (NF) presents a promising alternative to input-intensive agriculture, particularly
in ecologically fragile and economically vulnerable regions. To scale NF in a way that unlocks its
potential to enhance incomes and resilience of farms while ensuring nutrition security, a phased
approach with strategic focus on specific geographies and communities and leveraging existing
institutional and social capital is essential.
Scaling Natural Farming in rainfed areas for more equitable and sustainable
agricultural growth:
Rainfed agriculture covers 51% of India’s Net Sown Area (NSA) contributes 40% of food
production, and is characterised by low productivity, low input use, and monsoon-dependent
yield volatility (MoAFW, 2024). These rainfed areas face acute climate risks while supporting
81% of the rural poor, including marginal, tribal, and smallholder farmers (Gopinath et al., 2013).
Natural Farming (NF) offers a low-risk, high-reward opportunity for these regions. Transitioning
to Natural Farming (NF) can enhance productivity and help raise farmers’ yields and profitability.
Since a significant proportion of these farmers consume their produce, Natural Farming (NF)
would also appeal to them given its focus on practices that promote health and nutrition, such
as crop diversification (Annex VI.3). It would also help bring stability and resilience to rainfed
farm systems by fostering soil health and practices that focus on climate resilience. The National
Mission on Natural Farming (NMNF) also prioritises rainfed regions for Natural Farming (NF)
scale-up.
To provide chemical-free food for own
family, but will sell chemically farmed
produce to others
As using chemicals for
food production is bad
As produce fetches a higher premium
To improve soil quality
0%40%80%20%60%100%
51%
54%
62%
84%
Figure AnnexVI.3: Motivations of farmers to adopt Natural Farming
Source: Issue Brief - “What drives Natural Farming adoption in India?” Evidence from Farmer Behaviour and Practise
Trends, CEEW (to be published)
Green revolution regions may also hold opportunity hotspots for natural farming,
based on targeted evidence:
India’s Green Revolution (GR) regions, like Punjab, are now grappling with deep-rooted ecological
imbalances. Years of intensive input use, incentivised by input subsidies, have led to declining
soil fertility, falling groundwater tables, and public health concerns linked to excessive pesticide
use. In this context, Natural Farming (NF) offers an opportunity for ecological restoration and Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 63
Annexure VI: Scenario Rationale
enhancing long-term agricultural resilience. However, given that farmers in these regions are
typically risk-averse and yield-focused, the regional hotspots with extreme ecological stress,
putting farm productivity and incomes at high risk of decline, may only offer a window for
Natural Farming (NF) adoption in the short term. Building compelling proofs of concept in
Green Revolution regions with a focused strategy centred on evidence generation and localised
demonstrations would expand the Natural Farming (NF) opportunity in Green Revolution
regions towards the mid-term. Natural Farming (NF) programmes like National Mission on
Natural Farming (NMNF) are also building on similar approaches, targeting the creation of
Natural Farming (NF) clusters in Green Revolution regions with high input use and proximity
to major rivers (MoAFW, 2024).
Field evidence from the APCNF programme suggests that APCNF GPs in traditional Green
Revolution regions such as Godavari and Krishna are witnessing high uptake of natural
biostimulants in portions of their land as they transition into chemical farming with farmers
motivated by health and soil concerns as indicated in Annex VI.4 (Issue Brief - “What drives
Natural Farming adoption in India?” Evidence from Farmer Behaviour and Practise Trends,
CEEW (to be published) ).
Southern Zone
Scarce rainfall zone
North Coastal Zone
Krishna Zone
High Altitude Zone
Godavari Zone
0%40%80%20%60%100%
None Biostimulants only Both biostimulants & fertilisers Fertilisers only
Rabi 2022-23
Figure AnnexVI.4: Biostimulant adoption in different agro-climatic zones in Andhra Pradesh
By promoting diverse, indigenous crops, NF supports prosumption (production consumed in-
house) and better household diets. Aligning NF with nutrition-focused programmes like mid-
day meals, PDS, and ICDS can amplify its adoption and impact on both public health and local
food systems.
The deep reach of SHGS, CRPs, and FPOs across rural India can scale natural
farming through trusted, community-rooted institutions.
Institutionalisation at the community level has emerged as a critical success factor for scaling
sustainable agriculture programmes, with village-level championship models such as Community
Resource Persons playing a particularly important role. (CEEW, 2023). The APCNF initiative Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 64
Annexure VI: Scenario Rationale
exemplifies this approach, leveraging Community Resource Persons (CRPs) to scale Natural
Farming to over one million farmers across 26 districts in Andhra Pradesh in just nine years. This
demonstrates the potential for decentralised, community-driven models to mainstream natural
farming. Importantly, the institutional infrastructure necessary for such initiatives already exists.
India has over 8.3 million Self-Help Groups (SHGs), many integrated into state and National
Rural Livelihood Missions (NRLM). Additionally, networks such as Krishi Sakhis and over 8,000
Farmer-Producer Organisations (FPOs) offer robust platforms for peer-led extension services
(PIB, 2024).
Moreover, these grassroots institutions are particularly active in areas dominated by rainfed
farming and smallholder agriculture, making these regions a clear opportunity hotspot for
natural farming adoption. For instance, in Odisha, Mission Shakti’s SHG network plays a
significant role in districts such as Kandhamal and Rayagada, which face high agroecological
vulnerability yet have a long-standing tradition of ecological farming. In Chhattisgarh’s Bastar
region, SHG federations and Krishi Sakhis are central to farmer engagement, supported by
both state and non-state actors promoting natural farming as a low-cost, climate-resilient
alternative. Decentralised extension systems anchored in CRPs, SHGs, and FPOs not only build
trust and adapt the interventions to local realities but also reduce the transaction costs of
last-mile delivery, making them highly effective in driving behavioural change and embedding
sustainable practices across India’s diverse agricultural landscapes. REFERENCES Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 66
References
1. Agarwal, N., Apoorve, K., & Wal, A. (2023). How to design scalable and sustainable
programmes: Framework for India’s sustainable agriculture initiatives. Council on Energy,
Environment and Water. https://www.ceew.in/sites/default/files/how-can-india-design-
scalable-and-sustainable-programmes-for-sustainable-agriculture- initiatives.pdf
2. Agriculture Statistics. (2024). Agricultural statistics at a glance 2023. Government of
India, Ministry of Agriculture & Farmers Welfare, Department of Agriculture & Farmers
Welfare. https://desagri.gov.in/wp-content/uploads/2024/09/Agricultural- Statistics-at-a-
Glance-2023.pdf
3. APCNF. (n.d.). APCNF – Towards farmer prosperity, better citizen health, climate resilience
and cooling of the planet. https://apcnf.in/global/
4. Barman, A., Saha, P., Patel, S., & Bera, A. (2022). Crop diversification: An effective strategy
for sustainable agriculture development. In V. S. Meena, M. Choudhary, R. P. Yadav, & S. K.
Meena (Eds.), Sustainable crop production: Recent advances (pp. 1–17). IntechOpen. https://
doi.org/10.5772/intechopen.102635
5. Bhuvaneshwari, S., Hettiarachchi, H., & Meegoda, J. N. (2019). Crop residue burning in India:
Policy challenges and potential solutions. International Journal of Environmental Research
and Public Health, 16(5). https://doi.org/10.3390/ ijerph16050832.
6. Birthal, P. S., Khan, M. T., Negi, D. S., & Agarwal, S. (2014). Impact of climate change on
yields of major food crops in India: Implications for food security. Agricultural Economics
Research Review, 27. https://doi.org/10.5958/0974-0279.2014.00019.6
7. Central Electricity Authority-CEA. (2024). All India electricity statistics: General review 2024
(containing data for the year 2022–23). Ministry of Power, Government of India. https://cea.
nic.in/ general-review-report/?lang=en
8. Central Electricity Authority-CEA. (2025). Updated growth report 2025. https://cea.nic.in/
wp-content/uploads/general/2025/Updated_GR_2025_merged_new.pdf
9. CEEW. (2021). Policy Study on Sustainable Agriculture. https://www.ceew.in/sites/ default/
files/ceew-policy-study-on-sustainable-agriculture-india_0.pdf
10. CEEW–IWMI. (2023). Evaluating policy coherence in food, land, and water systems:
Evidence from India. Colombo, Sri Lanka: International Water Management Institute (IWMI).
CGIAR Initiative on National Policies and Strategies. 124p. https://www.ceew.in/publications/
evaluating-policy-coherence-in-food-land-and- water-systems-of-india
11. Chand, R. (2025). Reimagining agriculture for growth, poverty, nutrition, and sustainability.
Journal of the International Association of Agricultural Economists, 1(March). https://doi.
org/10.1111/agec.70015. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 67
References
12. Chhabra, A., Manjunath, K. R., & Panigrahy, S. (2009). Assessing the role of Indian livestock
in climate change. ISPRS Archives, XXXVIII-8/W3, 359–364. https:// www.researchgate.net/
publication/271702897
13. Chuphal, D. S., Kushwaha, A. P., Aadhar, S., & Mishra, V. (2024). Drought atlas of India,
1901–2020. Scientific Data, 11(1), 7. https://doi.org/10.1038/s41597-023- 02856-y
14. DAHD. (2005). 17th Indian Livestock Census: All-India Summary Report. Ministry of
Fisheries, Animal Husbandry & Dairying, Government of India. https://dahd.gov. in/sites/
default/files/2025-05/17thIndianLivestockCensusAll-IndiaSummaryReport. pdf
15. DAHD. (2007). 18th Livestock Census: All India Report. Ministry of Agriculture and Farmers
Welfare, Government of India. https://iss.icar.gov.in/Livestock_ Documents/18th_Livestock_
Census.pdf.
16. DAHD. (2018). Basic Animal Husbandry and Fisheries Statistics 2018. Ministry of Fisheries,
Animal Husbandry & Dairying, Government of India. https://iss.icar.gov. in/.
17. DADH. (2019). 20th Livestock Census: All India Report. Ministry of Fisheries, Animal
Husbandry & Dairying, Government of India. https://ruralindiaonline.org/ en/library/
resource/20th-livestock-census-2019-all-india-report/.
18. DAHD. (2023). Basic Animal Husbandry Statistics 2023. Ministry of Fisheries, Animal
Husbandry & Dairying, Government of India. https://dahd.gov.in/sites/ default/files/2024-10/
BasicAnimalHusbandryStatistics2023.pdf.
19. Das, P., Singh, V., Stevanović, M., Kumar Jha, C., Bodirsky, B. L., Beier, F., Humpenöder, F., Leip,
D., Chen, D. M. C., Crawford, M., von Jeetzen, P., Molina Bacca, E., Soergel, B., Springmann, M.,
Dietrich, J. P., Popp, A., Kumar Gosh, R., & Lotze-Campen, H. (2023). A healthy, sustainable,
and inclusive food system transformation for India. https://foodsystemeconomics.org/wp-
content/uploads/Das-et-al.-2023.pdf
20. Dhruw, U. K., Roy, D. K., & Verma, P. D. (2024). India’s growth in agricultural mechanisation
during last decades. International Journal of Advanced Biochemistry Research, 8(3 Suppl
C), 178–181. https://doi.org/10.33545/26174693.2024. v8.i3Sc.715
21. EMC. (2018). Study of agriculture pump sets in the State of Kerala: Detailed project report.
Energy Management Centre–Kerala https://keralaenergy.gov.in/files/Energy_ Efficiency_
study_of_Agriculture_Pump_sets.pdf
22. FAO. (2021). The state of the world’s land and water resources for food and agriculture –
Systems at breaking point: Synthesis report 2021. Food and Agriculture Organization of
the United Nations. https://doi.org/10.4060/cb7654en
23. FAO. (2024) Food Balance Sheets. Retrieved April 24, 2025. https://www.fao.org/ faostat/
en/#data/FBS.
24. FAO. (2025). Glossary. Retrieved April 24, 2025. https://openknowledge.fao.org/ server/
api/core/bitstreams/317db554-c763-4654-a0d3-24a8488bbc3a/content/status- women-
agrifood-systems-2023/glossary.html
25. Fertiliser Association of India (FAI). (2024). Annual Review of Fertiliser Production and
Consumption 2023–24. https://www.faidelhi.org/member/AR-Full-Rep.pdf.
26. Gogoi, N., Baruah, K. K., & Gupta, P. K. (2008). Selection of rice genotypes for lower
methane emission. Agronomy for Sustainable Development, 28(2), 181–186. https://doi.
org/10.1051/agro:2007052 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 68
References
27. Gómez-Casanovas, N., Mwebaze, P., Khanna, M., Branham, B., Time, A., DeLucia, E. H.,
Bernacchi, C. J., Knapp, A. K., Hoque, M. J., Du, X., Blanc-Betés, E., Barron- Gafford, G. A.,
Peng, B., Guan, K., Macknick, J., Miao, R., & Miljkovic, N. (2023). Knowns, uncertainties, and
challenges in agrivoltaics to sustainably intensify energy and food production. Cell Reports
Physical Science, 4(8), Article 101518. https:// doi.org/10.1016/j.xcrp.2023.101518
28. Gopinath, K. A., Dixit, S., Chary, G. R., Srinivasarao, Ch., Osman, M., Raju, B. M. K., Ramana,
D. B. V., Venkatesh, G., Grover, M., Maheswari, M., & Venkateswarlu,B. (2013). Improving the
rainfed farming systems of small and marginal farmers in Anantapur and Adilabad districts
of Andhra Pradesh. Central Research Institute for Dryland Agriculture, Hyderabad, Andhra
Pradesh. https://www.researchgate.net/ publication/259659509_Improving_the_Rainfed_
Farming_Systems_of_Small_and_ Marginal_Farmers_in_Anantapur_and_Adilabad_
Districts_of_Andhra_Pradesh
29. Gorh, D., & Baruah, K. K. (2019). Estimation of methane and nitrous oxide emission from
wetland rice paddies with reference to global warming potential. Environmental Science
and Pollution Research, 26(12), 11522–11532. https://doi.org/10.1007/ s11356-019-05026-z
30. Government of India, Ministry of Rural Development. (n.d.). SHG count. https:// nrlm.gov.
in/shgReport.do?methodName=showIntensiveStateWiseReport
31. Gupta, N., Pradhan, S., Jain, A., & Patel, N. (2021). Sustainable agriculture in India 2021:
What we know and how to scale up. Council on Energy, Environment and Water (CEEW).
https://www.ceew.in/sites/default/files/CEEW-FOLU-Sustainable- Agriculture-in-India-2021-
20Apr21.pdf
32. IPCC. (2006). 2006 IPCC guidelines for national greenhouse gas inventories: Volume 1:
General guidance and reporting. Task Force on National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change. https://www.ipcc-nggip. iges.or.jp/
public/2006gl/index.html
33. IPCC. (2019). “Interlinkages between Desertification, Land Degradation, Food Security
and Greenhouse Gas Fluxes: Synergies, Trade-offs and Integrated Response Options.” In
Climate Change and Land: an IPCC Special Report on Climate Change, Desertification,
Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas
Fluxes in Terrestrial Ecosystems. N.p.: Intergovernmental Panel on Climate Change. https://
www.ipcc.ch/site/assets/uploads/sites/4/2022/11/ SRCCL_Chapter_6.pdf?utm_source .
34. IPCC. (2014). The IPCC Fifth Assessment Report. https://www.ipcc.ch/site/assets/
uploads/2018/04/ipcc_ar5_leaflet.pdf.
35. Indian Dairy Association. (2012). 19th Livestock Census – 2012: All India Report. https://
indiandairyassociation.org/pdf/info/19th-Livestock-Census-2012.pdf
36. Jha, C. K., Singh, V., Stevanović, M., Dietrich, J. P., Mosnier, A., Weindl, I., Popp, A., Schmidt-
Traub, G., Ghosh, R. K., & Lotze-Campen, H. (2022). The role of food and land use systems
in achieving India’s sustainability targets. Environmental Research Letters, 17(7), 074022.
https://doi.org/10.1088/1748-9326/ac788a
37. John, S., & Babu, S. (2021). Lessons from the aftermaths of the Green Revolution on food
system sustainability in India. Frontiers in Sustainable Food Systems, 5, 644559. https://doi.
org/10.3389/fsufs.2021.644559 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 69
References
38. Kumar, R., Kumar, S., Yashavanth, B. S., Meena, P. C., Indoria, A. K., Kundu, S., & Manjunath,
M. (2020). Adoption of natural farming and its effect on crop yield and farmers’ livelihood
in India (ICAR-National Academy of Agricultural Research Management, Hyderabad, India).
https://www.niti.gov.in/sites/default/files/2021-03/NaturalFarmingProjectReport-ICAR-
NAARM.pdf
39. Lewis, W. A. (1954). Economic Development with Unlimited Supplies of Labour. University
of Texas. https://la.utexas.edu/users/hcleaver/368/368lewistable.pdf.
40. Meghalaya State Organic and Natural farming Policy 2023. https://investmeghalaya. gov.in/
resources/homePage/17/megeodb/policies/farming2023.pdf?utm
41. Mishra, G. K., & Tiwari, R. P. (2014). Infertility management protocols for dairy animals. Indian
Dairyman. https://www.researchgate.net/profile/Girish-Mishra-5/publication/322124388_
Infertility_Management_of_Dairy_Animals/links/5a463187a6fdcce1971a9c4d/Infertility-
Management-of-Dairy-Animals.pdf
42. MoAFW. (2017). Doubling Farmers’ Income Report. In Doubling Farmers’ Income–Volume I
March of Agriculture Since Independence and Growth Trends. Ministry of Agriculture and
Farmers’ Welfare. https://agriwelfare.gov.in/Documents/ DFIpercent20Volume%201.pdf.
43. MoAFW. (2021). All India Report on Input Survey 2016-17. Agriculture Census. https://
agcensus.da.gov.in/document/is2016/air_is_16-17_210121-final_220221.pdf.
44. MoAFW. (2022). Agricultural statistics at a glance 2022. Directorate of Economics and
Statistics, Department of Agriculture and Farmers Welfare, Government of India. https://
desagri.gov.in/wp-content/uploads/2023/05/Agricultural-Statistics-at- a-Glance-2022.pdf
45. MoAFW. (2024). National Mission on Natural Farming (NMNF) Operational Guidelines.
46. https://agriwelfare.gov.in/Documents/HomeWhatsNew/GuidelineofNMNF_
FinalApproved_27122024.pdf
47. MoAFW. (2024). Rainfed Farming System. Department of Agriculture and Farmers Welfare,
Government of India. https://agriwelfare.gov.in/en/RainfedDiv
48. MoEFCC. (2004). India’s Initial National Communication to the United Nations Framework
Convention on Climate Change. Ministry of Environment, Forest and Climate Change,
Government of India. https://unfccc.int/resource/docs/natc/indnc1. pdf
49. MoEFCC. (2018). India: Second Biennial Update Report to the United Nations Framework
Convention on Climate Change. Ministry of Environment, Forest and Climate Change,
Government of India. https://unfccc.int/sites/default/files/resource/ INDIA%20SECOND%20
BUR%202018.pdf
50. MoEFCC. (2021). India: Third Biennial Update Report to the United Nations Framework
Convention on Climate Change. Ministry of Environment, Forest and Climate Change,
Government of India. https://unfccc.int/sites/default/files/resource/ INDIA_%20BUR-
3_20.02.2021_High.pdf
51. MoEFCC. (2022). India’s Long-Term Low-Carbon Development Strategy. Ministry of
Environment, Forest and Climate Change, Government of India. https://moef.gov. in/
uploads/2022/11/Indias-LT-LEDS.pdf
52. MoEFCC. (2023). India: Third National Communication and Initial Adaptation Communication
to the United Nations Framework Convention on Climate Change. Ministry of Environment,
Forest and Climate Change, Government of India. https:// unfccc.int/sites/default/files/
resource/India-TNC-IAC.pdf Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 70
References
53. MoEFCC. (2024). India Fourth Biennial Update Report. United Nations Framework
Convention on Climate Change. https://unfccc.int/sites/default/files/resource/ India%20
BUR-4.pdf.
54. MoF. (2024). Economic Survey of India 2023-24. Government of India. Ministry of
Finance, Department of Economic Affairs. India Budget. https://www.indiabudget. gov.in/
economicsurvey/doc/eschapter/echap01.pdf.
55. MoF. (2025). Economic Survey of India 2024-25. Government of India. Ministry of
Finance, Department of Economic Affairs. India Budget. https://www.indiabudget. gov.in/
economicsurvey/doc/echapter.pdf.
56. Mohanty, S., Swain, C. K., Sethi, S. K., Dalai, P. C., Bhattacharyya, P., Kumar, A., Tripathi, R.,
Shahid, M., Panda, B. B., Kumar, U., Lal, B., Gautam, P., Munda, S., & Nayak, A. K. (2017).
Crop establishment and nitrogen management affect greenhouse gas emission and
biological activity in tropical rice production. Ecological Engineering, 104, 80–98. https://
doi.org/10.1016/j.ecoleng.2017.03.014
57. MoJS. (2024). 5th Minor Irrigation Census (MIC). Department of Water Resources, River
Development and Ganga Rejuvenation, Ministry of Jal Shakti, Government of India. https://
mowr.nic.in/irrigationcensus/
58. MPI. (2017). New Zealand Agriculture: A Policy Perspective (Document No. 27282).
Ministry for Primary Industries, Wellington, New Zealand. https://www.mpi.govt.nz/
dmsdocument/27282-New-Zealand-Agriculture
59. NAAS. (2013). Livestock Infertility and Its Management (Policy Paper No. 59). National
Academy of Agricultural Sciences, New Delhi. https://naas.org.in/Policy%20 Papers/
policy%2059.pdf
60. Nirmala, B., Tuti, M. D., Kumar, R. M., Waris, A., Muthuraman, P., Parmar, B., & Singh, T. V.
(2021). Integrated assessment of system of rice intensification vs. conventional method of
transplanting for economic benefit, energy efficiency and lower global warming potential
in India. Agroecology and Sustainable Food Systems, 45(4), 475–495. https://doi.org/10.10
80/21683565.2020.1868648
61. NITI Aayog. (2022). A New Paradigm for Indian Agriculture: From Agroindustry to
Agroecology. Government of India. https://www.niti.gov.in/sites/default/files/2023-03/A-
New-Paradigm-for-Indian-Agriculture-from-Agroindustry-to-Agroecology. pdf.
62. NITI Aayog. (2024). NITI Aayog Working Group Report on Crop Husbandry, Agricultural
Inputs, Demand and Supply 2024. Retrieved January 30, 2025, from https://www.niti.
gov.in/sites/default/files/2024-02/Working%20Group%20 Report%20on%20Demand%20
%26%20Supply%20Final_V9.pdf .
63. Odisha Government (Mission Shakti). (2022). Mission Shakti: A Silent Revolution [Coffee-
table book]. Women & Child Development and Mission Shakti Department, Government of
Odisha. https://missionshakti.odisha.gov.in/sites/default/ files/2022-03/Coffee-table-book.
pdf
64. OECD. (2019). Enhancing Climate Change Mitigation through Agriculture. OECD Publishing,
Paris. https://doi.org/10.1787/e9a79226-en
65. Parthasarathi, T., Vanitha, K., Mohandass, S., & Vered, E. (2019). Mitigation of methane
gas emission in rice by drip irrigation. F1000Research. https://doi. org/10.12688/
f1000research.20945.1 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 71
References
66. Pathak, H. (2015). Greenhouse gas emission from Indian agriculture: Trends, drivers and
mitigation strategies. Proceedings of the Indian National Science Academy, 81(5), 1133–1149.
https://doi.org/10.16943/ptinsa/2015/v81i5/48333
67. Patange, O., Purohit, P., Avashia, V., Klimont, Z., & Garg, A. (2024). Mitigation of non-CO2
greenhouse gases from Indian agriculture sector. Environmental Research Letters, 9. https://
doi.org/10.1088/1748-9326/ad4e4e
68. PIB. (2011). Foodgrain Production Reaches Record 241.6 Million Tonnes. Press Information
Bureau. https://www.pib.gov.in/newsite/PrintRelease.aspx?relid=75978
69. PIB. (2019). 4th Advance Estimates of production of major crops for 2018-19. https://www.
pib.gov.in/Pressreleaseshare.aspx?PRID=1582362
70. PIB. (2021). Productivity of Dairy Animals. Press Information Bureau. https://pib.gov.
in/PressReleaseIframePage.aspx?PRID=1707187#:~:text=As%20per%20Integrated%20
Sample%20Survey,(as%20per%20FAO%20Statistics).
71. PIB. (2022a). Milk Production in India: The Journey of India’s Dairy Sector. N.p.: Press
Information Bureau. https://pib.gov.in/FeaturesDeatils. aspx?NoteId=151137®=3&lang=1.
72. PIB. (2022b). Increased foodgrain production in India: Six-fold rise in foodgrain production
since independence. Press Information Bureau, Government of India. https://static.pib.gov.
in/WriteReadData/specificdocs/documents/2022/jul/ doc202272874801.pdf
73. PIB. (2022c). Cabinet approves India’s updated nationally determined contribution to
be communicated to the United Nations Framework Convention on Climate Change.
Press Information Bureau, Government of India. https://pib.gov.in/PressReleasePage.
aspx?PRID=1847813
74. PIB. (2023). Press release. Government of India. https://pib.gov.in/PressReleseDetailm.
aspx?PRID=1939473®=3&lang=1
75. PIB. (2024). 8,875 FPOs have been registered across the country. Press Information Bureau,
Government of India. https://www.pib.gov.in/PressReleaseIframePage. aspx?PRID=2040845
76. PIB. (2025a). India submits its 4th Biennial Update Report to the United Nations Framework
Convention on Climate Change. Press Information Bureau, Government of India. https://
www.pib.gov.in/PressReleasePage.aspx?PRID=2089589
77. PIB. (2025b). India’s renewable revolution: Building clean power, made in India [Factsheet
No. 149232]. Press Information Bureau, Government of India. https:// www.pib.gov.in/
FactsheetDetails.aspx?Id=149232
78. PMO. (2023). PM launches ‘Viksit Bharat @2047: Voice of Youth’. Prime Minister’s Office,
Government of India. https://www.pmindia.gov.in/en/news_updates/pm- launches-viksit-
bharat-2047-voice-of-youth/
79. Prabhu, S., & Chitale, V. (2024). Decoding India’s changing monsoon patterns – A tehsil-level
assessment. Council on Energy, Environment and Water. https://www. ceew.in/sites/default/
files/decoding-how-climate-change-is-changing-monsoon- rainfall-patterns-in-india.pdf
80. Rajasthan Organic Farming Policy. (2017). Rajasthan organic farming policy 2017. Department
of Agriculture, Government of Rajasthan. https://cuts-cart.org/pdf/ Rajasthan_Organic_
farming_Policy-2017.pdf
81. Ramesh, T., & Selvaraj, R. (2020). Evaluation of rice cultivation systems for greenhouse gas
emissions and productivity. Tamil Nadu Agricultural University. https://www. researchgate. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 72
References
net/publication/342347798_Evaluation_of_rice_cultivation_systems_ for_greenhouse_
gases_emission_and_productivity
82. Rao, A. (2024). Farm mechanisation in India’s agriculture sector: Challenges and opportunities.
India Briefing. https://www.india-briefing.com/news/india-farm- mechanisation-sector-
opportunities-challenges-31243.html
83. Rath, I., Pradhan, P. L., Dash, R. C., Mahapatra, M., Sahoo, P. K., Behera, D., Behera, A.,
& Kamendra. (2024). Mapping the dynamics of agriculture mechanisation: Present
dynamics and future trajectories. International Journal of Agriculture Extension and Social
Development, 7(3), 181–186. https://doi.org/10.33545/26180723.2024. v7.i3c.425
84. Reddy, D. N., & Motkuri, V. (2013). SRI cultivation in Andhra Pradesh: Achievements, problems
and implications for GHGs and work (MPRA Paper No. 52115). National Institute of Rural
Development (NIRD). https://mpra.ub.uni-muenchen.de/52115/
85. Richards, M., & Sander, B. O. (2014). Alternate wetting and drying in irrigated rice. CGIAR
Research Program on Climate Change, Agriculture and Food Security (CCAFS). https://www.
researchgate.net/publication/306372935_Alternate_wetting_ and_drying_in_irrigated_
rice_Implementation_guidance_for_policymakers_and_ investors
86. Sharma, B., Gulati, A., Mohan, G., Manchanda, S., Ray, I., & Amarasinghe, U. (2018). Water
productivity mapping of major Indian crops. National Bank for Agriculture and Rural
Development (NABARD) & Indian Council for Research on International Economic Relations
(ICRIER).https://www.nabard.org/auth/writereaddata/tender/1806181128Water%20
Productivity%20Mapping%20of%20 Major%20Indian%20Crops,%20Web%20Version%20
(Low%20Resolution%20 PDF).pdf
87. Sharma, H. R. (2023). Patterns, sources and determinants of agricultural growth in
India. Indian Journal of Agricultural Economics, 78(1). https://isaeindia.org/wp- content/
uploads/2023/04/2-H-R-SHARMA-KEYNOTE-PAPER.pdf
88. Sharma, S., Das, P., Chaturvedi, C., & Malyan, A. (2024). Sustainable rice cultivation in India.
Council on Energy, Environment and Water (CEEW).
89. Shukla, A. K., Behera, S. K., Chaudhari, S. K., & Singh, G. (2022). Fertiliser use in Indian
agriculture and its impact on human health and environment. Indian Journal of Fertiliser,
18(3), 218–237
90. Singh, B. (2023). Nitrogen use efficiency in crop production in India: Trends, issues, and
challenges. Agriculture Research, 12, 32–44. https://link.springer.com/ article/10.1007/
s40003-022-00626-7
91. Singh, V., Rastogi, A., Nautiyal, N., & Negi, V. (2017). Livestock and climate change: The key
actors and the sufferers of global warming. Indian Journal of Animal Sciences, 87(1), 11–20.
https://doi.org/10.56093
92. Tiwari, P. S., Singh, K. K., Sahni, R. K., & Kumar, V. (2019). Farm mechanization – Trends and
policy for its promotion in India. Indian Journal of Agricultural Sciences, 89(10), 1559–1565.
https://doi.org/10.56093/ijas.v89i10.94575
AGRICULTURE
SCENARIOS TOWARDS VIKSIT BHARAT AND NET ZERO
(VOL. 6) SCENARIOS TOWARDS
VIKSIT BHARAT AND NET ZERO
SECTORAL INSIGHTS:
AGRICULTURE
(VOL. 6) Copyright © NITI Aayog, 2026
NITI Aayog
Government of India,
Sansad Marg, New Delhi–110001, India
Suggested Citation
NITI Aayog. (2026). Scenarios Towards Viksit Bharat and Net Zero -
Agriculture (Vol. 6)
Available at: https://niti.gov.in/publications/division-reports
Disclaimer
1. This document is not a statement of policy by the National Institution for
Transforming India (hereinafter referred to as NITI Aayog). It has been prepared
by the Green Transition, Energy, Climate, and Environment Division of NITI Aayog
under various Inter-Ministerial Working Groups (IMWGs) constituted to develop Net
Zero pathways for India.
2. Unless otherwise stated, NITI Aayog, in this regard, has not made any representation
or warranty, express or implied, as to the completeness or reliability of the
information, data, findings, or methodology presented in this document. While due
care has been taken by the author(s) in the preparation of this publication, the
content is based on independently procured information and analysis available at
the time of writing and may not reflect the most current policy developments or
datasets.
3. The assertions, interpretations, and conclusions expressed in this report are those
of the author(s) and do not necessarily reflect the views of NITI Aayog or the
Government of India, unless otherwise mentioned. As such, NITI Aayog does not
endorse or validate any of the specific views or policy suggestions made herein by
the author(s).
4. NITI Aayog shall not be liable under any circumstances, in law or equity, for any
loss, damage, liability, or expense incurred or suffered as a result of the use of or
reliance upon the contents of this document. Any reference to specific organisations,
products, services, or data sources does not constitute or imply an endorsement
by NITI Aayog. Readers are encouraged to independently verify the data and
conduct their analysis before forming conclusions or taking any policy, academic,
or commercial decisions. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture v Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture vii
Working group members
and Authors
Chairperson
Prof. Ramesh Chand
Member, NITI Aayog
Leadership
Sh. Suman Berry
Vice chairman, NITI Aayog
Sh. B.V.R. Subrahmanyam
CEO, NITI Aayog
Dr. Anshu Bhardwaj
Programme Director, Green Transition and
Climate Change Division
Sh. Amit Verma
Former Director, Green Transition and Climate
Change, NITI Aayog;
Joint Secretary, Ministry of Commerce and
Industry
Authors
NITI Aayog
Dr. Anjali Jain
Consultant, NITI Aayog
Sh. Nitin Bajpai
Consultant, NITI Aayog
Dr. Priyanka Sarkar
Consultant, NITI Aayog
Sh. Venugopal Mothkoor
Energy and Climate Modelling Specialist,
NITI Aayog
Council on Energy, Environment
and Water (CEEW)
Dr. Chandan Jha
Programme Lead, CEEW
Ms. Nikhitha Jagadeesh
Programme Associate, CEEW
Sh. Apoorve Khandelwal
Fellow, Sustainable Food Systems,CEEW
Ms. Aastha Bafna
Research Analyst, CEEW
Sh. Abhishek Jain
Director and Fellow, Green Economy and
Impact Innovations, CEEW
Ms. Kumari Amisha Patel
Research Analyst, CEEW
Dr. Joy Rajbhanshi,
Programme Lead, CEEW
Ms. Mani Deshmukh
Research Analyst, CEEW
Sh. Gursimer Singh Gulati
Research Analyst, CEEW
Dr. Vaibhav Chaturvedi
Senior Fellow, CEEW Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture viii
Working group members and Authors
Core Modelling Team
NITI Aayog
Dr. Anjali Jain
Consultant, NITI Aayog
Sh. Nitin Bajpai
Consultant, NITI Aayog
Dr. Priyanka Sarkar
Consultant, NITI Aayog
Sh. Venugopal Mothkoor
Energy and Climate Modelling Specialist,
NITI Aayog
Council on Energy, Environment
and Water (CEEW) - Lead
Dr. Chandan Jha
Programme Lead, CEEW
Ms. Nikhitha Jagadeesh
Programme Associate, CEEW
Ms. Aastha Bafna
Research Analyst, CEEW
Peer Reviewer
Dr. Sivendra Kumar Srivastava
Senior Scientist, ICAR-NIAP
Working Group Coordinators
Dr. Priyanka Sarkar
Consultant, NITI Aayog
Ms. Diana Datta
Young professional, NITI Aayog
Ms. Aastha Singh
Young professional, NITI Aayog
Working Group Members
Sh. Franklin L. Khobung
Joint Secretary, Ministry of Agriculture and
Family Welfare (MoAFW)
Sh. N.K. Shah
Joint Secretary, Ministry of Environment,
Forest and Climate Change (MoEFCC)
Sh. Raman Mathur
Ministry of Rural Development (MoRD)
Sh. Rakesh Kumar Verma
Additional Secretary, Ministry of Jal Shakti
(MoJS)
Dr. Faiz Ahmed Kidwai
Former Chief Executive Officer (CEO),
National Rainfed Agriculture Authority
(NRAA)
Sh. Dhura Ram
Additional Commissioner (NRM/RFS),
Department of Agriculture and Farmer
Welfare (DoAFW)
Sh. Bhushan Tyagi
Joint Commissioner, Department of Animal
Husbandry and Dairying (DAHD)
Sh. Ajay Raghava
Deputy Director,
Ministry of Environment, Forest and Climate
Change (MoEFCC)
Dr. Zoya Rizvi
Deputy Commissioner at National Health
Mission, Ministry of Health and Family
Welfare (MoHFW)
Sh. Sharath Kumar Pallerla
Scientist G, Ministry of Environment, Forest
and Climate Change (MoEFCC)
Sh. Manoj Kumar
Director General, PPAC, Ministry of Petroleum
and Natural Gas (MoPNG)
Dr. Suresh Kumar Chaudhary
Former Deputy Director General (NRM), ICAR
Dr. Raghavendra Bhatta
Deputy Director General (Animal Science),
Indian Council of Agricultural Research (ICAR) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture ix
Working group members and Authors
Dr. Shyam Narayan Jha
Deputy Director General (Agricultural
Engineering), Indian Council of Agricultural
Research (ICAR)
Dr. A. Velmurugan
Assistant Director General (Soil and Water
Management), Indian Council of Agricultural
Research (ICAR)
Dr. Pratap S. Birthal
Director, National Institute of Agricultural
Economics and Policy Research (ICAR-NIAP)
Dr. Nitin Tyagi
Principal Scientist, National Dairy Resarch
Institute (ICAR-NDRI)
Dr. Goutam Mondal
Scientist, National Dairy Resarch Institute
(ICAR-NDRI)
Dr. Sunil Kumar
Director, Indian Institute of Farming Systems
Research (ICAR-IIFSR)
Dr. Vasu D
Scientist, National Bureau of Soil Survey and
Land Use Planning (ICAR -NBSS & LUP)
Dr. Pradeep Kumar Malik
Senior Scientist, National Institute of Animal
Nutrition and Physiology (ICAR - NIANP)
Dr. Pradeep Dogra
Principal Scientist, Indian Institute of Soil and
Water Conservation (ICAR - IISWC)
Dr. Pankaj Kaushal
Former Director, Indian Grassland and Fodder
Research Institute (ICAR-IGFRI)
Dr. Purushottam Sharma
Principal Scientist, Indian Grassland and
Fodder Research Institute (ICAR-IGFRI)
Dr. S.P. Datta,
Former Director, Indian Institute of Soil
Science (ICAR-IISS)
Dr. Ayyandar Arunchalam
Director, Central Agroforestry Research
Institute (ICAR-CAFRI)
Dr. Vinod Kumar Singh
Director, Central Research Institute for
Dryland Agriculture (ICAR - CRIDA)
Dr. Hemalatha N
Former Director, ICMR-National Institute of
Nutrition (NIN)
Dr. Vineeta Kumari
Deputy Director, MANAGE
Sh. Kamal Pandey
Deputy Director, Forest Survey of India
Dr. Indu K Murthy
Sector Head, Center for Study of Science,
Technology and Policy (CSTEP)
Sh. Kaveri Ashok
Research Scientist, Center for Study of
Science, Technology and Policy (CSTEP)
Dr. Ruchika Singh
Executive Programme Director, World
Resources Institute (WRI)
Dr. Chandrashekhar Biradar
Former Country Director, Centre for
International Forestry Research (CIFOR -
ICRAF)
Dr. Kavi Kumar
Professor, Madras School of Economics
(MSE)
Collaborators/Expert Consultants
Dr. Sivendra Kumar Srivastava
Senior Scientist, National Institute of
Agricultural Economics and Policy Research
(ICAR-NIAP)
Dr. Sivaramane N
Senior Scientist, National Academy of
Agricultural Research Management (ICAR-
NAARM) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture x
Working group members and Authors
Dr. Ranjit Kumar Paul
Senior Scientist, Indian Agricultural Statistics
Research Institute(ICAR-IASRI)
Dr. Niveta Jain
Principal Scientist, Indian Agricultural
Research Institute (ICAR-IARI)
Dr. Arti Bhatia
Principal Scientist, Indian Agricultural
Research Institute (ICAR-IARI)
Dr. V. Ramamurthy
Principal Scientist, National Bureau of Soil
Survey and Land Use Planning (ICAR -NBSS
& LUP)
Dr. Ram Kanwar Malik
India Country Coordinator and senior
agronomist at CIMMYT
Dr. Raman Meenakshi Sundaram
Director, Indian Institute of Science Research
(ICAR-IIRR)
Dr. Vasu D
Scientist, National Bureau of Soil Survey and
Land Use Planning (ICAR -NBSS & LUP)
Sh. V.P. Singh
Director(AHS), Department of Animal
Husbandry and Dairying (DAHD)
N. Ravishankar
Project Coordinator and Principal Scientist,
Indian Institute of Farming Systems Research
(IIFSR)
Editor
Ms. Aastha Manocha
Editor and Communication Consultant
Communication and Research &
Networking Division, NITI Aayog
Ms. Anna Roy
Programme Director, Research & Networking
Sh. Yugal Kishore Joshi
Lead, Communication
Ms. Keerti Tiwari
Director, Communication
Dr. Banusri Velpandian
Senior Specialist, Research & Networking
Ms. Sonia Sachdeva Sharma
Consultant, Communication
Sh. Souvik Chongder
Young Professional, Communication
NITI Design Team
NITI Maps & Charts Team Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xi
Contents
List of Figures xii
List of Tables xiv
List of Abbreviations xv
Executive Summary xix
Background xxvi
1. Introduction.....................................................................................................................................1
1.1. Historical trends in agricultural production and growth 2
1.2. Climate change, agriculture vulnerability and emissions profile 4
1.3. Historical trends in non-energy emissions from agriculture sector 6
2. Methodology.................................................................................................................................11
2.1 Approach to Estimating Mitigation Co-Benefits of Non-Energy Agricultural pathways 12
2.2 Energy demand estimations for agriculture 23
3. Results...........................................................................................................................................27
3.1 Non-Energy Emissions Pathways in Agriculture 28
3.2 Energy Emissions Pathways in Agriculture 37
4. Key Challenges and suggestions..............................................................................................41
4.1 Key Challenges 42
4.2 Suggestions for Sustainable Long-Term Pathways for Agriculture and Allied Sectors 44
Annexures............................................................................................................................................49
Annexure I: Country-Specific Emission Factors for the Study 50
Annexure II: Policy Typologies 52
Annexure III: Emissions in Sustainable Rice Systems 54
Annexure IV: Energy Demand Projections of Irrigation Pumping 56
Annexure V: Energy Demand Projections of Land Preparation 58
Annexure VI: Scenario Rationale 60
References...........................................................................................................................................65 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xii
List of Figures
Figure E.1: Overall agriculture (non-energy) emissions in Current Policy Scenario
and Net Zero Scenario (2019-2070) xxi
Figure E.2: Livestock sub-sector emissions in Current Policy Scenario and Net Zero Scenario
(2019-2070) xxii
Figure E.3: Crop sub-sector emissions in Current Policy Scenario and Net Zero Scenario
(2019-2070) xxii
Figure E.4: Overall energy consumption (Mtoe) in Agriculture Sector (2020-2070) xxiii
Figure 1.1: Historical trends in rice acreage (2011-2019) 2
Figure 1.2: Historical trends in rice yields (2011-2019) 3
Figure 1.3: Historical trends in rice production (2011-2019) 3
Figure 1.4: Historical trend of milk productivity (2011-2019) 4
Figure 1.5: Trends in share of female bovines in total herd composition (2003 – 2019) 4
Figure 1.6: India’s historical trends of agriculture non-energy emissions (AR2) (2011-2019) 5
Figure 1.7: Historical trends of emissions from rice cultivation (AR2) (2011-2019) 7
Figure 1.8: Trends of cropping intensity (2011-2019) 7
Figure 1.9: Total nitrogen fertiliser consumption (2011-2019) 8
Figure 1.10: Emissions from agricultural soils (AR2) (2011-2019) 8
Figure 1.11: Historical milk production (2011-2019) 9
Figure 1.12: Historical livestock emissions (AR2) (2011-2019) 10
Figure 2.1: Agriculture emission modelling methodology 12
Figure 2.2: Irrigation module for energy demand projections 24
Figure 2.3: Land preparation module for energy demand projections 24
Figure 3.1: Gross cropped area projection (2000 to 2070) 28
Figure 3.2: Production projections of bovine milk (2000-2070) 29
Figure 3.3: Projected agriculture emission under Current Policy Scenario
and Net Zero Scenario (2019-2070) 30
Figure 3.4: Overall emissions – Livestock sub-sector (2019-2070) 30
Figure 3.5: Overall emissions – Crop sub-sector (2019-2070) 31
Figure 3.6: Rice cultivation emission trends in Current Policy Scenario and Net Zero Scenario
(2019-2070) 32 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xiii
List of Figures
Figure 3.7: Area under rice cultivation in Current Policy Scenario (2019-2070) 32
Figure 3.8: Area under rice cultivation in Net Zero Scenario (2019-2070) 33
Figure 3.9: Rice production from 2019 to 2070 under Current Policy Scenario
and Net Zero Scenario Rice area (2019-2070) 33
Figure 3.10: Agricultural soil emission trends in Current Policy Scenario and Net Zero Scenario
(2019-2070) 34
Figure 3.11: Cropping intensity in Current Policy Scenario and Net Zero Scenario (2019-2070) 34
Figure 3.12: Nitrogen fertiliser consumption per ha in Current Policy Scenario
and Net Zero Scenario (2019-2070) 35
Figure 3.13: Area under Natural and Chemical-free farming Current Policy Scenario
and Net Zero Scenario 35
Figure 3.14: Emissions from livestock sector in Current Policy Scenario
and Net Zero Scenario (2019-2070) 36
Figure 3.15: Milk yield trends in Current Policy Scenario and Net Zero Scenario (2019-2070) 37
Figure 3.16: Share of in-milk bovine population in the total bovine population (2019-2070) 37
Figure 3.17: Overall energy consumption in Agriculture Sector (2020-2070) 38
Figure 3.18a: Energy demand and fuel mix in agricultural pumping under Current Policy Scenario
(CPS) and Net Zero Scenario (NZS) by 2050 and 2070 38
Figure 3.18b: Energy demand and fuel mix in land preparation under Current Policy Scenario
(CPS) and Net Zero Scenario (NZS) by 2050 and 2070 39
Figure Annex VI.1: State distribution map based on rice area and yield trends 60
Figure Annex VI.2: Crop diversification opportunities from rice to nutri-cereals for India 61
Figure AnnexVI.3: Motivations of farmers to adopt Natural Farming 62
Figure AnnexVI.4: Biostimulant adoption in different agro-climatic zones in Andhra Pradesh 63 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xiv
Table E.1: Long-term (non-energy) pathways and assumptions for the agriculture sector xx
Table E.2: Long-term energy transition pathways and assumptions for the agriculture sector xx
Table E.3: Key drivers for achieving 26% of mitigation co-benefits in 2070 xxiii
Table 1.1: Description of agricultural emissions categories and their sources 6
Table 2.1: Emission estimation methodology for various categories considered for the
agriculture sector (MoEFCC, 2021) 14
Table 2.2: Emission estimation methodology for various categories considered
for the agriculture sector 14
Table 2.3: Policy typologies mapped against their potential mitigation co-benefits 15
Table 2.4: Key assumptions for 2047 and 2070 17
Table 2.4a: Assumptions of cropping intensity in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 18
Table 2.4b: Assumptions of area-based crop diversification in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 19
Table 2.4c: Assumptions of sustainable yield intensification in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 20
Table 2.4d: Assumptions of chemical-free farming in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 21
Table 2.4e: Assumptions of fertiliser uptake in Current Policy Scenario and Net Zero Scenario
(from Table 2.4) 21
Table 2.4f: Assumptions of sustainable rice cultivation practices in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 22
Table 2.4g: Assumptions of enhanced in- milk bovine productivity in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 22
Table 2.4h: Assumptions of increasing share of the in-milk population in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 23
Table 2.4i: Assumptions of reduced burning of crop residue in Current Policy Scenario
and Net Zero Scenario (from Table 2.4) 23
Table 2.5: Assumptions for estimating energy consumption for irrigation under
Current Policy Scenario and Net Zero Scenario 25
Table 2.6: Assumptions for estimating energy demand for land preparation under
Current Policy Scenario and Net Zero Scenario 26
Table 3.1: Agriculture emission trends across crop and livestock sub-sectors (2019 to 2070) 30
List of Tables Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xv
List of Abbreviations
AFOLU Agriculture, Forestry, and Other Land Use
AIBPAccelerated Irrigation Benefits Programme
ANNArtificial Neural Network
APCNF Andhra Pradesh Community Managed Natural Farming
APYArea, Production, and Yield
AR5Fifth Assessment Report
ARIMA Autoregressive Integrated Moving Average
AWBAgricultural Waste Burning
AWDAlternate Wetting and Drying
BGREI Bringing Green Revolution to Eastern India
BioE3 Biotechnology for Economy, Environment and Employment
BPKPBharatiya Prakritik Krishi Paddhati
BRCBiodiversity Resource Centres
BUR4Fourth Biennial Update Report
CAGRCompound Annual Growth Rate
CBGCompressed Biogas
CDPCrop Diversification Programme
CGIAR Consultative Group on International Agricultural Research
CHCCustom Hiring Centres
CPSCurrent Policy Scenario
CRMCrop Residue Management
CRPCommunity Resource Person
DAHDDepartment of Animal Husbandry and Dairying
DIDrip Irrigation
DSRDirect Seeded Rice
FAIFertiliser Association of India
FAOFood and Agriculture Organization
FPOsFarmer Producer Organisations
FUEFertiliser uptake/use efficiency
GCAGross Cropped Area
GDPGross Domestic Product
GHGGreenhouse Gas
GoIGovernment of India
GPGram Panchayat
GWPGlobal Warming Potential Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xvi
HYVHigh-Yielding Varieties
IAMIntegrated Assessment Modelling
ICARIndian Council of Agricultural Research
ICDSIntegrated Child Development Services
IGFRI ICAR-Indian Grassland and Fodder Research Institute
INMIntegrated Nutrient Management
IPCCIntergovernmental Panel on Climate Change
IVFIn-Vitro Fertilisation
LT-LEDS Long-Term Low-Carbon Development Strategy
MhaMillion Hectares
MMManure Management
MoAFW Ministry of Agriculture & Farmers’ Welfare
MoEFCC Ministry of Environment, Forest and Climate Change
MTMillion Tonnes
MtCO
2
e Millions Tonnes of Carbon Dioxide equivalent
NAASNational Academy of Agricultural Sciences
NDCNationally Determined Contributions
NFNatural Farming
NFSANational Food Security Act
NFSMNational Food Security Mission
NICRA National Innovations in Climate Resilient Agriculture
NITI Aayog National Institution for Transforming India Aayog
NMMNational Millet Mission
NMNF National Mission on Natural Farming
NMSA National Mission for Sustainable Agriculture
NPOP National Programme for Organic Production
NRLM National Rural Livelihood Mission
NSA Net Sown Area
NUE Nitrogen Use Efficiency
NZSNet Zero Scenario
OECD Organisation for Economic Co-operation and Development
PDS Public Distribution System
PGS Participatory Guarantee System
PIB Press Information Bureau
PKVY Paramparagat Krishi Vikas Yojana
PM POSHAN Pradhan Mantri Poshan Shakti Nirman
PMDDKY PM Dhan Dhanya Krishi Yojana
PMGKAY Pradhan Mantri Garib Kalyan Anna Yojana
PMKSY Pradhan Mantri Krishi Sinchayee Yojana
PMKSY-MI Pradhan Mantri Krishi Sinchayee Yojana - Micro Irrigation
PMO Prime Minister’s Office
List of Abbreviations Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xvii
PM-PRANAM
Programme for Restoration, Awareness Generation, Nourishment, and Amelioration
of Mother-Earth
R&D Research & Development
RBP Ration Balancing Programme
RKVY Rashtriya Krishi Vikas Yojana
SATAT Sustainable Alternative Towards Affordable Transportation
SDG 17 Sustainable Development Goal 17
SHC Soil Health Card
SHGs Self-Help Groups
SHM Soil Health Management
SI Subsurface Irrigation
SMAM Sub-Mission on Agricultural Mechanisation
SOC Soil Organic Carbon
SRC Sustainable Rice Cultivation
SRI System of Rice Intensification
SYI Sustainable Yield Intensification
UN-DESA United Nations Department of Economic and Social Affairs
List of Abbreviations Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xix
Executive Summary
Context and Purpose
Agriculture sits at the complex intersection of India’s Viksit Bharat aspirations and its Net Zero
ambition. As the anchor of India’s rural economy, the sector supports 46% of the workforce
and ensures national food security while contributing ~14% to Gross Value Added (GVA) (MoF,
2025). However, this foundational role characterised by the dominance of small and marginal
farmers, is increasingly threatened by climate change, soil degradation, and acute water stress.
The sector also faces a dual challenge: it must meet escalating demands for food, fiber, and bio-
energy while grappling with a heavy environmental and resource footprint. Agriculture currently
accounts for ~14% of national Greenhouse Gas (GHG) emissions, driven by methane from enteric
fermentation and rice cultivation and nitrous oxide from agricultural soils (MoEFCC, 2024).
Furthermore, the sector consumes ~18% of national electricity (275 TWh) (CEA 2024), primarily
to power groundwater irrigation and expanding mechanisation.
Given the structural constrains and socio-economic salience, the sector’s long-term planning
requires a differentiated approach that prioritizes adaptation interventions while actively
delivering mitigation co-benefits. Recognising this imperative, NITI Aayog has constituted a
multi-ministerial Working Group on the Agriculture Sector. This 42-member inter-disciplinary
group operates with the objective:
“To develop and analyse various options/pathways to achieve long-term resilience, farmers’
incomes, food and nutritional security that deliver mitigation co-benefits, considering the
impacts of technology, policy, investment, ecology-based farming systems, and others.”
The Exercise and Scenarios
The study adopts an “adaptation-first” approach, assessing how pathways aimed at improving
resilience, farmers income, productivity and resource efficiency can also deliver mitigation co-
benefits. This mirrors India’s agricultural policy landscape, where initiatives such as the National
Mission on Sustainable Agriculture (NMSA), Crop Diversification Programme (CDP), National
Livestock Mission (NLM) already demonstrate the inherent synergy between adaptation and
mitigation outcomes (MoEFCC 2024).
The study applies supply-side modelling to assess long-term mitigation and on-farm energy-
efficiency co-benefits of various pathways (Table E.1 & E.2). Using 2019 as the baseline,
agricultural production projections for major crops and milk are aligned with NITI Aayog’s
“Crop Husbandry, Agriculture Inputs, Demand and Supply” for 2019–2047 and extrapolated to
2070. Any pathway-induced changes in production are translated into corresponding mitigation Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xx
Executive Summary
co-benefits using IPCC Tier-2 methods and into achieving on-farm energy efficiency. These
outcomes are assessed under two stakeholder-driven scenarios: The Current Policy Scenario
and an accelerated Net Zero Scenario. The two scenarios capture both existing and accelerated
policy adoption through stakeholder-driven assumptions for 2047 and 2070. Tables E.1 and E.2
below summarises the long-term stakeholder-driven assumptions considered in the analysis.
Table E.1: Long-term (non-energy) pathways and assumptions for the agriculture sector
Sl.
No
ScenariosUnit2019
(Baseline)
2070
(Current
Policy
Scenario)
2070
(Net Zero
Scenario)
1Cropping intensity % (Gross Cropped
Area/Net Sown Area)
151 165 180
2Crop diversification
(away from rice, wheat,
sugarcane)
% area shifting from
rice, wheat, sugarcane
0.23 15 20
3Sustainable Yield
Intensification (SYI)
% reduction in yield
gap
66% yield
gap
20 70
4Natural and Chemical-free
farming
% Net Sown Area <5% 20 25
5Fertiliser Uptake Efficiency
(FUE)
% nutrient uptake per
kg fertiliser applied
33 40 50
6Sustainable Rice
Cultivation (SRC) practices
% of area under rice 0.25 20 25
7Enhanced in-milk bovine
productivity
kg/head/day5.27 12 15
8Share of in-milk population% of total bovine
population
30 45 55
9Reduced crop residue
burning
% reduction0 30 60
Table E.2: Long-term energy transition pathways and assumptions for the agriculture sector
Sl.
No
Levers20202070
(Current Policy
Scenario)
2070
(Net Zero
Scenario)
1Irrigated share of Gross Cropped Area 53%65%60%
2Groundwater/ Pumping share65%65%60%
3Water Productivity Improvement-10%25%
4Share of Solar Pumps2%40%60%
5Share of Electric Pumps70%60%40%
6Pump efficiency (Solar & Electric) 36%40%50%
7Pumping Head (metre)285035 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxi
Executive Summary
Sl.
No
Levers20202070
(Current Policy
Scenario)
2070
(Net Zero
Scenario)
8Mechanisation level47%100%100%
9Tractor:tiller split95:5 70:3050:50
10Energy intensity per ha (MJ/ha)
(% reduction in energy intensity)
Tractors:880
Tillers: 960
–20%–40%
11Fuel Consumption in Land Preparation 100% diesel 9% diesel, 8%
CNG, 83% electric
99% Electric,
1% CNG/
Compressed
Biogas (CBG)
Modelling Insights
Modelling for non-energy pathways and mitigation co-benefits
Strategic scaling of nine (9) pathways (Table E.1) could unlock up to ~26% of the sector’s
mitigation co-benefits in the Net Zero Scenario (NZS) against the Current Policy Scenario
(CPS).
Under the Current Policy Scenario (CPS), agricultural emissions (non-energy) are expected to
rise from ~506 MtCO₂e in 2019 to ~531 MtCO₂e in 2070 (Figure E.1). This is driven by a ~20%
increase in livestock sub-sector and a ~21% decline in crop sub-sector (Figure E.2 and E.3).
Contrarily, Net Zero Scenario (NZS) is expected to deliver total emissions of ~399 MtCO₂e in
2070, with ~44% of decline in crop sub-sector and ~8% from livestock sub-sector (Figure E.2
and E.3). As a result, Net Zero Scenario could deliver ~25% mitigation co-benefits relative to
the CPS (Figure E.1). Table E.3 highlights key drivers of such substantial mitigation co-benefits.
Current Policy Scenario Net Zero ScenarioBaseline
Overall non-energy emissions from Agriculture sector (MtCO
2
e) (2019-2070)
600
400
200
0
Emissions (in MtCO
2
e)
Year
201920502070
506
535531
402399
~25%
Figure E.1: Overall agriculture (non-energy) emissions in Current Policy Scenario and Net Zero
Scenario (2019-2070) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxii
Executive Summary
Emissions (in MtCO
2
e)
Current Policy Scenario Net Zero ScenarioBaseline
Livestock sub-sector emissions (MtCO
2
e) (2019-2070)
Year
400
300
200
100
0
201920502070
322
379
286
386
297
Figure E.2: Livestock sub-sector emissions in Current Policy Scenario and Net Zero Scenario
(2019-2070)
Current Policy Scenario Net Zero ScenarioBaseline
Overall emissions from Crop sub-sector (MtCO
2
e) (2019-2070)
Year
250
200
150
100
50
0
183
156
145
116
102
201920502070
Emissions (in MtCO
2
e)
Figure E.3: Crop sub-sector emissions in Current Policy Scenario and Net Zero Scenario (2019-2070) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxiii
Executive Summary
Table E.3: Key drivers for achieving 26% of mitigation co-benefits in 2070
RiceAgriculture soilsLivestock
Three-pronged approach to
counter resource-intensive rice
cropping systems:
1. Crop diversification in areas
away from rice, wheat, and
sugarcane towards horticulture,
pulses, nutri-cereals etc.
2. Sustainable Yield Intensification
through technological (for
example high yielding varieties
etc.) interventions.
3. Adoption of sustainable rice
cultivation practices that
enhance water-use efficiency.
For example: alternate wetting
and drying (AWD), system of
rice intensification (SRI), direct
seeded rice (DSR), etc.
Two-pronged approach for
soil health enhancement
amidst the rising cropping
intensity:
1. Improving Fertiliser Use
Efficiency (FUE) through
informed and optimised
fertiliser use through Soil
Health Cards (SHCs),
adoption of neem-coated
urea.
2. Adoption of Natural and
Chemical-free farming
via National Mission on
Natural Farming (NMNF),
Paramparagat Krishi Vikas
Yojana (PKVY) etc.
Two-pronged approach for
enhancing the overall efficiency
of the livestock sector:
1. Enhancement of the
productivity of in-milk
bovine animals through
animal nutrition interventions
through dedicated
programmes on fodder and
also breed improvements.
2. Improving the share of
in-milk bovines in the
total livestock population
through animal health-
related programmes under
the National Livestock
Mission (NLM) (For example:
Veterinary services).
Modelling Energy Transition Pathways
Scaling eleven (11) pathways (Table E.2) could deliver ~30% energy savings in Net Zero
Scenario against Current Policy Scenario
Land Preparation Pumping
60
50
40
30
20
10
0
Mtoe
2020202520502070
Current Policy
Scenario
Current Policy
Scenario
Net Zero
Scenario
Net Zero
Scenario
Energy Consumption in the Agriculture Sector (Mtoe) (2020-2070)
2343
2124
38
31
51
36
33
23
27
42
34
54
39
Figure E.4: Overall energy consumption (Mtoe) in Agriculture Sector (2020-2070) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxiv
Executive Summary
In 2020, India’s agriculture consumed ~23 Mtoe, dominated by irrigation pumping. By 2070,
under the Current Policy Scenario, total demand rises to ~56 Mtoe, driven by expanding
irrigation, high groundwater use, and mechanisation. Pumping dominates with ~52.5 Mtoe
(mostly grid electricity, diesel, and 40% solar) followed by land preparation at ~3.7 Mtoe.
Under Net Zero Scenario, energy stabilises at ~39 Mtoe, with pumping plateauing at ~36.8 Mtoe
(60% solar, 40% grid) and land preparation at ~2.7 Mtoe, powered by electric tractors (~2.23
Mtoe) and Compressed Biogas (CBG) (~0.29 Mtoe) (Figure E.4). Efficiency gains, drip/sprinkler
irrigation, aquifer recharge, and technology shifts decouple energy use from rising production,
while Compressed Biogas (CBG) supported by Sustainable Alternative Towards Affordable
Transportation (SATAT) scheme, reduces residue burning, and generates rural income.
Key Suggestions
1. Develop intervention specific, targeted roadmaps: To maximise mitigation and energy-
efficiency co-benefits, policymakers must adopt a risk-calibrated, evidence-based approach
that integrates both supply and demand-side levers. Supply-side, adaptation-centric
pathways alone deliver ~25% of total mitigation co-benefits by 2070 (Figures E.1 & E.4),
underscoring the necessity of complementary demand-side shifts. On the demand side,
this includes rationalising energy use in agriculture and enabling dietary transitions towards
less resource-intensive, nutritionally dense foods. For instance, shifting consumption from
water and energy intensive rice towards climate-resilient millets can reduce emissions
while strengthening resilience. This could be supported by behaviour-change initiatives
such as the Eat Right Movement and National Millet Mission (NMM). To ensure that such
transitions scale without compromising farmer incomes or food and nutritional security, the
government must deploy phased, spatially targeted, and socio-economically differentiated
roadmaps, particularly for scaling natural and chemical-free farming interventions.
2. Institutionalize an integrated “agri-food” systems framework: No single intervention can
independently deliver meaningful mitigation or energy-efficiency co-benefits. Achieving
these outcomes requires an integrated approach that coordinates production systems,
dietary patterns, value chains, and environmental objectives across land, energy, food,
health, biodiversity and water systems. The Pradhan Mantri Dhan-Dhaanya Krishi Yojana
(PMDDKY) exemplifies the potential of such integration by converging multiple objectives
and programmes, including crop diversification, rural livelihoods, and access to credit,
across 100 low-productivity districts. Scaling similar initiatives using a whole-of-government
approach, with alignment across the Ministries of Agriculture, Energy, Water, and Health,
can embed clean energy, healthy diets and other low-emissions interventions directly into
agricultural development strategies. Such coordination enables coherent policy design,
reducing trade-offs and preventing fragmented interventions that risk generating competing
or counterproductive outcomes.
3. Conduct Integrated Assessment Modelling (IAM) to guide ambition setting and long-term
planning: Forward looking planning to achieve mitigation co-benefits by 2070 requires
evidence generation to evaluate trade-offs and synergies across farmer livelihoods, food and
nutritional security, and long-term resilience. Integrated Assessment Models (IAMs) provide
a data-driven framework to systematically link socio-economic trajectories, climate risks,
and policy levers such as carbon pricing and subsidy reform. When deployed effectively,
integrated assessment frameworks can inform policy design and implementation across Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxv
Executive Summary
national, state, and local levels of government, enabling the evaluation of both direct
impacts and second-order outcomes across land, energy, food, water and other systems.
4. Implement an “Efficiency-first + clean energy solutions” strategy to achieve maximum
efficiency within the sector: The energy demand, dominated by irrigation, must be managed
through an adaptation-first, agriculture-led approach, with energy interventions sequenced
subsequently to avoid energy-intensive lock-ins. An efficiency-first strategy should prioritise
resource-efficient practices such as micro-irrigation, sustainable crop management, and
rationalised input subsidies to strengthen resilience and reduce input intensity. Building on
these adaptation gains, energy interventions, including renewable adoption, electrification,
and Compressed Biogas (CBG), can then be deployed to decouple productivity growth
from energy use. Leveraging Custom Hiring Centres (CHCs) to expand access to clean
mechanisation for smallholders ensures that productivity gains translate into mitigation and
energy efficiency co-benefits without embedding high energy requirements. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxvi
Background
As India advances towards its Viksit Bharat vision by 2047 (PMO, 2023) and Net Zero
emissions by 2070 (MoEFCC, 2022), agriculture occupies a critical position at the intersection
of economic transformation, food security, and climate change. The sector supports nearly
46% of the population, and is dominated by small and marginal landholders. Despite facing
multiple shocks, including the COVID-19 pandemic and global geopolitical disruptions, Indian
agriculture has demonstrated resilience. Between 2017–18 and 2024–25, the sector sustained an
average annual growth rate of 5.22%, reinforcing its importance as a stabilising force within the
broader economy (MoF, 2025). However, this performance masks deep structural challenges
that threaten long-term sustainability and climate resilience.
Indian agriculture operates under rising climate risks, with small and marginal holders bearing
a disproportionate share of the burden. These pressures jeopardise farm livelihoods, weaken
production systems, and push households into deeper vulnerability. The challenge is further
intensified by widespread resource degradation, notably declining soil health and escalating
water stress.
However, agriculture sector also have substantial environmental footprint. It contributes about
~14% of India’s total greenhouse gas (GHG) emissions (MoEFCC, 2024), primarily from non-CO₂
gases and remains energy-intensive, accounting for 18–20% of national electricity consumption
and ranking second in diesel use (CEA, 2024).
Looking ahead, the sector’s vulnerability is likely to intensify due to rising heat stress, increasing
rainfall variability, and growing pressure on land and water resources, compounded by structural
constraints such as small and fragmented landholdings, high dependence on climate-sensitive
livelihoods, and limited adaptive capacity among smallholders. For instance, groundwater-
dependent irrigation systems heighten exposure to droughts and energy price shocks.
The sector faces high climate vulnerability and deep structural constraints, given its role in
livelihoods and food security. By 2070, the sector must feed billions, respond to evolving dietary
preferences and meet rising bioeconomy demands for feed, fibre, and bioenergy.
Consequently, agriculture in India cannot be approached through a narrow mitigation-centric
lens. For India, the priority is safeguarding productivity, farmers’ income and food and nutritional
security. This shall require focus on measures to build resilience to climate change. A mitigation-
focused approach risks exacerbating rural distress and undermining development outcomes.
Therefore, this report has taken a “differentiated” approach than what is adopted in other
sectoral reports in this series. It focuses on adaptation-first pathways
1
that support livelihoods
and food and nutritional security, and assesses their corresponding abilities in generating
1 Find strategies with their adaptation and mitigation outcomes in Table 2.3 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture xxvii
Background
mitigation co-benefits. For instance, diversification away from water-intensive cereals towards
pulses, oilseeds, and millets strengthens drought resilience and income stability, while mitigation
benefits arise through lower input use, reduced energy demand, and improved soil carbon,
leading to lower emissions intensity.
India has already initiated such multi-benefit approaches through programmes including the
National Mission on Sustainable Agriculture (NMSA), Crop Diversification Programme (CDP),
National Mission on Natural Farming (NMNF), National Millet Mission (NMM) among others.
These initiatives demonstrate how resilience enhancement, and resource conservation can also
contribute to lower emission intensity (MoF, 2025;MoEFCC, 2024).
Recognising this imperative, NITI Aayog has constituted a multi-ministerial Working Group on
the Agriculture Sector. This 42-member inter-disciplinary group operates with the objective:
To develop and analyse various options/pathways to achieve long-term resilience, farmers’
incomes, and food and nutritional security that deliver mitigation co-benefits, considering the
impacts of technology, policy, investment, ecology-based farming systems, and others.
The Terms of Reference (ToR) of the Working Group are:
1. To provide a comprehensive understanding of future trends in agricultural production of
major food commodities, including milk, through 2050 and 2070
2. To project non-energy emissions and energy demand through 2070 in India’s current policy
framework
3. To identify and develop long-term pathways that ensure farmers’ income, ensure resilience
and food and nutritional security that could deliver mitigation co-benefits.
4. To estimate overall mitigation co-benefits associated with the proposed pathways and
evaluate their effectiveness in supporting India’s climate goals.
Box 1: Scope of the Working Group
The Agriculture, Forestry, and Land Use (AFOLU) sector in India has exhibited a
net-negative emissions trend since 2018, primarily due to land-use-related carbon
sequestration offsetting agricultural emissions (MoEFCC, 2024). However, the focus
of this study is on understanding gross emissions from the agriculture sector (not
accounting sequestration). The study aims to provide a detailed assessment of various
adaptation-centric interventions with mitigation co-benefits in the agriculture sector
from non-energy use. 1
INTRODUCTION Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 2
Introduction
1
1.1. HISTORICAL TRENDS IN AGRICULTURAL PRODUCTION AND
GROWTH
India’s agricultural growth trajectory over the past five decades has been shaped by sustained
gains in productivity. In the pursuit of food security, the country more than doubled its food
grain production between 1970 and 2010, rising from ~108 to ~244 million tonnes (Agriculture
Statistics, 2023). Over the same period, milk production increased nearly fivefold, from ~22 to
~122 million tonnes, positioning India as the world’s largest producer. These achievements were
driven by transformative interventions under the Green Revolution and the White Revolution,
which expanded access to improved seed varieties, irrigation, fertilisers, veterinary services and
institutional support (John and Babu, 2021).
The momentum in agricultural output has continued in the last decade, reflecting improvements
in agricultural productivity and policy support. Between 2011 and 2019, food grain production
increased to ~285 million tonnes and further to ~332 million tonnes in 2023-24 (PIB,2011; PIB,2019;
Agriculture Statistics, 2023), while milk production rose sharply to ~198 million tonnes (DAHD,
2023). Such production gains were largely achieved through productivity improvements over
area or herd size expansion.
For example, rice yields increased by ~14% between 2011 and 2019, from ~2.3 to ~2.7 tonnes
per hectare, while the area under rice cultivation remained broadly stable at around 44 million
hectares (Agriculture Statistics, 2023) (Figure 1.1 & 1.2). As a result, rice production increased
from ~105 in 2011 to ~119 million tonnes in 2019 (Figure 1.3). This reflects the widespread adoption
of high-yielding varieties supported by expanded irrigation coverage under the Pradhan Mantri
Krishi Sinchayee Yojana (PMKSY).
44 43 44 44 44 44 44 44 44
75
50
25
0
Area (million hectares)
Year
20112013201520172012201420162018 2019
Area under rice cultivation (million hectares) (2011-2019)
Figure 1.1: Historical trends in rice acreage (2011-2019) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 3
Introduction
2.42.42.4
2.6
2.52.5
2.4
2.6
2.7
4
3
2
1
0
Yields (tonnes/hectare)
Year
20112013201520172012201420162018 2019
Rice yields (tonnes/hectare) (2011-2019)
Figure 1.2: Historical trends in rice yields (2011-2019)
Year
20112013201520172012201420162018 2019
200
150
100
50
0
Production (million tonnes)
Rice production (million tonnes) (2011-2019)
107 105 104
110
113
116
119
105 105
Figure 1.3: Historical trends in rice production (2011-2019)
Similarly, the livestock sector witnessed strong productivity gains. Average milk yield per in-
milk bovine increased by ~28.5%, from 4.10 kg/day in 2011 to 5.27 kg/day in 2019 (DAHD 2023),
supported by policy initiatives such as the National Dairy Plan and the National Livestock
Mission (Figure 1.4). Structural changes in herd composition further reinforced these gains.
Between 2012 and 2019, the share of female bovines increased from 72% to 81% (DAHD 2019),
alongside a gradual shift from low-yielding to higher-yielding and crossbred animals (Figure
1.5). These trends enabled rapid growth in milk output while maintaining relative stability in
the overall bovine population. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 4
Introduction
Aggregate milk productivity of in-milk bovines (kg/day/head) (2011-2019)
8
6
4
2
0
Milk productivity (kg/day/head)
Year
20112013201520172012201420162018 2019
4.1
4.34.2
4.5
4.7 4.8 4.9
4.1
5.3
Figure 1.4: Historical trend of milk productivity (2011-2019) (DAHD, 2018, 2019)
100
75
50
25
0
% composition
2003201220072019
Year
Feminisation of bovine animals (2003-2019)
Females (%) Males (%)
3534
28
19
6566
72
81
Figure 1.5: Trends in share of female bovines in total herd composition
(2003 – 2019) (DAHD, 2019)
Taken together, these historical trends highlight a defining feature of Indian agriculture: output
growth driven predominantly by productivity improvements, supported by public investment,
technology adoption and institutional reforms. This foundation is critical for understanding how
the sector now intersects with emerging climate-related challenges.
1.2. CLIMATE CHANGE, AGRICULTURE VULNERABILITY AND
EMISSIONS PROFILE
Agriculture in India is acutely exposed to climate risks. Frequent dry spells (Chuphal et.al, 2024)
and extreme rainfall events (Prabhu and Chitale, 2024) have been disrupting yields. Rising
temperatures and shifting precipitation patterns are projected to reduce crop productivities by Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 5
Introduction
8–12% by 2099 (MoF, 2025). These climate impacts are compounded by resource degradation:
declining soil organic carbon, unsustainable fertiliser use, and water stress linked to input-
intensive cropping systems (Birthal et al, 2014; MoEFCC, 2022). Together, these pressures are
jeopardising farmer livelihoods and weakening resilience by elevating costs and risks.
At the same time, the agriculture and allied sectors currently contribute ~13.7% to India’s
Greenhouse Gas (GHG) emissions (MoEFCC, 2024), predominantly from non-CO₂ GHGs such
as methane (CH₄) and nitrous oxide (N₂O). These gases have global warming potentials (GWP)
of 28 and 265 times that of CO₂ over 100 years (IPCC, 2014). Currently, it is responsible for ~75%
of India’s CH₄ and ~73% of its N₂O emissions, driven by enteric fermentation from livestock, rice
cultivation, and synthetic fertiliser use (Table 1.1) (Patange et al, 2024; MoEFCC, 2021).
In 2019, livestock emissions dominated agricultural emissions at ~60%, through enteric fermentation
(~53%) and manure management (~7%). This is followed by emissions from agricultural soils
(~21%) and methane from rice cultivation (~17%). Historical data indicates that agricultural non-
energy emissions increased marginally by ~3% from ~409 MtCO₂e in 2011 to ~421 MtCO₂e in
2019 (Figure 1.6) (MoEFCC, 2021). This is despite a ~19% growth in food grain production and
a ~55% growth in milk production, over the same period (Agriculture Statistics, 2023; DAHD
2023). This stabilisation of emissions in the last decade against significant production gains is
primarily due to:
a. Rice yield improvements by ~14% from 2.39 to 2.72 tonnes per hectare on a relatively
constant rice acreage of 44 million hectare (Agriculture Statistics, 2023).
b. Relatively stable livestock population as a result of 22% rise in productivity, due to the
following factors of herd restructuring:
i. Transition from low-yielding to high-yielding animals (NITI Aayog, 2024);
ii. Replacement of male bovines with female bovines, increasing the share of female
animals in the overall population
Agricultural
Waste Burning
Agricultural Soils
Rice Cultivation
Manure Management
Enteric Fermentation.
Total emissions
500
400
300
200
100
0
Emissions (MtCO
2
e)
Year
2011 2013 2015 20172012 2014 2016 2018 2019
Historical Agricultural Emissions (MtCO
2
e) (2011-2019)
219 222 224 227 222 223 223 223 223
28
73
88
421
28
74
84
417
28
74
81
411
27
71
78
408
27
72
80
410
28
73
81
417
28
73
80
414
27
71
80
408
27
73
82
409
Figure 1.6: India’s historical trends of agriculture non-energy emissions (AR2) (2011-2019)
(MoEFCC, 2021) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 6
Introduction
In addition, the sector is a major energy consumer, accounting for ~18% of national electricity
consumption and ranking second in diesel use (CEA, 2025). The emissions from diesel and
other fossil-fuel consumption in land-preparation and pumping are accounted as agriculture
energy emissions. In this study, the emissions from the electricity use in the agriculture sector
are accounted for in power sector emissions. Table 1.1 summarises the detailed description of
agriculture sector’s energy and non-energy emission sources.
As shown in Figure 1.6, in 2019, livestock emissions dominated agricultural emissions at ~60%,
through enteric fermentation (~53%) and manure management (~7%). This is followed by
emissions from agricultural soils (~21%) and methane from rice cultivation (~17%) (MoEFCC
2021).
Understanding the major drivers of agricultural emissions is critical for interpreting historical
trends, projecting future emission trajectories, and evaluating the effectiveness of policy
interventions. The following section examines historical drivers in detail.
Table 1.1: Description of agricultural emissions categories and their sources
SourceDescription of emission sources
Rice cultivation
Methane (CH₄) is produced in flooded rice fields through anaerobic
decomposition of organic matter.
Agricultural soils
Nitrous Oxide (N
2
O) is emitted from soils due to nitrogen inputs such as
fertilisers and manure, through microbial processes including nitrification and
denitrification.
Agricultural waste
burning
Both CH
4
and N
2
O are released during burning of crop residues, primarily
due to incomplete combustion of biomass and nitrogen-containing plant
material.
Enteric fermentation
CH
4
is generated in the digestive system of ruminant livestock as microbes
break down feed, and is mostly expelled via belching.
Manure management
CH4 and N
2
O are emitted during storage and treatment of manure, where
anaerobic conditions produce methane, and microbial processes release
nitrous oxide from nitrogen compounds.
Land preparation
and Pumping
Emissions (CO
2
e) due to fossil fuel consumption for land preparation and
pumping.
1.3. HISTORICAL TRENDS IN NON-ENERGY EMISSIONS FROM
AGRICULTURE SECTOR
Methane Emissions from Rice Cultivation
Methane (CH₄) emissions from rice cultivation is due to methanogenesis, driven by anaerobic
soil conditions and flooded water regimes. As a result, overall rice emissions in India are driven
by two factors: the spatial extent (acreage) of rice cultivation and the rice water-management
regimes (MoEFCC, 2022). While rice production increased between 2011 and 2019, emissions Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 7
Introduction
from rice cultivation remained broadly stable (Figure 1.7). This stabilisation reflects consistent
water management practices with potential shifts in space. While conventional flooded systems
persist in states such as Punjab, Haryana, West Bengal and Rajasthan, water-scarce states such
as Tamil Nadu and Karnataka have increasingly adopted Alternate Wetting and Drying (AWD)
and aerobic rice systems. These sustainable rice cultivation practices reduce methane emissions
by ~48% (Annexure III) per hectare (emission intensity) offsetting emission pressures from
productivity-led intensification.
Emissions (MtCO
2
e)
Historical rice emissions (MtCO
2
e) (2011-2019)
150
100
50
0
Year
20112013201520172012201420162018 2019
7373 73 72 71 74 74 7371
Figure 1.7: Historical trends of emissions from rice cultivation (AR2) (2011-2019) (MoEFCC, 2022)
Nitrous Oxide (N2O) Emission from Agricultural Soils
N
2
O emissions from agricultural soils in India are primarily driven by two factors: nitrogen
application rates
2
per cropping cycle (kg/ha) – including both synthetic fertilisers and organic
inputs – and cropping intensity (number of cropping cycles per year – GCA/NSA), which
determines how frequently nitrogen is applied per hectare in a year (IPCC, 2014).
1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.5
1.5
3.0
2.0
1.0
0.0
Cropping intensity (GCA/NSA)
Year
Cropping intensity (GCA/NSA) (2011-2019)
2011 2012 2013 2014 2015 2016 2017 2018 2019
Figure 1.8: Trends of cropping intensity (2011-2019)
2 Rate of application of nitrogen refers to the amount of nitrogen inputs applied per ha (kg/ha). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 8
Introduction
25
20
15
10
5
0
Nitrogen consumption
(in million tonnes)
Nitrogen fertiliser consumption (million tonnes) (2011-2019)
17.3
16.8 16.8 16.9
17.4
16.7 17.0
17.6
19.1
Year
20112013201520172012201420162018 2019
Figure 1.9: Total nitrogen fertiliser consumption (2011-2019)
Emissions from agricultural soils (MtCO
2
e) (2011-2019)
200
150
100
50
0
20112013201520172012201420162018 2019
Emissions (MtCO
2
e)
Year
82
80 80 81 80 78
81 84
88
Figure 1.10: Emissions from agricultural soils (AR2) (2011-2019)
India is one of the world’s largest consumers of synthetic fertilisers with an average application
rate of ~140 kg of total nutrients (N + P
2
O
5
+ K
2
O) per hectare per cropping cycle (FAI, 2024).
However, nutrient application is heavily skewed toward nitrogen, with an N:P:K ratio of 10.9:4.4:1
indicating significant overuse of nitrogen relative to others (FAI, 2024). As a result, agricultural
soils emissions in India rose by ~7% from 82 to 88 MtCO
2
e between 2011 and 2019 (Figure 1.10).
This was in parallel to a 10.4% increase in overall fertiliser consumption from ~17 to 19 million
tonnes (FAI, 2024) (Figure 1.9). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 9
Introduction
The rise in fertiliser consumption can be attributed to two main factors. First, cropping intensity
increased from ~139% to ~151% between 2011 and 2019 Figure 1.8), driven by expanded irrigation
under Pradhan Mantri Krishi Sinchai Yojna (PMKSY). Second, declining Nitrogen Use Efficiency
(NUE) (Singh, 2023) led to higher per-hectare nitrogen application, which rose from ~88.5
to ~90.4 kg/ha over the same period (FAI, 2024). Nitrogen use from organic sources also
grew by ~1.44%, further increasing soil emissions. While programs like the Paramparagat Krishi
Vikas Yojana (PKVY) and the National Mission on Natural Farming (NMNF) promote organic
alternatives that reduce emissions, their adoption remains limited (<3% of cropland) (NITI
Aayog, 2024), suggesting that these emission trends may persist.
Livestock Emissions: Enteric fermentation (CH₄) and Manure Management (N
2
O + CH₄)
The emissions in the livestock sector are driven by methane from enteric fermentation and by
methane and nitrous oxide from manure management. Bovine animals, cattle and buffaloes,
are the dominant source of livestock emissions, accounting for ~82%
3
of livestock emissions in
2019. Given this dominance of bovine animal emissions in the livestock sub-sector, this analysis
focuses specifically on bovine-related emissions.
Milk production rose by ~55% between 2011 and 2019, growing from ~128 million tonnes to ~198
million tonnes (Figure 1.11). However, emissions from the livestock sector showed a moderate
growth of only 2.23%, from ~246 MtCO
2
e to ~251 MtCO
2
e (Figure 1.12).
200
150
100
50
0
Historical milk production (million tonnes) (2011-2019)
Year
20112013201520172012201420162018 2019
Total Milk (million tonnes)
128
132
138
146
155
165
176
188
198
Figure 1.11: Historical milk production (DAHD, 2018, 2019, 2023)
3 (Authors’ analysis based on MoEFCC 2021) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 10
Introduction
Historical emissions from livestock sub-sector (MtCO
2
e) (2011-2019)
Year
20112013201520172012201420162018 2019
Livestock emissions (MtCO
2
e)
300
200
100
0
246 249
252 255
250 250 250 251 251
Figure 1.12: Historical livestock emissions (AR2) (2011-2019) (MoEFCC, 2021)
Such stabilisation trends in livestock emissions are primarily driven by (i) an increase in bovine
productivity (Figure 1.4) and (ii) the displacement of male animals by and with the increasing
female population, keeping the total bovine population stable so far (Figure 1.5). 2
METHODOLOGY Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 12
2
Methodology
aa
2.1 APPROACH TO ESTIMATING MITIGATION CO-BENEFITS OF
NON-ENERGY AGRICULTURAL PATHWAYS
As mentioned in the Background, this report has taken a “differentiated” approach than what
is adopted in other sectoral reports in this series. It focuses on adaptation-first pathways that
support livelihoods and food and nutritional security, and assesses their corresponding abilities
in generating mitigation co-benefits. However, this requires integrated frameworks that address
synergies and trade-offs across different time scales (IPCC 2019). This analysis is limited to
supply-side, production-oriented, scenario-based modelling of agricultural emissions.
This section details the report’s approach followed to:
1. Production projections: Compile historical and baseline (2019) production data for
crops and livestock, and project production trajectories for eight major crops and milk
through 2070.
2. Emissions assessment: Estimate sectoral greenhouse gas emissions from crops and
livestock through 2070, based on projected production pathways.
3. Policy pathway analysis: Develop two long-term policy pathways—the Current Policy
Scenario and the Net Zero Scenario—aligned with resilience, farmer incomes, and food
and nutritional security, and assess and quantify associated mitigation co-benefits
Figure 2.1 shows the methodology for estimating future emissions from non-energy use. It
uses 2019 as the baseline year and employs an annual time-step model
4
to project emissions
trajectories from 2020 to 2070, with intermediary milestones of 2047
5
.
Figure 2.1: Agriculture emission modelling methodology
4 An annual time-step model projects year-by-year changes by updating key variables and recalculating emissions each year.
5 India’s timeline to become a developed nation,Viksit Bharat, on the occasion of centenary year of Independence
Step 1Step 2Step 3
Production
projections
Emission
estimations
Development of Current policy
scenarios and Alternative pathways
Crop Husbandry,
Agriculture Inputs,
Demand and Supply
2047 report,
2019-2047
Projections
extended from
2047-2070
Country specilic
emission factors from
IRCC tier 1 and tier 2
methodologies
Policy
identification
Policy typology
development
Scenario
identification
Participatory
scenario
development Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 13
Methodology
Step 1: Compiling historical and baseline (2019) production data for crops and
livestock and projecting future production for 8 major crops and milk.
Consistent with the supply-side scope of this analysis, agricultural emissions are modelled using
production projections of nine key food commodities - for 8 major crops
6
and milk.
a. For the period 2021–2047, production projections are directly adopted from NITI
Aayog’s “Crop Husbandry, Agriculture Inputs, Demand and Supply” (2024), which
applies a time-series methodology grounded in historical area, production and yield
trajectories (see Box 2).
b. For the period 2048–2070, production projections are extended from the 2047
endpoints using the methodology adopted in the NITI Aayog (2024) report, ensuring
continuity and methodological consistency through 2070.
Box 2: Methodology followed for Forecasting the Production
of Food Commodities
The Working Group Report on Crop Husbandry, Agriculture Inputs, Demand and Supply,
Report of 2024 of NITI Aayog assess trends in demand and supply of food commodities,
inputs, and feasible levels of exports through 2047. The report uses four forecasting
methods for projecting supply/production based on historical trends of change. They
are: a) Autoregressive Integrated Moving Average (ARIMA), b) Artificial Neural Network
(ANN), c) Holt’s smoothing, and d) the exponential growth rate model (based on the
past 10 years).
Step 2: Emission estimations through 2070
Emissions are estimated using the IPCC Tier 1
7
and Tier 2
8
methodologies (Table 2.1). These
estimates incorporate country-specific emission factors across five emission categories within
the agricultural sector (Table 2.2). Methane (CH₄) and nitrous oxide (N₂O) are the dominant
greenhouse gases in this sector; their emissions are therefore expressed in carbon dioxide
equivalents (CO₂e) using 100-year Global Warming Potential (GWP) values of 28 for CH₄ and
265 for N₂O, as reported in the IPCC’s Fifth Assessment Report (AR5). The baseline year for
emissions projections is 2019, consistent with emissions reported in India’s Third National
Communication. To ensure methodological consistency across the analysis, historical 2019
emissions were converted from AR2 to AR5 GWP values.
6 Major eight crops are considered as they contribute directly to GHG emissions from the sector. These are: Rice,
Wheat, Cotton, Jute, Rapeseed and Mustard, Maize, Sugarcane and Nutri-cereals
7 Tier 1 methodology uses IPCC default emission factors and general activity data; suitable for countries with limited
data
8 Tier 2 methodology uses country-specific emission factors and detailed activity data. It requires better-quality
national information and captures local conditions more effectively (India mostly uses Tier 2) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 14
Methodology
Table 2.1: Emission estimation methodology for various categories considered for the
agriculture sector (MoEFCC, 2021)
Sector/CategoryGas Method Used Emission Factor
Enteric FermentationCH
4
T1, T2D, CS
Manure Management
CH
4
T1D
N
2
OT1D
Rice CultivationCH
4
T2CS
Agricultural SoilsN
2
OT2CS
Field Burning of Agricultural Residues
CH
4
T1D
N
2
OT1D
Notation/Legend: T1: Tier 1; T2–Tier 2; CS–Country specific emission factors; D–IPCC Default emission factors
Table 2.2: Emission estimation methodology for various categories considered for the
agriculture sector
Emission
Category
GHG Emission
Type
Emission Estimation Methodology
Livestock
emissions
Enteric
fermentation
(CH
4
)
To estimate livestock emissions from 2020 to 2070, bovine
populations were projected (82% of total livestock emissions in
2019) using milk production projections. In-milk and non-in-
milk animal numbers were derived from productivity trends and
historical trends of herd composition. Emissions were computed
by applying country-specific emission factors to these population
categories (species type and dairy and non-dairy cattle based
on their ages) as indicated in Annexure I. Given the limited
contributions of the non-bovine animals, these emissions are
assumed to remain constant at 2019 levels through 2070.
Manure
Management
(N
2
O, CH
4
)
Rice
emissions
Methane
emissions (CH
4
)
Between 2011 and 2019, rice cultivation in India maintained a stable
emission intensity of 2.11 MtCO
2
e/ha over 44 million hectares,
reflecting consistent aggregate water management practices
(Annexure I). Future emissions are projected by applying this
emissions intensity to anticipated rice cultivation areas, assuming
aggregate water regimes remain unchanged unless specified.
Agricultural
soil
emissions
Nitrous oxide
emission (N
2
O)
based on soil
activity
Agricultural soil (N
2
O) emissions, categorised as direct and indirect,
are estimated based on projections of total nitrogen consumption
from both synthetic and organic fertilisers. Appropriate emission
factors are applied to estimate emissions from agriculture soils are
estimated by summing direct and indirect emissions (Annexure I)
Agricultural
Waste
Biomass
(AWB)
Emissions from
crop residue
burning (N
2
O,
CH
4
)
Crop residue burning represents a source of CH₄ and N
2
O
emissions and which is estimated based on the amount of crop
residue burnt. Crop residue burnt is estimated using residue crop
ratios, dry matter content, and combustion efficiency
9
for each of
the eight major crops. CH₄ and N
2
O emission factors were applied
to the estimated biomass burnt to compute agricultural waste
burning (AWB) emissions from 2020 to 2070 (Annexure I).
Note: The Annexure I provides detailed country-specific emission factors used across the five categories of emissions.
9 Median state-level combustion efficiency was used for rice, while national average values were applied for other crops Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 15
Methodology
Step 3: Development of Current Policy Scenario (CPS) and Net Zero Scenario (NZS)
Two policy pathways: the Current Policy Scenario and the Net Zero Scenario—were developed
to generate long-term emissions projections for India’s agriculture and allied sectors. These
pathways are structured around four food system based policy typologies and nine key
interventions as in Table 2.3 & 2.4 and Annexure II.
Current Policy Scenario: This scenario considers the effective implementation of
prevailing/current agricultural policies in India. It assumes policy implementation rates
across various interventions that help to achieve the intended ambitions of existing
government policies.
Net Zero Scenario: This scenario envisions a transformative outcomes characterized by
accelerated adoption of existing and new agricultural policies beyond the Current Policy
Scenario. Consequently, the pathway is framed around to identify those interventions
which will improve farmers’ income, farm productivity and strengthen climate change
resilience with potential mitigation co-benefits.
The list of various such possible interventions and their corresponding mitigation co-benefits
is provided in Table 2.3. Assumptions underpinning both scenarios (Table 2.4), were developed
through an iterative, multi-stakeholder consultation process involving over 30 experts. These
assumptions reflect historical rates of policy penetration, the ambition embedded within the
current policy framework, and desirable future pathways. Any pathway-induced changes in
production are translated into corresponding mitigation co-benefits.
The list of various such possible interventions is provided in Table 2.3.
Table 2.3: Policy typologies mapped against their potential mitigation co-benefits
Sl.
No
Implementation
pathway
Relevant schemes Parameter of
change
Primary outcomes
achieved
Potential
impacts
on GHG
emissions
Sustainable agricultural production
1Sustainable
yield
intensification
Pradhan Mantri
Krishi Sinchai
Yojna (PMKSY);
Micro Irrigation
Fund; Sub-mission
On Agriculture
Mechanisation
(SMAM); Rainfed
Area Development
Enhance output per
ha (kg/ha)
1. Farmer livelihood
through
enhanced farm
incomes
2. Enhance food
security
3. Building adaptive
capacity of
farmers against
the impacts of
climate shocks
Reduced
emission
intensity per
ha (CO
2
e/ha)
2Crop
diversification
Crop Diversification
Programme
(CDP)
10
;
Horticulture
Mission; Mission on
Edible oils, Pulses
and Nutri-cereals
(millets)
1. Input efficiency
(kg/ha or lt/ha)
2. Soil health
enhancement
3. Climate resilience
4. Diversified
plate (kcal
restructuring)
1. Farm resilience
against climate
and market
shocks
2. Farm profitability
3. Food and
Nutritional
Security of India
Reduced
emission
intensity per
ha (CO
2
e/ha)
10 Rashtriya Krishi Vikas Yojna (RKVY) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 16
Methodology
Sl.
No
Implementation
pathway
Relevant schemes Parameter of
change
Primary outcomes
achieved
Potential
impacts
on GHG
emissions
3Cropping
intensity
Pradhan Mantri
Krishi Sinchayee
Yojna (PMKSY-
MI); Accelerated
Irrigation Benefits
Programme (AIBP)
Enhanced output
(kg/ha/year)
1. Farmer livelihood
through
enhanced due
unlocking more
cropping cycles
2. Food security
3. No net increase
in Net sown area
Reduced
emissions per
output (CO
2
e/
kg)
Sustainable Livestock Production
4Sustainable
Yield
Intensification
(SYI)
National Livestock
Mission (NLM);
Ration Balancing
Programme (RBP)
Enhanced milk
output per animal
per day (lt/day/
animal)
Feed efficiency
improvement
(kgfeed/lt)
1. Enhanced
income
2. Food and
nutritional
security
3. Adaptive
capacity of
farmers against
shocks
4. Reduced
overall animal
population
(millions)
Reduced
emission
intensity
(CO
2
e/ animal/
day)
5Livestock health
management
National Livestock
Mission (NLM);
Rashtriya Gokul
Mission (RGM)
1. Enhanced
reproductive
health of
livestock
2. Climate resilience
(Singh et al,
2017)
1. Reduced costs
of livestock
maintenance at
the farmer level,
enhancing the
profitability per
herd
Reduced
overall
emissions
from livestock
Sustainable Agricultural Practices
6Natural and
Chemical-free
farming
National Mission
on Natural
Farming (NMNF);
Paramparagat
Krishi Vikas Yojna
(PKVY); Soil health
card scheme; PM–
PRANAM; Green
credits; Neem-
coated urea
1. Input efficiency
(kg/ha of L/ha)
2. Soil health (SOC)
3. Climate resilience
4. Agro-biodiversity
1. Long-term yield
sustainability
2. Long-term
livelihood
security
4. Farm resilience
5. Nutritional
security
Reduced
nitrous oxide
emissions from
the reduction
in application
of chemical
fertilisers
7Enhance Fertiliser
uptake/use
efficiency (FUE)
Neam-coated urea;
Integrated Nutrient
Management (INM)
1. Input efficiency
(kg input/ kg
output)
2. Soil health
protection
3. Overall reduction
in the use of
fertiliser
1. Long-term yield
sustainability
2. Food security
Reduced
nitrous oxide
emissions per
kg output,
improving
the emission
intensity of
production Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 17
Methodology
Sl.
No
Implementation
pathway
Relevant schemes Parameter of
change
Primary outcomes
achieved
Potential
impacts
on GHG
emissions
8Sustainable Rice
Cultivation (SRC)
practices
Bringing Green
Revolution to
Eastern India
(BGREI)
1. Water use
efficiency (lt/ha)
2. Water stress
management
3. Climate resilience
1. Farm income
stability
2. Climate resilience
Up to 59%
reduction
in methane
emissions from
rice fields
(Annexure III)
Circular Bioeconomy
9Agriculture Waste
Burning
Crop residue
management
under RKVY
9
;
BioE3 Policy
1. Diversified farm
incomes
2. Climate action
3. Soil health
management
4. Enhanced
bioeconomy
1. Farmer
livelihoods
2. Reduced air
pollution
Reduced
methane and
nitrous oxide
emissions from
the burning of
biomass
Table 2.4: Key assumptions for 2047 and 2070
Policy
typology
Scenarios
Number
Interventions Unit Current
status
for the
baseline of
2019
Current
Policy
Scenario
Net Zero
Scenario
2047207020472070
1. Sustainable
agriculture
production
1.1
Cropping
intensity
% GCA
(ha)/ NSA
(ha)
151 160 165170180
1.2
Crop
diversification
away from rice,
wheat and
sugarcane
% area
shifting
from rice,
wheat and
sugarcane
0.23
(2019)
10 15 15 20
1.3
Sustainable
Yield
Intensification
(SYI)
% reduction
in yield
gap
11
0 (66%
yield gap)
15 20 40 70
2. Sustainable
agriculture
practices
2.1
Natural and
Chemical-free
farming
% net sown
area6 15 20 20 25
2.2
Fertiliser uptake
efficiency (FUE)
% of kg of
nutrient
uptake /kg
of fertiliser
applied
33 38 40 45 50
2.3
Sustainable
Rice Cultivation
(SRC) practices
% of area
under rice 0.25 10 20 18 25
11 Yield gap for crops is defined as the difference between the current attainable yield and the average yield achieved
in India. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 18
Methodology
Policy
typology
Scenarios
Number
Interventions Unit Current
status
for the
baseline of
2019
Current
Policy
Scenario
Net Zero
Scenario
2047207020472070
3. Sustainable
livestock
production
3.1
Enhanced in-
milk bovine
productivity
kg/head/
day5.27 8 12 12 15
3.2
Share of the In-
milk population
% in-milk in
total bovine
population
30 40 45 45 55
4. Circular
bio-
economy
4.1
Reduced
burning of crop
residue
% reduction
in crop
residue
burnt
0 20 30 40 60
Note: Annexure II contains a detailed policy mapping and assumptions behind the Scenarios presented
in the above table.
Each parameter shown in the table is described subsequently.
Scenario 1.1: Cropping Intensity
Cropping intensity refers to the number of crops grown on the same field during one
agricultural year. Recent data shows that the national average cropping intensity in India is
~155% (Agriculture Statistics, 2023), meaning cropland is cultivated approximately 1.55 times
annually. This represents a gradual increase from ~140% in the early 2010s (Sharma, 2023) due
to the implementation of Pradhan Mantri Krishi Sinchayee Yojana (PMKSY) and Rashtriya Krishi
Vikas Yojana (RKVY) since 2015.
Increasing cropping intensity boosts food production per unit area, increases farm incomes,
and potentially reduces agriculture land expansion. Concurrent scaling of agroecology and soil
management practices through National Mission on Natural Farming (NMNF), Soil Health Cards
(SHC), and Pradhan Mantri Krishi Vikas Yojna (PKVY) is crucial to prevent risks of unsustainable
intensification, notably soil degradation through over-fertilisation and water table depletion
from over-extraction. Increasing cropping intensity is expected to lead to higher GHG emissions
per hectare, but lower GHG emissions per output.
In the Current Policy Scenario, cropping intensity is projected to increase to 160% in 2047 and
165% in 2070. In Net Zero Scenario, it is projected to increase to 170% in 2047 and 180% in
2070 (Table 2.4a).
Table 2.4a: Assumptions of cropping intensity in Current Policy Scenario and Net Zero
Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Cropping intensity % GCA / NSA
(in ha)
151 160 165 170 180 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 19
Methodology
Scenario 1.2: Crop diversification
Mitigation “co-benefits” from the GoI’s Crop Diversification Programme (CDP) under Rashtriya
Krishi Vikas Yojana (RKVY), which has led to diversification of 1.02 lakh ha (0.102 Mha) away
from water-intensive crops (rice and tobacco), stood at 0.214 MtCO2e between 2019-24
(MoEFCC, 2024).
Crop diversification is a strategy in which farmers shift away from rice, wheat, or sugarcane-
dominated monoculture systems toward high-value crops (horticulture, oilseeds etc) or nutri-
cereals crops as a climate adaptation strategy. This transition can enhance farm incomes by
reducing risk and increasing value per hectare and enhance nutritional security (Barman et
al, 2022). This transition also yields relative mitigation co-benefits, as Greenhouse Gas (GHG)
emissions per hectare decline when farmers shift from input-intensive monoculture systems to
more diversified cropping systems.
Crop diversification pathways must consider implications for food security and farm incomes,
in both the short and long term. The analytical snapshot, given in Annexure VI, evaluates the
feasibility of diversifying away from rice to nutri-cereals as an example, identifies potential
leading states and outlines a short-term roadmap to facilitate this transition.
In the Current Policy Scenario, ~10% of the cropped area is assumed to be diverted from rice,
wheat and sugarcane by 2047 and ~15% by 2070%. In Net Zero Scenario, the corresponding
numbers are ~15% by 2047 and ~20% by 2070 (Table 2.4b).
Table 2.4b: Assumptions of area-based crop diversification in Current Policy Scenario and
Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero Scenario
2047 2070 2047 2070
Area-based crop
diversification away
from rice, wheat and
sugarcane
% area shifting
from rice, wheat
and sugarcane
0.23
(2019)
10 15 15 20
Scenario 1.3: Sustainable Yield Intensification
Sustainable Yield Intensification (SYI) refers to enhancing crop productivity per unit of arable land
through agronomic, ecological, and technological interventions without degrading environmental
quality or depleting natural resources. In this report, Sustainable Yield Intensification (SYI) focuses
on narrowing yield gaps relative to current realisable yields through technological upgrades and
resource-efficient practices, including site-specific nutrient management and climate and stress-
tolerant, high-yielding crop varieties promoted and developed under the National Innovations
in Climate Resilient Agriculture (NICRA), among others. Given that yield gaps for major crops
such as rice, wheat, maize, and sugarcane range between 66% and 75%, narrowing these gaps
is critical to meeting rising food and biomass demands while addressing the “land squeeze”
from competing uses such as bioenergy and fiber production. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 20
Methodology
In the Current Policy Scenario, ~20% yield gap will be bridged by 2070. In Net Zero Scenario,
the corresponding scenarios are 70% by 2070 (Table 2.4c).
Table 2.4c: Assumptions of sustainable yield intensification in Current Policy Scenario and
Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Sustainable yield
intensification (SYI)
% reduction in
yield gap
12
0 (66%
yield gap)
15 20 40 70
Scenario 2.1: Natural and Chemical-free farming
Natural and Chemical-free farming encompasses agroecological practices that eliminate or
replace synthetic chemical inputs with bio-based alternatives, relying on ecological processes
to maintain soil fertility, manage pests, and sustain crop productivity. This report explores
long- term scenarios for scaling the adoption of natural and chemical-free farming, focusing
on natural
13
and organic farming systems
14
, which currently cover 6% of India’s Net Sown Area
(NSA)
15
. The analysis is situated within key policy initiatives, including the Paramparagat Krishi
Vikas Yojana (PMKY) and the National Mission on Sustainable Agriculture (NMSA). In light of
recent policy momentum with the announcement of the National Mission on Natural Farming
(NMNF), which aims to scale natural farming to ~7.5 lakh hectares of net sown area, Annexure
VI (Part 2) presents a framework for scaling chemical-free practices. While large-scale adoption
of natural farming and agroecological practices offers significant long-term environmental and
cost benefits, perceived short-term yield risks under certain conditions may constrain adoption
and must be carefully managed to safeguard food security (Kumar et al, 2020). As a result,
under the Current Policy Scenario, natural and chemical-free farming, currently covering less
than 5% of the net sown area, is assumed to expand to 20% by 2070, increasing further to 25%
under the Net Zero Scenario by 2070) (Table 2.4d).
12 Yield gap for crops is defined as the difference between the current attainable yield and the average yield achieved
in India.
13 Natural Farming is a system rooted in agroecological principles that integrates crops, trees and livestock with
functional biodiversity. It is largely based on on-farm biomass recycling with major stress on biomass mulching, use
of on-farm cow dung-urine formulations; maintaining soil aeration and exclusion of all synthetic chemical inputs.
Natural farming is expected to reduce dependency on purchased inputs. It is considered as a cost- effective farming
practice with scope for increasing employment and rural development.
14 Organic farming systems’ focus is on using naturally available resources as inputs, such as organic wastes (crop,
animal and farm wastes, aquatic wastes) and other biological materials along with beneficial microbes (biofertilisers/
bio control agents) to release nutrients to crops and protect them from insect pest and diseases for increased
agricultural production.
15 Stakeholder consultations Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 21
Methodology
Table 2.4d: Assumptions of chemical-free farming in Current Policy Scenario and Net Zero
Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Natural and Chemical-
free farming
% net sown area 6 15 20 20 25
Scenario 2.2: Fertiliser Uptake Efficiency
Mitigation “co-benefits” achieved through adoption of 134.05Mt neem-coated urea as a
measure to improve FUE stood at 26.81 MtCO2e between 2019-24 (MoEFCC, 2024).
Fertiliser Uptake Efficiency (FUE) measures how effectively crops utilise applied fertilisers, and
is calculated as the ratio of crop output to fertiliser used. In India, FUE has declined, with
Nitrogen Use Efficiency (NUE) having dropped from 48% in the 1960s to 35% in 2018 (Singh,
2023) due to increased reliance on synthetic fertilisers. This report explores long-term scenarios
for the likely effects of initiatives like Soil Health Management (SHM) and the mandate for 100%
neem-coated urea to improve FUE. As a result, Fertiliser use efficiency is assumed to increase
to 40% by 2070 in Current Policy Scenario and 50% by 2070 in Net Zero Scenario (Table 2.4e).
Table 2.4e: Assumptions of fertiliser uptake in Current Policy Scenario and Net Zero
Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Fertiliser uptake % of kg of nutrient
uptake/kg of
fertiliser applied
33 38 40 45 50
Scenario 2.3: Sustainable Rice Cultivation Practices
Mitigation “co-benefits” of the adoption of System of Rice Intensification (SRI) and Direct
Seeded Rice (DSR) rice cultivation practices across 1.11 lakh ha (0.11 Mha) stood at 0.19
MtCO2e between 2019-24 (MoEFCC, 2024).
Sustainable Rice Cultivation (SRC) refers to agronomic practices that can enhance water
efficiency and reduce input costs in paddy cultivation, which accounts for 40% of India’s
irrigation water use. Key techniques like Alternate Wetting and Drying (AWD), System of
Rice Intensification (SRI), Subsurface Irrigation (SI), and Drip Irrigation (DI) can reduce water
use by 30–40% while maintaining or improving yields. These practices also promote aerobic
conditions in the paddy fields, reducing the methane emissions. This report models long-term
scenarios for scaling Sustainable Rice Cultivation (SRC) given its strong water-saving potential
and climate mitigation co- benefits. Annexure III contains the mitigation potentials of various
SRCs in different states of India. Under the Current Policy Scenario, sustainable rice cultivation
practices is assumed to increase to 20% of rice area by 2070 and under the Net Zero scenario
the same will increase to 25% of rice area by 2070 (Table 2.4f). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 22
Methodology
Table 2.4f: Assumptions of sustainable rice cultivation practices in Current Policy Scenario
and Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Sustainable rice
cultivation practices
% of area under
rice
0.25 10 20 18 25
Scenario 3.1: Milk Productivity in Bovine Animals
Mitigation “co-benefits” of the adoption of the Ration Balancing Programme (RBP) stood at
0.0205 MtCO2e during 2019-24 for 1.63 lakh/163 thousand animals (MoEFCC, 2024)
Milk productivity refers to the average daily milk output of lactating animals. It is influenced
by several interrelated factors such as quality and quantity of feed and fodder, genetic
potential of the breed, animal health status, and regional agro-climatic conditions. Enhancing
milk productivity is critical for growing milk production without a proportional increase in the
bovine population. This, in turn, would moderate the sector’s greenhouse gas emissions. Recent
policy initiatives on animal health and nutrition, such as the Ration Balancing Programme (RBP),
Rashtriya Gokul Mission (RGM) and the adoption of innovative feed additives like Harit Dhara,
exhibit the potential to significantly increase milk yields across breeds.
Under the Current Policy Scenario, bovine productivity is assumed to increase from 5.27 to 12
kg/head/day by 2070 and 15 kg/head/day by 2070 in Net Zero Scenario (Table 2.4g).
Table 2.4g: Assumptions of enhanced in- milk bovine productivity in Current Policy
Scenario and Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Enhanced in- milk
bovine productivity
kg/head/day 5.27 8 12 12 15
Scenario 3.2: Share of In-Milk Population
In-milk adult female bovine animals refer to those cows and buffaloes that are actively lactating
and producing milk. The share of in-milk animals increases with a higher proportion of female
bovines in the herd and, within this group, a greater proportion of animals in lactation. For the
former, techniques like sex-sorted semen, which increase the probability of getting a female calf,
can be explored. For the latter, enhancing animal breed quality, nutrition, and health can extend
lactation periods, thereby improving the proportion of in-milk animals. Practices like deworming
can further improve nutrient absorption and reproductive health, while regular vaccination can
prevent reproductive infections (NAAS, 2013). Estrus detection and synchronisation techniques
to ensure timely insemination significantly improve conception rates and reduce calving intervals
(Mishra and Tiwari, 2014). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 23
Methodology
Under the Current Policy Scenario, in-milk bovine population is to assumed to increase in share
from 30% in 2019 to 45% by 2070 and 55% by 2070 in Net Zero Scenario (Table 2.4h).
Table 2.4h: Assumptions of increasing share of the in-milk population in Current Policy
Scenario and Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Share of the In- milk
population
% in-milk in
total bovine
population
30 40 45 45 55
Scenario 4.1: Reduced Crop Residue Burning
Mitigation “co-benefits” of the Crop Residue Management scheme (CRM) implemented under
Rashtriya Krishi Vikas Yojana (RKVY) aimed to reduce crop residue burning through ex-situ
management stood at 1.447 MtCO2e between 2019-24 (MoEFCC, 2024).
Crop residue refers to plant material, such as straw and stubble, that is left after harvesting.
In some parts of the country, for certain crops, some of this residue is burned to quickly clear
fields cost-effectively. This exacerbates air pollution and greenhouse gas emissions while wasting
valuable biomass. India generates around 140 tonnes of surplus crop residue annually, of which
92 tonnes are burnt (Bhuvaneshwari,2019). This report estimates the percentage reduction in
residue burning in the backdrop of the Crop Residue Management (CRM) scheme, exploring
long-term scenarios for significant reductions by 2050 and near elimination by 2070.
Under the Current Policy Scenario, crop residue burning is to assumed to decrease by 30% in
2070 and 60% by 2070 in Net Zero Scenario (Table 2.4i).
Table 2.4i: Assumptions of reduced burning of crop residue in Current Policy Scenario and
Net Zero Scenario (from Table 2.4)
Interventions Unit Current
status for
the baseline
of 2019
Current Policy
Scenario
Net Zero
Scenario
2047 2070 2047 2070
Reduced burning of
crop residue
% reduction in
crop residue
burnt
0 20 30 40 60
2.2 ENERGY DEMAND ESTIMATIONS FOR AGRICULTURE
The energy demand modelling framework consists of two modules: (i) irrigation pumping and
(ii) land preparation, tracing the pathway from key drivers to final energy use based on the
crop production projections.
1. Irrigation Module: estimates energy demand for pumping by linking crop demand
projections with irrigation water requirements, pump stock and efficiency parameters
As shown in Figure 2.2, the methodology starts with projected demand for major Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 24
Methodology
crops, which is converted into total cultivated area and then split into irrigated and
rainfed portions.
Irrigated crop area is transformed into irrigation water requirement using crop-specific
water productivity (kg/m³). In this study, only the pump-dependent share of this water
is carried forward to estimate total energy demand for irrigation water pumping.
Pumped water demand is converted into pump stock and finally into energy demand
using assumptions on pump discharge, operating hours, dynamic head, technology
mix, and pump efficiency,.estimates pumping energy demand by linking crop demand
projections with irrigation water requirements, pump stock and efficiency parameters
(Figure 2.2). A detailed methodology is given in Annexure IV.
Crop Demand
(million
tonnes)
Rice
Wheat
Maize
Arhar
Gram
Groundnut
Rapeseed &
Mustard
Sugarcane
Cotton
Share of
Irrigation
Irrigated
Crop
Demand
Water
Coefficient
(kg/m
3
)
Pumping
Water
Demand
Number of
Pumps
Pumping
Energy
Demand
Water Coefficient
*kg/m
3
)
Share of
Pumping
Average Discharge rate,
Dynamic Head, and
Funcitoning Hours
Technology Share of
Water Pumped +
Efficiency of Pumps
Figure 2.2: Irrigation module for energy demand projections
2. Land Preparation Module: As shown in Figure 2.3, Land-preparation energy demand
is estimated by projecting Gross Cropped Area (GCA) and applying the assumed
mechanisation rate to derive the area prepared using tractors and power tillers.
This mechanised area is allocated between tractors and tillers using a conservative
equivalent land-coverage assumption (tractor:tiller contribution based on operating-
capacity conversion). Finally, specific energy intensity factors (operating hours/ha ×
fuel use/hour) are applied to each area segment and aggregated to obtain total final
energy demand. A detailed methodology is given in Annexure V.
Gross
Cropped Area
Level of
Mechanisation
Land prepared
through
tractors and
tillers
Fuel
Consumption
Parameters
Final Energy
Demand
Figure 2.3: Land preparation module for energy demand projections Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 25
Methodology
To analyse the long-term energy demand of India’s agriculture sector, two alternate pathways
are assessed up to 2070: Current Policy Scenario and Net Zero Scenario. Both scenarios assume
the same crop production trajectories as developed in Figure 3.1, but differ in how this demand
is met in terms of energy use.
Assumptions for Irrigation Energy Consumption
Irrigation is the dominant source of agricultural energy use. Under the Current Policy Scenario,
irrigated share of cropped area rises steadily, groundwater dependence deepens, and diesel
pumps decline only gradually. Pump efficiency improves slowly, and solar adoption remains
limited. Under the Net Zero Scenario, in contrast, efficient irrigation practices (drip, sprinkler)
reduce water demand substantially, diesel pumps are phased out by 2035, and solar pumps
dominate by 2070 with much higher efficiencies (Table 2.5).
Table 2.5: Assumptions for estimating energy consumption for irrigation under Current
Policy Scenario and Net Zero Scenario
Scenarios 2020 Current
Policy
Scenario
(2070)
Net Zero
Scenario
(2070)
Notes
Irrigated share of
Gross Cropped
Area
53% 65% 60%
FAO (2021) notes that India already
leads globally in irrigated area;
future increases constrained by
water stress.
Groundwater/
Pumping share
65% 65% 60%
India remains heavily groundwater-
dependent in comparison to the
US (15%) and China (40%). Net
Zero Scenario assumes investments
in canal systems and recharge.
Water
Productivity
Improvement
+10 +25%
Net Zero Scenario assumes large-
scale drip/sprinkler adoption
(Sharma et al, 2018) assuming that
drip can halve water needs for
sugarcane/vegetables.
Share of Solar
Pumps
2% 40% 60% Diesel pump phase out by 2040
in Current Policy Scenario and by
2035 in Net Zero Scenario.
Share of Electric
Pumps
70% 60% 40%
Pump efficiency
(Solar & Electric)
36% 40% 50% Reflects best practices (EMC
2018).
Pumping Head
(metre)
28 50 35 Net Zero Scenario assumes aquifer
recharge and efficiency to prevent
sharp rise. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 26
Methodology
Assumptions for Land Preparation Energy Demand
Both scenarios assume full mechanisation by 2047, driven by rising rural wages and declining
farm labour. Differences lie in the energy profile: under the Current Policy Scenario, electric
tractors and tillers dominate with small amount of diesel and Compressed Natural Gas (CNG)
even by 2070. While in the Net Zero Scenario, there is almost 100% shift toward electric
tractors and tiller with higher share of tillers in land preparation compared to Current Policy
Scenario. (Table 2.6).
Table 2.6: Assumptions for estimating energy demand for land preparation under Current
Policy Scenario and Net Zero Scenario
Scenarios 2019
2070
Current Policy
Scenario
2070
Net Zero
Scenario
Notes
Mechanisation level 47% 100% 100% Tillers gain share as
smallholder mechanisation
expands.Tractor:tiller split 95:5 70:30 50:50
Energy intensity
per ha (MJ/ha) (%
reduction in energy
intensity)
Tractors:880
Tillers: 960
–20% by
2070
–40%
Fuel Consumption
in Land Preparation100% diesel
9% diesel,
8% CNG,
83% electric
99% electric,
1% Compressed
Natural Gas
(CNG)/
Compressed
Biogas (CBG)
Net Zero Scenario assumes
large-scale adoption of
e-tractors and clean fuel
tech. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 27
Methodology
3
RESULTS Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 28
Results
As discussed in the Background, this section presents mitigation co-benefits and energy
demand for the agriculture sector against the policy pathways. The chapter is organised into
two sections: (i) non-energy emissions pathways and (ii) energy transition pathways. The non-
energy emissions pathways cover crop and milk production projections, the resulting emissions
trajectories and mitigation co-benefits. The energy transition pathways present the projected
trends in energy consumption and demand for on-farm operations through 2070 under the
Current Policy Scenarios (CPS) and the Net Zero Scenarios (NZS).
3.1 NON-ENERGY EMISSIONS PATHWAYS IN AGRICULTURE
This section presents long-term emissions trajectories for the agriculture sector, with a particular
focus on emissions from rice cultivation, agricultural soils, and livestock (enteric fermentation
and manure management). As outlined earlier, the analysis adopts a supply-side, production-
linked modelling framework with 2019 as the baseline and assesses mitigation co-benefits under
the Current Policy Scenario (CPS) and the Net Zero Scenario (NZS) for 2047 and 2070.
Accordingly, rice production is expected to increase from about ~121 million tonnes to 184 million
tonnes (52%), while wheat to rise from ~109 million tonnes to ~178 million tonnest (63%). Maize
is expected to record the fastest growth, expanding from ~30 million tonnes to ~106 million
tonnes (~250%).
400
300
200
100
0
Gross cropped area (million hectares)
201020002020 2030 2040 2050 2060 2070
Year
185
198
216
225
233
239 240 240
Gross cropped area (million hectares) (2000 - 2070)
ProjectedHistorical
Figure 3.1: Gross cropped area projection (2000 to 2070)
3 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 29
Results
In this analysis, food production projections do not directly determine land-use outcomes.
Accordingly, Gross Cropped Area (GCA) projections are derived from historical trends (Figure
3.1). These two inputs are combined to derive overall fertiliser demand. Projections for organic
nitrogen inputs similarly follow historical trends, consistent with India’s submissions to the
UNFCCC (MoEFCC, 2022).
Figure 3.2: Production projections of bovine milk (2000-2070)
Figure 3.2 provide projections for milk that are based on trend-based approach, extrapolating
historical trajectories from 2000 to 2070. This excludes goat milk, which accounts for
approximately 4-5% of total milk output. Overall bovine milk is projected to increase from ~201
to ~694 million tonnes. This represents an increase of ~493 million tonnes, equivalent to a ~245%
rise over the period, indicating more than a threefold expansion.
Long-term non-energy emissions pathways
Under the Current Policy Scenario (CPS), agricultural emissions are projected to increase
modestly from ~506 in 2019 to ~531 MtCO₂e by 2070. This aggregate trend masks diverging
sub-sectoral trajectories. In the crop sub-sector, emissions (agricultural soils, rice cultivation,
and residue burning) are expected to decline by ~21% from ~183 to ~145 MtCO₂e (Figure 3.5).
In contrast, livestock sub-sector emissions (enteric fermentation and manure management)
are expected to rise by ~20% from ~322 to ~386 MtCO₂e (Figure 3.4). Consequently, the crop
sector’s share of agricultural emissions falls from ~36% in 2019 to ~27% in 2070, while livestock’s
share increases from ~64% to ~73% by 2070 (Table 3.1).
In contrast to the Current Policy Scenario (CPS), under the Net Zero Scenario (NZS) total
agricultural emissions are expected to decline to ~399 MtCO₂e by 2070. This reduction is driven
by a ~44% decline in crop sub-sector emissions and a modest decline ~8% decline in livestock
sub-sector emissions. Overall, NZS delivers a ~25% mitigation co-benefit relative to CPS by 2070
(Figure 3.3; Table 3.1).
Overall and bovine milk production (million tonnes) (2000-2070)
Production (million tonnes)
Bovine milk (million tonnes) Total milk (million tonnes)
2000 2010 2020 2030205020402060 2070
Year
800
600
400
200
0
NITI Report, 2024ProjectedHistorical
76
81
117
122
201
207
308
408
507
608
708
300
398
495
595
694 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 30
Results
Note: In 2019, agricultural emissions were at 421 MtCO₂e (AR2) which equals to 506 MtCO₂e
(AR5)
16
.
Table 3.1: Agriculture emission trends across crop and livestock sub-sectors (2019 to 2070)
Year Emission in Current Policy Scenario
(MtCO
2
e)
Emission in Net Zero Scenario
(MtCO
2
e)
Crop sub-
sector
Livestock
sub-sector
Total Crop sub-
sector
Livestock
sub-sector
Total
2019183 322 506 183 322 506
2050156 379 535 116 286 402
2070145 386 531 102 297 399
Current Policy Scenario Net Zero ScenarioBaseline
Overall agricultural emissions (non-energy) (MtCO
2
e) (2019-2070)
600
400
200
0
Emissions (in MtCO
2
e)
Year
201920502070
506
535531
402399
~25%
Figure 3.3: Projected agriculture emission under Current Policy Scenario and Net Zero Scenario
(2019-2070)
Current Policy Scenario Net Zero ScenarioBaseline
Overall livestock sub-sector (MtCO
2
e) (2019-2070)
Year
400
300
200
100
0
201920202070
322
379
286
386
297
Emissions (in MtCO
2
e)
Figure 3.4: Overall emissions – Livestock sub-sector (2019-2070)
16 As per authors’ analysis based on MoEFCC, 2021. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 31
Results
Current Policy Scenario Net Zero ScenarioBaseline
Overall emissions from crop sub-sector (MtCO
2
e) (2019-2070)
Year
250
200
150
100
50
0
183
156
145
116
102
201920502070
Emissions (in MtCO
2
e)
Figure 3.5: Overall emissions – Crop sub-sector (2019-2070)
The subsequent sections examine the key drivers of agricultural emission trajectories and their
associated mitigation co-benefits. Understanding these drivers is crucial to identifying pathways
that maximise mitigation co-benefits while delivering adaptation outcomes.
Methane emission from rice cultivation
The geographical concentration of rice mono-cropping in major producing regions such as
Punjab, Haryana, and Western Uttar Pradesh has intensified water stress and degraded soil
health. These regions also witness plateaued yields thereby, limiting farm profitability over the
past two decades (NFSM, 2014). As Section 1.3 highlights, water-management practices have
persisted in recent years. Key interventions to improve of rice cultivation in India include:
1. Crop diversification away from rice toward nutrient-dense, high-value alternatives.
2. Sustainable yield intensification through technological innovations, including high-
yielding varieties.
3. Adoption of sustainable rice cultivation practices such as alternate wetting and drying
(AWD), system of rice intensification (SRI), and direct-seeded rice (DSR).
Considering a coordinated scale-up of the above three interventions, the Net Zero Scenario
(NZS) is projected to deliver ~47% mitigation co-benefits against that of the Current Policy
Scenario (CPS) in 2070. Under the CPS, methane emissions from rice cultivation are projected
to decline by ~30%, from ~98 MtCO₂e in 2019 to ~69 MtCO₂e by 2070. In the NZS, emissions
decrease further to ~37 MtCO₂e, corresponding to a ~62% decline from 2019 (Figure 3.6). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 32
Results
Emissions from rice cultivation MtCO
2
e) (2019-2070)
125
100
75
50
25
0
Emissions (in MtCO
2
e)
201920502070
Year
98
79
50
69
37
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.6: Rice cultivation emission trends in Current Policy Scenario and Net Zero
Scenari (2019-2070)
Under Current Policy Scenario (CPS), rice acreage is expected to decline from ~44 to ~37 million
hectares, by 2070. Almost ~20% area is expected to adopt sustainable rice cultivation (SRC)
practices in the same period (Figure 3.7). Diversifying ~15% of the area and closing ~20% of the
yield gap raises average yields from 2.7 t/ha to 3.8 t/ha, allowing production to increase from
119 million tonnes to ~133 million tonnes (Figure 3.9) despite a ~16% reduction in cultivated area
(Figure 3.9).
Rice area under Current Policy Scenario (2070)
20%
80%
Figure 3.7: Area under rice cultivation in Current Policy Scenario (2019-2070)
Conventional rice cultivation
Sustainable rice cultivation Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 33
Results
Rice area under Net Zero Scenario (2070)
25%
75%
Figure 3.8: Area under rice cultivation in Net Zero Scenario (2019-2070)
Under the Net Zero Scenario (NZS), interventions are more ambitious. Rice acreage is expected
to decline to ~20 million hectares, with sustainable rice cultivation (SRC) practices covering
25% of rice area (Figure 3.8) by 2070. Diversifying ~20% of the area and closing ~70% of the
yield gap
17
, will sustain production at ~126 million tonnes (Figure 3.9). The modest production
increase mirrors India’s population increase and the declining per capita rice consumption,
consistent with broader dietary diversification (FAO, 2024). Together, these measures account
for the significant mitigation co-benefits under both the scenarios without comprising on food
security of India (Figure 3.9).
Production of rice (million tonnes) (2019-2070)
200
150
100
50
0
Production (million tonnes)
201920502070
Year
119
135134
126128
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.9: Rice production from 2019 to 2070 under Current Policy Scenario and Net Zero Scenario
Rice area (2019-2070)
17 Projected yield in 2070 is ~7.6 t/ha.
Conventional rice cultivation
Sustainable rice cultivation Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 34
Results
Nitrous oxide emissions from Agricultural soils
Higher fertiliser application rates increase manufacturing demand, contribute to rising import
dependence, and impose a fiscal burden of subsidies exceeding `2 lakh crore, while also
degrading soil health (Singh, 2023). To address these challenges, India has implemented
interventions to improve fertiliser use efficiency (FUE) through reduced application, soil health
management, promotion of sustainable agricultural practices among others. At the same time,
policies aimed at increasing cropping intensity and enabling additional cropping cycles are
expected to raise aggregate nitrogen fertiliser consumption, partially offsetting the gains.
Under both the Current Policy Scenario and the Net Zero Scenario, these interacting dynamics:
improvements in FUE reflected in lower per-hectare application rates, adoption of sustainable
practices such as natural farming/organic farming (chemical-free farming), and the countervailing
effects of higher cropping intensity, are jointly modelled to assess long-term agricultural soil
emission trajectories.
Emissions from agricultural soils (MtCO
2
e) (2019-2070)
80
60
40
20
0
Emissions (MtCO
2
e)
201920502070
Year
76
68
62
67
60
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.10: Agricultural soil emission trends in Current Policy Scenario and Net Zero Scenario
(2019-2070)
Cropping intensity (GCA/NSA) (2019 - 2070)
2.0
1.5
1.0
0.5
0.0Cropping intensity (GCA/NSA)
201920502070
Year
1.5
1.6
1.71.7
1.8
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.11: Cropping intensity in Current Policy Scenario and Net Zero Scenario (2019-2070) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 35
Results
Nitrogen fertiliser consumption (kg/ha) (2019-2070)
100
75
50
25
0
Fertiliser consumption (kg/ha)
201920502070
Year
90
83
72
80
66
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.12: Nitrogen fertiliser consumption per ha in Current Policy Scenario and Net Zero Scenario
(2019-2070)
Under the Current Policy Scenario (CPS), these measures are projected to deliver ~11% mitigation
co-benefits, reducing emissions from ~76 MtCO₂e in 2019 to ~67 MtCO₂e by 2070 (Figure 3.10).
This outcome reflects improvements in fertiliser use efficiency, which lower nitrogen application
rates from 90 kg/ha in 2019 to 80 kg/ha by 2070 (Figure 3.12). At the same time, the expansion
of natural and chemical-free farming is projected to increase to 28 million hectares (20% of
NSA) (Figure 3.13). This reduces total nitrogen fertiliser demand in India from 19 million tonnes
in 2019 to 15 million tonnes in 2070, even as cropping intensity increases (Figure 3.11).
Similarly, under the Net Zero Scenario, emissions from fertiliser use are expected to decline
further to 60 MtCO₂e by 2070 (~20% reduction), providing an additional 10% of mitigation co-
benefit relative to Current Policy Scenario (Figure 3.10). This is achieved through wider adoption
of natural and chemical-free farming practices upto 25% of Net Sown Area (Figure 3.13), lowering
nitrogen application rates due to improved fertiliser use efficiency (~50% by 2070).
40
30
20
10
0
Area (million hectares)
20502070
Year
22
2928
35
Area under Chemical-free farming (million hectares) (2019 - 2070)
Current Policy Scenario Net Zero Scenario
Figure 3.13: Area under Natural and Chemical-free farming Current Policy Scenario and Net Zero
Scenario
Note: Agricultural soil emissions are also sensitive to crop diversification, particularly shifts from rice to high-input
crops like horticulture. Currently, nitrogen use per hectare is estimated at the aggregate level, but integrating crop-wise
fertiliser data from the All-India Input Survey 2016–17 could improve future sensitivity analyses. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 36
Results
Realising the Net Zero Scenario (NZS) requires careful, calibrated scaling of key interventions.
Integrated Nutrient Management (INM) under the National Mission for Sustainable Agriculture
(NMSA) and digital Soil Health Cards optimize nutrient application and maintain soil health.
Mandatory consumption of 100% neem-coated urea reduces nitrogen volatilisation losses.
Scaling chemical-free farming under National Mission on Natural Farming (NMNF) and Pradhan
Mantri Krishi Vikas Yojna (PMKVY) must be implemented strategically to protect food security
and farmer incomes, while transitioning millions of hectares to low-input, sustainable cultivation.
Livestock emissions
India is the world’s largest producer of milk and contributes to ~25% of global milk output (PIB
2024). Milk production is projected to grow to ~467 million tonnes in 2050 and ~693 million
tonnes in 2070, cumulatively rising by ~245% since 2020.
Emissions from livestock sub-sector (MtCO
2
e) (2019-2070)
400
300
200
100
0
Emissions (in MtCO
2
e)
201920502070
Year
322
379
286
386
297
Current Policy Scenario Net Zero ScenarioBaseline
Figure 3.14: Emissions from livestock sector in Current Policy Scenario and Net Zero Scenario
(2019-2070)
Under the Current Policy Scenario (CPS), livestock emissions are projected to rise from ~322
MtCO₂e in 2019 to ~386 MtCO₂e by 2070 (~20% increase) (Figure 3.14), with average in-milk
productivity expected to reach 12 kg/day per animal (Figure 3.15). In contrast, the Net Zero
Scenario (NZS) reduces emissions to ~297 MtCO₂e by 2070 (~8% below 2019 levels) (Figure
3.14), while boosting productivity to 15 kg/day per animal (Figure 3.15). Within the herd, the
proportion of in-milk animals rises from 35% in 2019 to 50% in 2070, supporting higher milk
yields (Figure 3.16).
The Net Zero Scenario achieves ~23% mitigation co-benefits in the livestock sector through
technological and management interventions. Yield improvements are driven by breed and
genetic enhancements via programs like the Nationwide Artificial Insemination Programme
(NAIP), alongside advanced breeding technologies, including in-vitro fertilisation (IVF).
Additionally better nutrition through the Ration Balancing Programme (RBP), and year-round
availability of green fodder using silage and roughage technologies further help to enhance
productivity. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 37
Results
Productivity of in-milk bovines (kg/day/head) (2019-2070)
201920502070
Year
20
15
10
5
0
Productivity (kg/day/head)
Current Policy Scenario Net Zero ScenarioBaseline
5
9
13
12
15
Figure 3.15: Milk yield trends in Current Policy Scenario and Net Zero Scenario (2019-2070)
Current Policy Scenario Net zero ScenarioBaseline
In-milk bovine population (million) (2019-2070)
200
150
100
50
0
In-milk bovine population (in million)201920502070
Year
100
154
108
157
127
Figure 3.16: Share of in-milk bovine population in the total bovine population (2019-2070)
3.2 ENERGY EMISSIONS PATHWAYS IN AGRICULTURE
In 2020 India’s agriculture consumed ~23 Mtoe of direct energy, 21 Mtoe for pumping (mostly
electricity and diesel) and 2.1 Mtoe for land preparation (primarily diesel for tractors and
tillers) (CEA, 2022). Under Current Policy Scenario (CPS), the total energy consumption in
agriculture is expected to increase to 42 Mtoe by 2050 and 54 Mtoe by 2070. Under the Net
Zero Scenario (NZS) also, the total energy use increases to 35 Mtoe by 2050 and 39 Mtoe
by 2070. However, the total energy use in NZS is lower than the corresponding numbers for
CPS. During the corresponding period, the agricultural output has nearly doubled. This shows
that efficiency gains and technology shifts can decouple energy demand from agricultural
output (Figure 3.17). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 38
Results
Land Preparation Pumping
60
50
40
30
20
10
0
Mtoe
2020202520502070
Current Policy
Scenario
Current Policy
Scenario
Net Zero
Scenario
Net Zero
Scenario
Energy Consumption in the Agriculture Sector (Mtoe) (2020-2070)
23
4
3
2124
38
31
51
36
33
Figure 3.17: Overall energy consumption in Agriculture Sector (2020-2070)
Energy consumption in irrigation
Under Current Policy Scenario, energy demand rises from 21 Mtoe in 2020 to 38 Mtoe in 2050
and 51 Mtoe by 2070, driven by expanding irrigation (from 53% to 65% of GCA) and higher
groundwater reliance (Figure 3.18a). Diesel pumps decline slowly, while grid electricity remains
primary, complemented by solar pumps (40% of energy by 2070). Modest efficiency gains
(40%) and deeper pumping heads (50 m) sustain high energy demand.
In Net Zero Scenario, pumping rises more moderately from 21 to 32 Mtoe by 2050, plateauing
at 36 Mtoe in 2070 (Figure 3.18a). Efficiency improvements, adoption of drip/sprinkler irrigation,
aquifer recharge, and better management limit energy growth. Diesel pumps are phased out by
2035, with 40% grid electricity and 60% solar supplying pumping energy by 2070 (22 Mtoe).
Energy Consumption in Pumping (Mtoe) (2020-2070)
60
50
40
30
20
10
0
Mtoe
2020
1.9 1.3
18.9 21.2
28.6
20
14.2
30.3
0.2
21
23.5
37.9
31
50.6
35.5
0.9
9.2
11
21.3
20.2
202520502070
Current Policy
Scenario
Current Policy
Scenario
Net Zero
Scenario
Net Zero
Scenario
Diesel Electricity Solar
Figure 3.18a: Energy demand and fuel mix in agricultural pumping under Current Policy Scenario
(CPS) and Net Zero Scenario (NZS) by 2050 and 2070
23
27
42
34
54
39 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 39
Results
Diesel CNG/CBG Electricity
Energy Consumption in Land Preparation (Mtoe) (2020-2070)
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Mtoe
2020 202520502070
Current Policy
Scenario
Current Policy
Scenario
Net Zero
Scenario
Net Zero
Scenario
2
2.5
1.7
1.0
0.3
2.5
0.2
0.3
2.7
1.9
0.3
1.7
Figure 3.18b: Energy demand and fuel mix in land preparation under Current Policy Scenario
(CPS) and Net Zero Scenario (NZS) by 2050 and 2070
Energy consumption in land preparation
Under the Current Policy Scenario (CPS), energy demand rises from 2.1 Mtoe in 2020 to 3.8
Mtoe in 2050 and 3.3 Mtoe by 2070, with 9% comming from diesel and 8% from CNG by
2070 (Figure 3.18b). Efficiency gains and precision agriculture reduce per-hectare fuel use, but
expanding mechanisation drives overall demand.
Under Net Zero Scenario, total energy stabilises at ~2.5 Mtoe by 2070 despite full mechanisation
(Figure 3.18b). Diesel is fully phased out by 2070, replaced by electric tractors and tillers (~2.5
Mtoe) with just 1% Compressed Biogas (CBG), sourced from crop residues and animal waste, acts
as a transitional fuel in the 2040s, supporting India’s Sustainable Alternative Towards Affordable
Transportation (SATAT) initiative, reducing residue burning, and generating rural income. In the
later decades, electric tractors dominate, offering ~30% higher efficiency and integration with
a decarbonised grid and solar charging.
2
2.5
3.8
3.2
3.3
2.5 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 40
Results
Box 3: State-Level Transitions in Practice
Gujarat – The Suryashakti Kisan Yojana (SKY) has shown how decentralized solar pumps
connected to the grid can displace diesel, reduce subsidy costs, and even create new
income streams as farmers sell surplus electricity. Farmers in Dhundi village, for example,
have eliminated dozens of diesel pumps and now treat solar power as a secondary crop.
Rajasthan – In Rajasthan, drip irrigation coupled with solar pumps has enabled farmers
to sustain yields while cutting water and energy use by 30–50%. This exemplifies the
water–energy efficiency nexus modeled in the Net Zero Scenario.
Maharashtra – Maharashtra’s feeder solarization programme demonstrates how
centralized solar generation can deliver daytime electricity to thousands of pumps
simultaneously. By 2025, the state targets 30% solarized feeders, reducing dependence
on coal-based power. Taken together, these cases illustrate that the modeled Net Zero
Scenario is not abstract.
The combination of efficiency (Rajasthan), decentralized solar (Gujarat), and feeder-
level solarization (Maharashtra) shows how India can achieve plateauing energy demand
despite rising output, while lowering fiscal and environmental costs. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 41
Results
4
KEY CHALLENGES AND
SUGGESTIONS Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 42
4
Key Challenges and
Suggestions
4.1 KEY CHALLENGES
The transition of India’s agriculture and allied sectors from the Current Policy Scenario (CPS) to
ambitious Net Zero Scenario (NZS) faces complex, interconnected structural challenges, despite
the NZS offering a ~25% mitigation co-benefit by 2070 compared to the CPS trajectory. As a
result, achieving the mitigation co-benefits in NZS require addressing many issues:
1. Effectively managing trade-offs while harnessing synergies across livelihoods,
resilience, and food security is critical to implementing Net Zero Scenario pathways:
For instance, adopting chemical-free practices, such as Natural Farming, can increase
the availability of diverse and nutrient-rich foods, improving both public health and
environmental quality by reducing agrochemical runoff and soil degradation. On the
other hand, it may lower yields in the green revolution regions in the short term while
possibly increasing them in the rainfed regions. The scaling up thus needs to be well
planned to keep the food grain supply stable for India’s food security. Balancing these
competing and complementary objectives is critical. Hence, developing evidence-
backed long-term strategic roadmaps is critical for a risk-calibrated approach to
implementing the Net Zero Scenario (NZS) pathways.
Driving the intervention identified under the Net Zero and Current Policy Scenarios
feasibly needs comprehensive, long-term scaling strategies that are context-specific,
targeted, and phased to capture synergies and balance trade-offs. For instance, as
exemplified in Annexure VI (Part-1), scaling crop diversification requires a phased
approach that targets states based on yields, biophysical suitability, and the capacity
of public procurement channels, while safeguarding national food and nutrition
security. Scaling animal health and nutrition interventions to boost milk productivity
must account for contextual realities, such as state-specific breed composition, feed
consumption patterns among various breeds, socioeconomic drivers of bovine rearing,
and climate resilience of the whole bovine economy.
2. Inherent affordability and access barriers for scaling adoption: Agri-food systems
face constrained adoption of technologies, mechanisation, particularly among small
and marginal producers who struggle with affordability and last-mile access. These
constraints are compounded by under capacitated support services, across extension,
credit, insurance, market linkages, and post-harvest systems, that fail to enable a
smooth transition to resilient and diversified practices. Further, significant gaps in
timely, reliable, and localised data limit evidence-based decision-making for producers,
value-chain actors, and policymakers alike. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 43
Key Challenges and Suggestions
Addressing these barriers requires a systemic overhaul of the enabling ecosystem
that connects farmers and consumers. This includes stronger investments in research
and development, deeper technology penetration, and the creation of targeted,
responsive, and dynamic Krishi Decision Support Systems such as being done through
the Agri-Stack. Improved market intelligence and transparent, well-designed incentive
disbursement mechanisms will be essential to drive widespread adoption of sustainable
agri-food practices.
This exercise of supply-side modelling that has generated pathways, is a critical first step
towards informing long-term planning for the agriculture sector. However, translating
the emission pathways into policy and planning frameworks requires feasible and
targeted roadmaps. An agri-food systems approach delivers this required integrated
perspective, which is essential for maximising agriculture’s contribution to long-term
livelihoods development, nutrition and health enhancement, resilience-building, as well
as climate mitigation co-benefits.
3. Managing trade-offs and leveraging land–energy–water synergies: The Net Zero
Scenario implementation must balance food security, water sustainability, clean energy
deployment, and fiscal outcomes. Mechanisation and electrification without subsidy and
groundwater reforms risk increasing power demand and utility stress, while large-scale
solar raises land-use competition. Integrated approaches, combining solar irrigation,
micro-irrigation, electric machinery, and agrivoltaics offer strong synergies but require
coordinated, cross-sectoral planning. Institutional silos and fragmented governance
must be resolved.
4. Rising energy demand from irrigation pumping and groundwater dependence:
Irrigation energy demand continues to grow due to increasing cropping intensity,
deeper groundwater tables, and climate-induced variability in rainfall. Even with
solarisation, pumping loads may rise if water use remains unmanaged, limiting net
energy savings. Weak regulation of groundwater extraction and limited adoption of
efficient irrigation technologies compound this challenge. Managing pumping demand
is therefore central to achieving durable mitigation outcomes.
5. Energy-intensive land preparation and slow transition from diesel equipment: Land
preparation remains heavily reliant on diesel-powered tractors and tillage equipment,
contributing significantly to on-farm energy use and emissions. While electric and
Compressed Biogas (CBG)-based alternatives are emerging, adoption is constrained by
high costs, limited charging or fuel infrastructure, and concerns over reliability during
peak seasons. Without targeted support and shared-access models, diesel lock-in in
land preparation risks persisting well into the transition period.
6. Behavioural Inertia Across Producers and Consumers: Deep-rooted production and
consumption habits limit shifts toward diversified, nutritious, and sustainable food
systems. Producers remain anchored to familiar cropping patterns due to risk aversion
and market uncertainties, while consumers continue to prefer staple-heavy diets despite
the availability of healthier alternatives. This is exacerbated by the absence of strong,
integrated demand–production signals. Currently, fragmented many incentives work at
cross-purposes. This reinforces existing production patterns and slows the transition
to diversified, sustainable production systems. Addressing demand-side drivers and Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 44
Key Challenges and Suggestions
barriers is far more critical: fostering dietary diversification (demand) enables shifts in
cropping patterns (supply) and unlocks greater mitigation potential than pure supply-
side measures (Jha et al., 2023; Patange et al., 2024).
For instance, mainstreaming millet consumption through public procurement channels
(e.g., the Public Distribution System) and high-visibility initiatives like the International
Year of Millets and India’s Millet Mission can stimulate consumer demand, incentivising
farmers to shift cultivation away from emission-intensive crops like rice. In addition,
unlocking market potential, both domestic and global, is crucial to sustaining the
production trajectory. For instance, milk exports have expanded notably over the past
decade, yet boosting global competitiveness remains a challenge, constrained by
quality standards, trade barriers, and logistical inefficiencies.
4.2 SUGGESTIONS FOR SUSTAINABLE LONG-TERM PATHWAYS FOR
AGRICULTURE AND ALLIED SECTORS
This analysis demonstrates that the proposed Net Zero Scenario yields a ~25% mitigation co-
benefit against the Current Policy Scenario. The finding is based on nine key interventions
developed under multi-benefit centered, policy-driven assumptions. Interventions refined
through rigorous, multi-stakeholder consultations highlight that there is both the need and
feasibility of a systemic transformation within the sector that also comes with significant
mitigation co-benefits. As a result, the following framework is proposed to accelerate an agri-
food systems transformation for resilience, farmers’ incomes and food security that deliver
mitigation co-benefits:
1. Develop long-term and short-term strategies to scale multi-benefit interventions:
Realising mitigation co-benefits requires ambitious yet feasible, risk-calibrated scaling
of multiple interventions. This calls for a careful assessment of opportunities, trade-offs,
social acceptance, and financial viability to avoid negative spillovers while safeguarding
food security and livelihoods. This report therefore suggest intervention-specific
roadmaps to maximise co-benefits and minimise trade-offs, as outlined in the following
section:
a) Crop diversification: India’s crop diversification programme under Rashtriya Krishi
Vikas Yojna (RKVY) has promoted shifts from water-intensive rice cultivation in
Green Revolution states since 2015. Yet these regions still dominate national rice
production. Achieving a 20% reduction in rice cultivation area by 2070 demands
pragmatic interventions (technological, economic, and institutional) supported
by geographically sensitive and temporally phased roadmaps that strategically
enable:
i. Supply-side diversification: Promote diversification through crop alternatives,
such as pulses, millets, oilseeds, and horticultural crops, leveraging the
Government of India’s flagship missions.
ii. Demand-side linkages and diet diversification: Ensure production shifts are
complemented by strong demand signals. This includes integrating pulses Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 45
Key Challenges and Suggestions
and millets into the Public Distribution System (PDS), to create assured
market linkages that drive consumption shifts. These efforts, as they enable
integrated production- consumption shifts, must be guided by socio-economic
assessments that align geographical diversification priorities with household-
level nutrition and affordability considerations.
As outlined in Annexure VI (Part-1), strategically bundling and sequencing
the above supply and demand side interventions will be critical to realising
crop diversification, without undermining the food system security or farmer
livelihoods.
b) Natural and Chemical-free farming: India has initiated several efforts to promote
natural and chemical-free farming, including the National Mission on Natural
Farming (NMNF), Paramparagat Krishi Vikas Yojana (PKVY), and Bharatiya Prakritik
Krishi Paddhati (BPKP). These programs have laid a foundational framework for
agroecological transitions by focusing on policy support, certification mechanisms,
and capacity-building initiatives. The pace of adoption needs to be accelerated.
Achieving the target of bringing 25% of agricultural land under natural and
chemical-free farming by 2070 will therefore require a combination of technological
and institutional interventions, supported by implementation strategies tailored to
agro-climatic suitability and local farming systems.
As explained in Annexure VI (Part-2), targeting should integrate agronomic
(productivity, fertiliser use), biophysical (soil, rainfall, elevation), and socio-
economic (community institutions like SHGs) parameters to secure long-term
nutrition and environmental sustainability. Natural Farming can be applied both
to rainfed areas (boosting yields, profitability, and nutrition) and Green Revolution
hotspots addressing water stress and soil degradation.
c) Enhancement of aggregate livestock productivity: Requires converging
production and demand-side strategies across milk, feed, and fodder value chains,
to ensure food security, climate resilience, and reduced emissions intensity. State-
wise bovine breed analysis, feed needs, and fodder shortage mapping will help to
boost output while optimising land use. To balance the trade-off, there is a need
for:
i. Breed improvement: Breed improvements may be facilitated through
technological interventions, such as artificial insemination and in-vitro
fertilisation, guided by agro-climatic and socio-economic suitability of the
breeds.
ii. Improve animal nutrition and health: Breed improvements impact feed and
fodder demand that could constrain fodder availability in India. As a result,
it is imperative to assess the future feed requirements of different breeds.
Developing institutional mechanisms for channeling fodder from surplus
to deficit states can address spatial imbalances. To overcome temporal
shortages, particularly in green fodder, practices such as silage-making should
be promoted in fodder-surplus regions. The improvement in animal nutrition
would potentially also improve animal health and productivity. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 46
Key Challenges and Suggestions
iii. Feed efficiency: Improve overall feed quality with high-protein options to
boost livestock productivity, thereby reducing land pressure as enhanced
efficiency lowers total fodder demand.
The increase in livestock productivity would require a dedicated focus on animal
nutrition and adequate availability of fodder, increasing the pressure on land. This will
potentially necessitate an increase in India’s cropping intensity even more.
2. Adopt an integrated “agri-food” systems approach: India’s agricultural transition
requires coordinated policy action across land, energy, and water systems; isolated
interventions, such as solar irrigation without groundwater governance, electrification
without subsidy reform, or renewable deployment without land-use planning, risk
inefficiencies, fiscal stress, and competition with food production. Our analysis indicates
that no single intervention can independently deliver meaningful mitigation or energy-
efficiency co-benefits by 2070; whether focused on crop diversification, natural and
chemical-free farming, or yield intensification, interventions scaled in isolation risk
unintended trade-offs, as illustrated by the Green Revolution, which addressed food
security but undermined long-term soil health and ecosystem resilience (John and Babu,
2021). Achieving durable outcomes, therefore, requires an agri-food systems approach
that aligns production systems, dietary patterns, value chains, and environmental
objectives across land, energy, food, health, biodiversity, and water systems (FAO,
2024). Initiatives such as the Pradhan Mantri Dhan-Dhaanya Krishi Yojana (PMDDKY)
demonstrate the potential of such integration by converging crop diversification,
rural livelihoods, and access to credit across 100 low-productivity districts. Scaling
similar efforts through a whole-of-government approach-ensuring alignment across
the Ministries of Agriculture, Energy, Water, and Health-can embed clean energy,
micro-irrigation, electric farm machinery, healthy diets, and dual-use solutions such as
agrivoltaics (Gómez-Casanovas et al., 2023) directly within agricultural development
strategies.
3. Conduct integrated assessment of the agri-food system for long-term planning
and ambition setting: Conduct integrated assessment of the agri-food system for
long-term planning and ambition setting: To scale integrated interventions effectively,
ambition setting must be future-sensitive, underpinned by robust scenario analyses
and periodic reviews for adaptive governance, while accounting for socio-economic
and climatic uncertainties. Maximising mitigation co-benefits from the agriculture
sector by 2070 while balancing economic development requires a fundamental shift
away from siloed, short-term planning approaches. Integrated Assessment Modelling
(IAM) is essential for generating data-driven insights that support decision-making and
navigate the complex interdependencies of climate, agriculture, and socio-economic
systems (IPCC, 2014). For example, Jha et al. (2022) highlight that dietary shifts
towards healthy diets could reduce India’s emissions by ~60 % compare to baseline.
Similarly, a robust IAM assessment, calibrated to India’s national context, can integrate
supply-side interventions with demand-side dynamics (e.g., rising incomes, urban
dietary shifts), while quantifying trade-offs such as land-use competition between
food security, afforestation goals and goals of other land requiring economic sectors. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 47
Key Challenges and Suggestions
Critically, it can assess how macroeconomic levers impact farm profitability and rural
livelihoods, ensuring no population is marginalised in the transition. By embedding
climate projections (e.g., monsoon variability, heat stress). This could be vital to align
India’s dual goals of becoming a Viksit Bharat by 2047 and a net-zero economy by
2070, while ensuring food systems transformation strengthens, rather than strains, the
livelihoods of those who feed the nation.
4. Implement an “Efficiency-first + clean energy solutions” strategy to achieve maximum
efficiency within the sector: The agricultural energy transition, driven primarily by
irrigation demand, must follow an adaptation-first, agriculture-led sequencing to avoid
energy-intensive lock-ins. Energy demand projections (Figure 3.17) indicate that simply
substituting diesel and grid-connected pumps with solar pumps lowers emissions but
does not curb total energy demand, as irrigation volumes and groundwater dependence
continue to rise. An efficiency-first strategy is therefore essential, prioritising resource-
efficient practices such as micro-irrigation, precision and daytime irrigation scheduling,
sustainable practices, and rationalised input usage to reduce both water and energy
intensity while strengthening climate resilience. Evidence from Box 3, demonstrates
that solarisation, when explicitly linked to efficient water use, can induce behavioural
change and deliver up to 30% reductions in water and energy consumption.
Building on these efficiency and adaptation gains, clean energy interventions, including
renewable adoption, electrification of farm operations, and the use of clean fuels such
as Compressed Biogas (CBG), can then be scaled to decouple productivity growth
from energy use. Mechanisation, which is inevitable by mid-century, need not lock in
emissions if the transition is directed towards electric and clean-fuel-based machinery,
as reflected in the net-zero pathway. Custom Hiring Centres (CHCs) will be central to
this transition, lowering upfront costs, improving the utilisation of clean machinery, and
extending access to smallholders who cultivate farms averaging less than 1.1 hectares,
thereby ensuring that mechanisation delivers productivity, energy-efficiency, and
mitigation co-benefits in a resource- and fiscally sustainable manner. ANNEXURES Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 50
Annexure I:
Country-Specific Emission
Factors for the Study
Table Annex. I.1: Country-specific emission factors for Rice cultivation
Region/EcosystemWater Regime Emission Factor (kg CH
4
/ha)
Irrigated
Continuously Flooded159.74
Single Aeration66.2
Multiple Aeration19.3
RainfedDrought Prone68.84
Flood Prone189
Deep WaterDeep Water190
Source: MoEFCC, 2018 (BUR 4 emission factors are unavailable)
Table Annex. I.2: Agriculture soil emissions: Emission factors
ParameterCountry-specific emission coefficients/
factors (% of N converted to N2O)
EF1 (N
2
O emission from applied fertiliser)0.55
EF4 (N
2
O emission from volatilized N from fertiliser
and manure)
0.50
EF5 (N
2
O emission from leached and run-off N from
fertiliser and manure)
0.50
FracGASF (Gas loss through volatilisation from
inorganic fertiliser)
20
FracGASF-AM (Gas loss through volatilisation from
manure)
20
Fracleach (Leaching loss of N from applied fertiliser
and manure)
10
Source: MoEFCC, 2023
Table Annex. I.3: AWB: Emission factors (CH
4
and N
2
O)
GHG Gas typeEmission Factor (kg GHG/kg biomass burnt)
CH
4
0.0027
N
2
O0.00007
Source: BUR 2, 2019 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 51
Annexure I: Country-Specific Emission Factors for the Study
Table Annex. I.4: Livestock: Emission factors (CH
4
and N
2
O)
Category Sub-Category Age Group Methane Emission Factor Nitrous Oxide
Enteric
Fermentation
(kg CH
4
/
head/ year)
Manure
Management
(kg CH
4
/
head/ year)
Manure
Management
(kg N
2
O/head/
year)
Indigenous
Cattle
Dairy Cattle Indigenous 283.5 0.0006
Non-Dairy Cattle
(indigenous)
0–1 year 91.2 0.0004
1–3 years 232.8 0.0004
Adult 322.9 0.0004
Crossbred
Cattle
Dairy Cattle Cross-bred 433.8 0.0006
Non-Dairy Cattle
(cross-bred)
0–1 year 111.1 0.0004
1–3 years 262.3 0.0004
Adult 332.5 0.0004
Buffalo Dairy Buffalo504.4 0.0006
Non-Dairy
Buffalo
0–1 year 81.8 0.0004
1–3 years 223.4 0.0004
Adult 444 0.0004
Source: MoEFCC, 2004 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 52
Annexure II:
Policy Typologies
Table Annex. II.1: Policy mapping and assumptions behind scenarios
ScenariosAssumptions
Cropping intensity Pradhan Mantri Krishi Sinchayee Yojana–Micro Irrigation (PMKSY-MI) and
the Accelerated Irrigation Benefits Programme (AIBP) are expected to
enhance cropping intensity, though overall increase may be limited by
small landholdings and gradual labour shift away from agriculture.
Crop diversification Policies like the Crop Diversification Programme (CDP) and Mera
Paani Meri Virasat (MPMV) aim to reduce reliance on rice, wheat, and
sugarcane. Coupled with rising income and demand for pulses, millets,
and horticulture, these shifts are likely to make alternative crops more
profitable and widely adopted.
Yield intensification Schemes like Sub-Mission on Agricultural Mechanisation (SMAM) and
Custom Hiring Centres (CHCs) aim to improve access to farm machinery
and enhance cultivation efficiency. Further, Soil Health Card (SHC) and
Integrated Nutrient Management (INM) initiatives aim to improve soil
fertility and support sustainable yield growth.
Natural and Chemical-
free farming
Schemes like National Mission on Natural Farming, Paramparagat Krishi
Vikas Yojana (PKVY), and Bharatiya Prakritik Krishi Paddhati (BPKP) aim
to promote natural and organic farming through targeted support and
awareness. Further Participatory Guarantee Scheme (PGS) and National
Programme on Organic Production (NPOP) certifications encourage
adoption by offering credible certification systems for organic produce.
Fertiliser uptake
efficiency
Fertiliser uptake is expected to improve through interventions like
neem-coated urea, fertigation, micro irrigation, and Integrated Nutrient
Management (INM).
Support measures such as gypsum distribution under the National Mission
for Sustainable Agriculture and upcoming technologies like AI-driven
precision agriculture further enhance nutrient efficiency and application.
Conventional rice
cultivation practices
Policies like the National Food Security Mission (NFSM) and Bringing
Green Revolution to Eastern India (BGREI) promote practices such as
System of Rice Intensification (SRI) and Direct Seeded Rice (DSR), which
help reduce methane emissions from rice cultivation.
Crop residue burning Government initiatives such as crop residue management schemes and the
promotion of equipment like Happy Seeders aim to reduce Agricultural
Waste Burning (AWB).
Bovine productivity An overall increase in livestock productivity is assumed, driven by
government initiatives focused on animal health and nutrition. Programs
such as the National Dairy Plan (NDP), which promotes ration balancing,
and state-wise fodder development efforts led by institutions like Indian
Grassland and Fodder Research Institute (IGFRI), are expected to enhance
per-animal yield (kg/day). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 53
Annexure II: Policy Typologies
Development of Current Policy Scenario and Net Zero Scenario
Long-term strategic pathways were developed through iterative, multi- stakeholder consultations
(with 30+ experts). The process evaluated adoption trajectories of different interventions, and
impact potential is quantified across temporal horizons (2020–2070). The four-phased pathways
development process comprised:
1. Policy identification: Mapping government policies shaping agricultural production systems.
2. Policy typology development: Classification of policies into typologies based on their
primary outcome (productivity enhancement, sustainable agriculture practices, agricultural
intensification, etc.) with their corresponding mitigation co-benefits.
3. Scenario definition: Identifying key variables against the policy typologies.
4. Scenario Building: Consultations for consensus building with stakeholders, experts and
Working Group members to align on differentiated assumptions for scenarios across near-
term (2030), mid-century (2047), and long-term (2070) horizons.
The last step is followed for the development of two pathways: Current Policy Scenario (CPS)
and Net Zero Scenario (NZS). Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 54
Annexure III:
Emissions in Sustainable
Rice Systems
Table Annex. III.1: Alternative Rice cultivation strategies and their emission reduction
potentials
StateAlternative
Cultivation Strategy
Emission Reduction
Potential from
Literature (%)
References
AssamSemi-Dry Cultivation 29.0(Gorh and Baruah 2019)
(Gogoi, Baruah, and Gupta
2008)
Andhra Pradesh
(excluded)
SRI + AWD26.8 (Duvvuru and Motkuri 2013)
Bihar
DSR +AWD89.7 (Pathak and Aggarwal 2012)
SRI +AWD71.5
AWD29.5
DI100
Haryana
DSR + AWD89.5 (Pathak and Aggarwal 2012)
SRI +AWD64.0
AWD29.1
DI100
OdishaAWD75.0(Mohanty et al. 2017)
Punjab
DSR +AWD89.5 (Pathak and Aggarwal 2012)
DSR82.0
SRI + AWD64.0
DI100
Tamil Nadu
AWD52.8 (Thanakkan and Selvaraj 2020)
DSR + AWD16.6 (Thanakkan and Selvaraj 2020)
SRI + AWD26.8 (Thanakkan and Selvaraj 2020)
DI68.0 (Thanakkan and Selvaraj 2020)
(Parthasarathi et al. 2019)
TelanganaSRI + AWD23.4(Nirmala et al. 2021) Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 55
Annexure III: Emissions in Sustainable Rice Systems
StateAlternative
Cultivation Strategy
Emission Reduction
Potential from
Literature (%)
References
Uttar Pradesh DSR + AWD89.5 (Pathak and Aggarwal 2012)
SRI + AWD64.0
AWD29.1
DI100
West Bengal DSR + AWD89.7 (Pathak and Aggarwal 2012)
SRI + AWD71.5
AWD29.5
DI100
Note: DSR - Direct Seeded Rice
SRI - System of Rice Intensification;
AWD - Alternate Wetting and Drying;
DI: Drip Irrigation Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 56
Annexure IV:
Energy Demand Projections
of Irrigation Pumping
Steps in Figure 2.1 are explained below:
1. Crop demand projections: Demand projections for this study are drawn from NITI Aayog’s
Working Group Report on Crop Husbandry, Agricultural Inputs, and Demand–Supply, which
provides estimates up to 2047. These projections were subsequently extended to 2070 in
collaboration with the scientists and experts from Indian Council of Agricultural Research
(ICAR) The crops considered are rice, wheat, maize, pulses, oilseeds, sugarcane, and cotton.
Together, these account for the majority of India’s irrigated land and water consumption.
2. Water demand estimation: The water demand for pumping is estimated from crop
production requirements. Crop production (in million tonnes) is translated into crop area
using projected yields, with a distinction drawn between rainfed and irrigated shares using
crop specific irrigation intensities. The table below (Table Annex. IV.1) presents the share
of each major crop’s area that was irrigated in 2020.
Table Annex. IV.1: Crop-wise share of irrigation as in 2020- Baseline
CropIrrigated Share (2020)
Rice60.9%
Wheat94.6%
Maize36.7%
Arhar (pigeonpea)4.2%
Gram (chickpea)42.8%
Groundnut29.1%
Rapeseed & Mustard79.9%
Sugarcane96.0%
Cotton35.7%
Multiplying each crop’s irrigated share by its water productivity coefficient (kg crop per m
3
)
yields the total volume of irrigation water demand (Sharma et al, 2018).
Not all irrigation water is lifted by pumps – a portion is supplied by gravity flow in canal
command areas and by tank irrigation. A pumping share factor is applied to reflect the fraction
of irrigation water that requires energy for pumping. Currently, about 60–70% of India’s irrigated Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 57
Annexure IV: Energy Demand Projections of Irrigation Pumping
area is served by groundwater (wells and tube wells) or other lift systems, which implies that
roughly two-thirds of irrigation water is pumped (The remainder from canals may involve minor
lifting at field level, but is largely gravity-fed). A baseline value of 75% is used as the share of
irrigation water that is pumped (MoAFW, 2022). For future scenarios, this factor can change
based on investments in canal infrastructure or micro-irrigation (for instance, expanded surface
irrigation could reduce reliance on pumps, whereas deeper groundwater use could increase
energy needed per unit water).
Energy demand estimations: Energy demand for irrigation is calculated by converting pump-
dependent water requirement into useful energy and then into final energy, accounting for
operating conditions and technology parameters.
1. Pump discharge and utilisation: Based on the 5th Minor Irrigation Census (MIC)
in 2017 (MoJS, 2024) and supporting field studies, an average irrigation pump is
considered to be rated as 5–6 Horsepower (HP), with a discharge rate of 20 m³/h
under a nominal head of 25 metres. Utilisation differs sharply by technology: electric
and solar pumps operate for 750 hours annually, while diesel pumps operate for
250 hours due to higher fuel costs. Using these assumptions, the model reproduces
a base-year pump stock of 20 million electric and 10 million diesel units, consistent
with estimates in MIC 2017.
2. Dynamic head: The average pumping head in 2019 was 28 m, and is a representative
value across shallow and deep groundwater systems reported in MIC 2017 (MoJS,
2024). This is projected to rise to 50 m by 2070 as groundwater tables decline.
3. Pump efficiency: Overall pump–motor efficiency is assumed to be 30% for diesel
and 36% for electric pumps in 2020, improving gradually to 45–55% by 2070 with
technology advances and better maintenance (EMC, 2018). Solar pumps use high-
efficiency electric motors and are assumed to perform comparably to grid-electric
pumps.
4. Energy calculation: Useful energy required for pumping is estimated as:
Useful Energy Demand = E
u
=N
p
× H
p
× A
h
Where,
Ground Water Demand
N
p
= Number of active pumps =
_____________________________________________
Average Discharge Rate
*
Functioning Hours per Year
H
p
= Horsepower of lifting device, assumed to be 5 based on MIC 2017.
A
h
= Annual Hours Usage, assumption based on MIC, IWMI, and consultations.
EU
Final Energy Demand E
f
=
___________, where η is overall efficiency of the pump
n
Modelled outputs are validated against observed consumption: 207 TWh of electricity in
agriculture in 2019-20 (CEA 2024) and about 6-8 MMT of diesel annually (Petroleum Planning
and Analysis Cell (PPAC)). The base-year estimates are within a narrow margin of these reported
values, confirming the robustness of the approach. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 58
Annexure V:
Energy Demand Projections
of Land Preparation
Steps in Figure 2.3 are explained below:
1. Mechanised land preparation area: The starting point is the gross cropped area (GCA) as
per the cropping intensity scenario for Current Policy Scenario in Table 2.4. The extent of
mechanisation determines what share of this area is prepared using machines rather than
manual or animal power. The current level of mechanisation in India is 47%. For the base
year 2019, this translates to 93 Mha prepared by tractors or tillers.
2. Methods of land preparation: Mechanised land preparation in India is dominated by tractors,
but power tillers also play a critical role, especially in smallholder farms. While tractors
are known to form the majority of farm power in absolute numbers, exact and recent
data on the shares of tractors and tillers in mechanised farming has not been consistently
documented. That said, the share of mechanical and electrical power in farm power has
risen markedly from just 7% in 1960–61 to over 87% in 2009–10, replacing animate power
sources like animals and humans (Tiwari et al, 2019). Mechanisation trends suggest that
tractors dominate field-level tillage, yet power tillers remain relevant for small, fragmented
farms. Over 85% of Indian farmers are small or marginal holders (owning under 2 hectares
of land), making full-sized tractors expensive or logistically cumbersome. Power tillers are
more cost- efficient, manoeuvrable, and versatile for such small plots, particularly in paddy
and horticultural systems (Rath et al, 2024).
Given the lack of recent national data on the share of tractors and tillers, this module retains
the conservative assumption that for every two power tillers there is one tractor in terms of
land coverage capacity (the hours required to prepare an equivalent area of land), a conversion
metric commonly used in established technical analyses.
Estimating energy demand: The energy requirement for land preparation is estimated by first
determining the work effort—measured as operating hours per hectare, and the corresponding
fuel consumption rate of each implement type. Literature and field studies provide benchmarks
for both hours per hectare and energy per hour, with tractors generally requiring fewer hours
per hectare but consuming more fuel per hour, and power tillers requiring longer operating
times at lower hourly fuel rates (20 hours compared to 8 hours). However, energy intensity
per hectare is not fixed, it can vary substantially depending on soil type, moisture conditions,
implement depth, and operator skill, which influence the number of passes required and the
effective load on the engine. These variations highlight the need for more detailed, crop- and
region-specific studies to capture the true range of energy use across India’s diverse farming
systems. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 59
Annexure V: Energy Demand Projections of Land Preparation
On the basis of these assumptions, energy intensity per-hectare is obtained for tractors and
tillers. These figures are then applied to their respective areas. The results are aggregated to
arrive at total energy demand for land preparation.
E = GCA * Mechanisation (%) * ∑ (A
*
I
v
)
v
Where, A is the area prepared by implement type, I is the energy intensity per hectare, GCA
is the Gross Cropped Area.
This formulation captures both differences in implement efficiency and variations in operating
practices. In the base year, applying these intensities to the mechanized area yields diesel use
consistent with national estimates of agricultural fuel consumption. This methodology is limited
to tractors and power tillers for estimating energy demand. It does not explicitly account for
other forms of mechanisation such as laser land levellers, seed drills, or the emerging role of
drones and automated machinery in land preparation and field management. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 60
1. Strategic opportunities for diversifying areas away from rice to nutri-
cereals in India
Classifying states: Potential for diversification & Potential for rice expansion
The following figure presents an analytical classification of Indian states based on their current
and decadal trends of area, production, and yield (APY) of rice cultivation. To assess their
potential for diversification away from rice, Indian states have been plotted based on two
composite indicators on area and yield, respectively in Figure Annex VI.1.
How to read the graph:
1. X axis–Area composite score = rice area as (%) of the state’s GCA + rice area growth rate
(CAGR) from 2014 to 2023.
2. Y axis–Yield composite score = current rice yield in the states and yield CAGR from 2014
to 2023.
3. Size of the bubble: % of the State’s contribution to India’s total production.
4. Orange states: States where short-term diversification away from rice is feasible due to
sufficient production
of nutri-cereals. This means that public procurement channels in the
states can replace rice with nutri-cereals without trade-offs.
Area composite score (Rice area as % Gross cropped area of the state and state rice area change CAGR)
0.12
01
00.8
00.6
00.4
00.2
00
0 0.1 0.20.40.60.810.30.50.70.91.1 1.2
Yield (State rice yield change - CAGR and rice yield in state)
Nutri-cereals production surplus states
Quadrant II
India Rice area composite score line
India yield composite score line
Quadrant I
Quadrant IV
Quadrant III
KAKA
KLKL
MHMH
GJGJ
RJRJ
UPUP
APAP
HRHR
MPMP
BHBH
TNTN
WBWB
CGCGTLTL
ODOD
JHJH
ASAS
PBPB
JKJK
01
Figure Annex VI.1: State distribution map based on rice area and yield trends (Authors’ analysis)
Annexure VI:
Scenario Rationale Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 61
Annexure VI: Scenario Rationale
Quadrant I: Taking into account both the current levels and growth rates of rice area and yield,
states like Punjab, Haryana, and Telangana exhibit potential for natural diversification away from
rice in the future. Long-term sustainability of rice production remains a concern for these states,
as biophysical constraints such as groundwater depletion and soil health degradation are likely
to create pressure. Some diversification away from rice in these states is expected to occur
gradually, driven more by ecological necessity than immediate economic incentives.
Quadrant II: States in these quadrants show varied potentials for diversification and rice area
expansion. The trajectory of diversification in states like Andhra Pradesh and Jammu and Kashmir
is defined by declining trends in area under rice cultivation, suggesting natural diversification is
occurring. In contrast, states like Uttar Pradesh, Rajasthan, and Karnataka show positive trends
in rice expansion with smaller area under cultivation and higher yields. These states, unlike
the previous two states, remain at risk of future rice expansion, particularly if irrigation access
improves.
Quadrant III: These states currently have low rice cultivation area and yield, but are experiencing
positive growth rates in both, indicating a potential risk of future rice expansion. Kerala is the
only exception, showing a negative growth rate in both area and yield.
Quadrant IV: This group includes states where yields remain low and rice area expansion exhibits
varying trends. These states present a strong case for diversifying some areas away from rice.
Diversification would offer considerable economic and resilience benefits by shifting to crops
better suited to local conditions. This approach aligns with the primary objectives and outcomes
intended under the recently announced PM Dhan Dhanya Krish Yojana (PIB, 2025 (a)).
While states have been identified for diversification away from rice, it is essential to adopt
a phased approach that accounts for the value chain readiness of alternative crops. In the
following suggestive roadmap in Figure Annex VI.2, we focus on diversification to nutri-cereals,
which received strong support from the GoI in recent years.
Suggestive Roadmap: Supporting Diversification through procurement by Food
Welfare Programmes
CONSUMPTION DIVERSIFICATION
Diversify consumption in states where nutri-cereals are
widely produced and consumed
PRODUCTION DIVERSIFICATION
Diversify production in high potential Quadrant IV states
RAMP UP
Achieve full-scale value chain diversification
6 States
HR, KA, MP, MH, RJ, UP
3 States
AS, JH, OD
All 15 States
with diversified procurement
Leveraging PDS, PM POSHAN, POSHAN 2.0
to mainstream diverse crops, improve public health particularly for states with high malnutrition, and shift farmer incentives
EXPANSION
Diversification expands to Quadrant I, II, III states
YEAR
1 & 2
YEAR 5 & 6
YEAR 3 & 4
YEAR 10
Figure Annex VI.2: Crop diversification opportunities from rice to nutri-cereals for India Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 62
Annexure VI: Scenario Rationale
2. Natural farming: A Scalable Agroecological Pathway for India
Natural farming (NF) presents a promising alternative to input-intensive agriculture, particularly
in ecologically fragile and economically vulnerable regions. To scale NF in a way that unlocks its
potential to enhance incomes and resilience of farms while ensuring nutrition security, a phased
approach with strategic focus on specific geographies and communities and leveraging existing
institutional and social capital is essential.
Scaling Natural Farming in rainfed areas for more equitable and sustainable
agricultural growth:
Rainfed agriculture covers 51% of India’s Net Sown Area (NSA) contributes 40% of food
production, and is characterised by low productivity, low input use, and monsoon-dependent
yield volatility (MoAFW, 2024). These rainfed areas face acute climate risks while supporting
81% of the rural poor, including marginal, tribal, and smallholder farmers (Gopinath et al., 2013).
Natural Farming (NF) offers a low-risk, high-reward opportunity for these regions. Transitioning
to Natural Farming (NF) can enhance productivity and help raise farmers’ yields and profitability.
Since a significant proportion of these farmers consume their produce, Natural Farming (NF)
would also appeal to them given its focus on practices that promote health and nutrition, such
as crop diversification (Annex VI.3). It would also help bring stability and resilience to rainfed
farm systems by fostering soil health and practices that focus on climate resilience. The National
Mission on Natural Farming (NMNF) also prioritises rainfed regions for Natural Farming (NF)
scale-up.
To provide chemical-free food for own
family, but will sell chemically farmed
produce to others
As using chemicals for
food production is bad
As produce fetches a higher premium
To improve soil quality
0%40%80%20%60%100%
51%
54%
62%
84%
Figure AnnexVI.3: Motivations of farmers to adopt Natural Farming
Source: Issue Brief - “What drives Natural Farming adoption in India?” Evidence from Farmer Behaviour and Practise
Trends, CEEW (to be published)
Green revolution regions may also hold opportunity hotspots for natural farming,
based on targeted evidence:
India’s Green Revolution (GR) regions, like Punjab, are now grappling with deep-rooted ecological
imbalances. Years of intensive input use, incentivised by input subsidies, have led to declining
soil fertility, falling groundwater tables, and public health concerns linked to excessive pesticide
use. In this context, Natural Farming (NF) offers an opportunity for ecological restoration and Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 63
Annexure VI: Scenario Rationale
enhancing long-term agricultural resilience. However, given that farmers in these regions are
typically risk-averse and yield-focused, the regional hotspots with extreme ecological stress,
putting farm productivity and incomes at high risk of decline, may only offer a window for
Natural Farming (NF) adoption in the short term. Building compelling proofs of concept in
Green Revolution regions with a focused strategy centred on evidence generation and localised
demonstrations would expand the Natural Farming (NF) opportunity in Green Revolution
regions towards the mid-term. Natural Farming (NF) programmes like National Mission on
Natural Farming (NMNF) are also building on similar approaches, targeting the creation of
Natural Farming (NF) clusters in Green Revolution regions with high input use and proximity
to major rivers (MoAFW, 2024).
Field evidence from the APCNF programme suggests that APCNF GPs in traditional Green
Revolution regions such as Godavari and Krishna are witnessing high uptake of natural
biostimulants in portions of their land as they transition into chemical farming with farmers
motivated by health and soil concerns as indicated in Annex VI.4 (Issue Brief - “What drives
Natural Farming adoption in India?” Evidence from Farmer Behaviour and Practise Trends,
CEEW (to be published) ).
Southern Zone
Scarce rainfall zone
North Coastal Zone
Krishna Zone
High Altitude Zone
Godavari Zone
0%40%80%20%60%100%
None Biostimulants only Both biostimulants & fertilisers Fertilisers only
Rabi 2022-23
Figure AnnexVI.4: Biostimulant adoption in different agro-climatic zones in Andhra Pradesh
By promoting diverse, indigenous crops, NF supports prosumption (production consumed in-
house) and better household diets. Aligning NF with nutrition-focused programmes like mid-
day meals, PDS, and ICDS can amplify its adoption and impact on both public health and local
food systems.
The deep reach of SHGS, CRPs, and FPOs across rural India can scale natural
farming through trusted, community-rooted institutions.
Institutionalisation at the community level has emerged as a critical success factor for scaling
sustainable agriculture programmes, with village-level championship models such as Community
Resource Persons playing a particularly important role. (CEEW, 2023). The APCNF initiative Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 64
Annexure VI: Scenario Rationale
exemplifies this approach, leveraging Community Resource Persons (CRPs) to scale Natural
Farming to over one million farmers across 26 districts in Andhra Pradesh in just nine years. This
demonstrates the potential for decentralised, community-driven models to mainstream natural
farming. Importantly, the institutional infrastructure necessary for such initiatives already exists.
India has over 8.3 million Self-Help Groups (SHGs), many integrated into state and National
Rural Livelihood Missions (NRLM). Additionally, networks such as Krishi Sakhis and over 8,000
Farmer-Producer Organisations (FPOs) offer robust platforms for peer-led extension services
(PIB, 2024).
Moreover, these grassroots institutions are particularly active in areas dominated by rainfed
farming and smallholder agriculture, making these regions a clear opportunity hotspot for
natural farming adoption. For instance, in Odisha, Mission Shakti’s SHG network plays a
significant role in districts such as Kandhamal and Rayagada, which face high agroecological
vulnerability yet have a long-standing tradition of ecological farming. In Chhattisgarh’s Bastar
region, SHG federations and Krishi Sakhis are central to farmer engagement, supported by
both state and non-state actors promoting natural farming as a low-cost, climate-resilient
alternative. Decentralised extension systems anchored in CRPs, SHGs, and FPOs not only build
trust and adapt the interventions to local realities but also reduce the transaction costs of
last-mile delivery, making them highly effective in driving behavioural change and embedding
sustainable practices across India’s diverse agricultural landscapes. REFERENCES Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 66
References
1. Agarwal, N., Apoorve, K., & Wal, A. (2023). How to design scalable and sustainable
programmes: Framework for India’s sustainable agriculture initiatives. Council on Energy,
Environment and Water. https://www.ceew.in/sites/default/files/how-can-india-design-
scalable-and-sustainable-programmes-for-sustainable-agriculture- initiatives.pdf
2. Agriculture Statistics. (2024). Agricultural statistics at a glance 2023. Government of
India, Ministry of Agriculture & Farmers Welfare, Department of Agriculture & Farmers
Welfare. https://desagri.gov.in/wp-content/uploads/2024/09/Agricultural- Statistics-at-a-
Glance-2023.pdf
3. APCNF. (n.d.). APCNF – Towards farmer prosperity, better citizen health, climate resilience
and cooling of the planet. https://apcnf.in/global/
4. Barman, A., Saha, P., Patel, S., & Bera, A. (2022). Crop diversification: An effective strategy
for sustainable agriculture development. In V. S. Meena, M. Choudhary, R. P. Yadav, & S. K.
Meena (Eds.), Sustainable crop production: Recent advances (pp. 1–17). IntechOpen. https://
doi.org/10.5772/intechopen.102635
5. Bhuvaneshwari, S., Hettiarachchi, H., & Meegoda, J. N. (2019). Crop residue burning in India:
Policy challenges and potential solutions. International Journal of Environmental Research
and Public Health, 16(5). https://doi.org/10.3390/ ijerph16050832.
6. Birthal, P. S., Khan, M. T., Negi, D. S., & Agarwal, S. (2014). Impact of climate change on
yields of major food crops in India: Implications for food security. Agricultural Economics
Research Review, 27. https://doi.org/10.5958/0974-0279.2014.00019.6
7. Central Electricity Authority-CEA. (2024). All India electricity statistics: General review 2024
(containing data for the year 2022–23). Ministry of Power, Government of India. https://cea.
nic.in/ general-review-report/?lang=en
8. Central Electricity Authority-CEA. (2025). Updated growth report 2025. https://cea.nic.in/
wp-content/uploads/general/2025/Updated_GR_2025_merged_new.pdf
9. CEEW. (2021). Policy Study on Sustainable Agriculture. https://www.ceew.in/sites/ default/
files/ceew-policy-study-on-sustainable-agriculture-india_0.pdf
10. CEEW–IWMI. (2023). Evaluating policy coherence in food, land, and water systems:
Evidence from India. Colombo, Sri Lanka: International Water Management Institute (IWMI).
CGIAR Initiative on National Policies and Strategies. 124p. https://www.ceew.in/publications/
evaluating-policy-coherence-in-food-land-and- water-systems-of-india
11. Chand, R. (2025). Reimagining agriculture for growth, poverty, nutrition, and sustainability.
Journal of the International Association of Agricultural Economists, 1(March). https://doi.
org/10.1111/agec.70015. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 67
References
12. Chhabra, A., Manjunath, K. R., & Panigrahy, S. (2009). Assessing the role of Indian livestock
in climate change. ISPRS Archives, XXXVIII-8/W3, 359–364. https:// www.researchgate.net/
publication/271702897
13. Chuphal, D. S., Kushwaha, A. P., Aadhar, S., & Mishra, V. (2024). Drought atlas of India,
1901–2020. Scientific Data, 11(1), 7. https://doi.org/10.1038/s41597-023- 02856-y
14. DAHD. (2005). 17th Indian Livestock Census: All-India Summary Report. Ministry of
Fisheries, Animal Husbandry & Dairying, Government of India. https://dahd.gov. in/sites/
default/files/2025-05/17thIndianLivestockCensusAll-IndiaSummaryReport. pdf
15. DAHD. (2007). 18th Livestock Census: All India Report. Ministry of Agriculture and Farmers
Welfare, Government of India. https://iss.icar.gov.in/Livestock_ Documents/18th_Livestock_
Census.pdf.
16. DAHD. (2018). Basic Animal Husbandry and Fisheries Statistics 2018. Ministry of Fisheries,
Animal Husbandry & Dairying, Government of India. https://iss.icar.gov. in/.
17. DADH. (2019). 20th Livestock Census: All India Report. Ministry of Fisheries, Animal
Husbandry & Dairying, Government of India. https://ruralindiaonline.org/ en/library/
resource/20th-livestock-census-2019-all-india-report/.
18. DAHD. (2023). Basic Animal Husbandry Statistics 2023. Ministry of Fisheries, Animal
Husbandry & Dairying, Government of India. https://dahd.gov.in/sites/ default/files/2024-10/
BasicAnimalHusbandryStatistics2023.pdf.
19. Das, P., Singh, V., Stevanović, M., Kumar Jha, C., Bodirsky, B. L., Beier, F., Humpenöder, F., Leip,
D., Chen, D. M. C., Crawford, M., von Jeetzen, P., Molina Bacca, E., Soergel, B., Springmann, M.,
Dietrich, J. P., Popp, A., Kumar Gosh, R., & Lotze-Campen, H. (2023). A healthy, sustainable,
and inclusive food system transformation for India. https://foodsystemeconomics.org/wp-
content/uploads/Das-et-al.-2023.pdf
20. Dhruw, U. K., Roy, D. K., & Verma, P. D. (2024). India’s growth in agricultural mechanisation
during last decades. International Journal of Advanced Biochemistry Research, 8(3 Suppl
C), 178–181. https://doi.org/10.33545/26174693.2024. v8.i3Sc.715
21. EMC. (2018). Study of agriculture pump sets in the State of Kerala: Detailed project report.
Energy Management Centre–Kerala https://keralaenergy.gov.in/files/Energy_ Efficiency_
study_of_Agriculture_Pump_sets.pdf
22. FAO. (2021). The state of the world’s land and water resources for food and agriculture –
Systems at breaking point: Synthesis report 2021. Food and Agriculture Organization of
the United Nations. https://doi.org/10.4060/cb7654en
23. FAO. (2024) Food Balance Sheets. Retrieved April 24, 2025. https://www.fao.org/ faostat/
en/#data/FBS.
24. FAO. (2025). Glossary. Retrieved April 24, 2025. https://openknowledge.fao.org/ server/
api/core/bitstreams/317db554-c763-4654-a0d3-24a8488bbc3a/content/status- women-
agrifood-systems-2023/glossary.html
25. Fertiliser Association of India (FAI). (2024). Annual Review of Fertiliser Production and
Consumption 2023–24. https://www.faidelhi.org/member/AR-Full-Rep.pdf.
26. Gogoi, N., Baruah, K. K., & Gupta, P. K. (2008). Selection of rice genotypes for lower
methane emission. Agronomy for Sustainable Development, 28(2), 181–186. https://doi.
org/10.1051/agro:2007052 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 68
References
27. Gómez-Casanovas, N., Mwebaze, P., Khanna, M., Branham, B., Time, A., DeLucia, E. H.,
Bernacchi, C. J., Knapp, A. K., Hoque, M. J., Du, X., Blanc-Betés, E., Barron- Gafford, G. A.,
Peng, B., Guan, K., Macknick, J., Miao, R., & Miljkovic, N. (2023). Knowns, uncertainties, and
challenges in agrivoltaics to sustainably intensify energy and food production. Cell Reports
Physical Science, 4(8), Article 101518. https:// doi.org/10.1016/j.xcrp.2023.101518
28. Gopinath, K. A., Dixit, S., Chary, G. R., Srinivasarao, Ch., Osman, M., Raju, B. M. K., Ramana,
D. B. V., Venkatesh, G., Grover, M., Maheswari, M., & Venkateswarlu,B. (2013). Improving the
rainfed farming systems of small and marginal farmers in Anantapur and Adilabad districts
of Andhra Pradesh. Central Research Institute for Dryland Agriculture, Hyderabad, Andhra
Pradesh. https://www.researchgate.net/ publication/259659509_Improving_the_Rainfed_
Farming_Systems_of_Small_and_ Marginal_Farmers_in_Anantapur_and_Adilabad_
Districts_of_Andhra_Pradesh
29. Gorh, D., & Baruah, K. K. (2019). Estimation of methane and nitrous oxide emission from
wetland rice paddies with reference to global warming potential. Environmental Science
and Pollution Research, 26(12), 11522–11532. https://doi.org/10.1007/ s11356-019-05026-z
30. Government of India, Ministry of Rural Development. (n.d.). SHG count. https:// nrlm.gov.
in/shgReport.do?methodName=showIntensiveStateWiseReport
31. Gupta, N., Pradhan, S., Jain, A., & Patel, N. (2021). Sustainable agriculture in India 2021:
What we know and how to scale up. Council on Energy, Environment and Water (CEEW).
https://www.ceew.in/sites/default/files/CEEW-FOLU-Sustainable- Agriculture-in-India-2021-
20Apr21.pdf
32. IPCC. (2006). 2006 IPCC guidelines for national greenhouse gas inventories: Volume 1:
General guidance and reporting. Task Force on National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change. https://www.ipcc-nggip. iges.or.jp/
public/2006gl/index.html
33. IPCC. (2019). “Interlinkages between Desertification, Land Degradation, Food Security
and Greenhouse Gas Fluxes: Synergies, Trade-offs and Integrated Response Options.” In
Climate Change and Land: an IPCC Special Report on Climate Change, Desertification,
Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas
Fluxes in Terrestrial Ecosystems. N.p.: Intergovernmental Panel on Climate Change. https://
www.ipcc.ch/site/assets/uploads/sites/4/2022/11/ SRCCL_Chapter_6.pdf?utm_source .
34. IPCC. (2014). The IPCC Fifth Assessment Report. https://www.ipcc.ch/site/assets/
uploads/2018/04/ipcc_ar5_leaflet.pdf.
35. Indian Dairy Association. (2012). 19th Livestock Census – 2012: All India Report. https://
indiandairyassociation.org/pdf/info/19th-Livestock-Census-2012.pdf
36. Jha, C. K., Singh, V., Stevanović, M., Dietrich, J. P., Mosnier, A., Weindl, I., Popp, A., Schmidt-
Traub, G., Ghosh, R. K., & Lotze-Campen, H. (2022). The role of food and land use systems
in achieving India’s sustainability targets. Environmental Research Letters, 17(7), 074022.
https://doi.org/10.1088/1748-9326/ac788a
37. John, S., & Babu, S. (2021). Lessons from the aftermaths of the Green Revolution on food
system sustainability in India. Frontiers in Sustainable Food Systems, 5, 644559. https://doi.
org/10.3389/fsufs.2021.644559 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 69
References
38. Kumar, R., Kumar, S., Yashavanth, B. S., Meena, P. C., Indoria, A. K., Kundu, S., & Manjunath,
M. (2020). Adoption of natural farming and its effect on crop yield and farmers’ livelihood
in India (ICAR-National Academy of Agricultural Research Management, Hyderabad, India).
https://www.niti.gov.in/sites/default/files/2021-03/NaturalFarmingProjectReport-ICAR-
NAARM.pdf
39. Lewis, W. A. (1954). Economic Development with Unlimited Supplies of Labour. University
of Texas. https://la.utexas.edu/users/hcleaver/368/368lewistable.pdf.
40. Meghalaya State Organic and Natural farming Policy 2023. https://investmeghalaya. gov.in/
resources/homePage/17/megeodb/policies/farming2023.pdf?utm
41. Mishra, G. K., & Tiwari, R. P. (2014). Infertility management protocols for dairy animals. Indian
Dairyman. https://www.researchgate.net/profile/Girish-Mishra-5/publication/322124388_
Infertility_Management_of_Dairy_Animals/links/5a463187a6fdcce1971a9c4d/Infertility-
Management-of-Dairy-Animals.pdf
42. MoAFW. (2017). Doubling Farmers’ Income Report. In Doubling Farmers’ Income–Volume I
March of Agriculture Since Independence and Growth Trends. Ministry of Agriculture and
Farmers’ Welfare. https://agriwelfare.gov.in/Documents/ DFIpercent20Volume%201.pdf.
43. MoAFW. (2021). All India Report on Input Survey 2016-17. Agriculture Census. https://
agcensus.da.gov.in/document/is2016/air_is_16-17_210121-final_220221.pdf.
44. MoAFW. (2022). Agricultural statistics at a glance 2022. Directorate of Economics and
Statistics, Department of Agriculture and Farmers Welfare, Government of India. https://
desagri.gov.in/wp-content/uploads/2023/05/Agricultural-Statistics-at- a-Glance-2022.pdf
45. MoAFW. (2024). National Mission on Natural Farming (NMNF) Operational Guidelines.
46. https://agriwelfare.gov.in/Documents/HomeWhatsNew/GuidelineofNMNF_
FinalApproved_27122024.pdf
47. MoAFW. (2024). Rainfed Farming System. Department of Agriculture and Farmers Welfare,
Government of India. https://agriwelfare.gov.in/en/RainfedDiv
48. MoEFCC. (2004). India’s Initial National Communication to the United Nations Framework
Convention on Climate Change. Ministry of Environment, Forest and Climate Change,
Government of India. https://unfccc.int/resource/docs/natc/indnc1. pdf
49. MoEFCC. (2018). India: Second Biennial Update Report to the United Nations Framework
Convention on Climate Change. Ministry of Environment, Forest and Climate Change,
Government of India. https://unfccc.int/sites/default/files/resource/ INDIA%20SECOND%20
BUR%202018.pdf
50. MoEFCC. (2021). India: Third Biennial Update Report to the United Nations Framework
Convention on Climate Change. Ministry of Environment, Forest and Climate Change,
Government of India. https://unfccc.int/sites/default/files/resource/ INDIA_%20BUR-
3_20.02.2021_High.pdf
51. MoEFCC. (2022). India’s Long-Term Low-Carbon Development Strategy. Ministry of
Environment, Forest and Climate Change, Government of India. https://moef.gov. in/
uploads/2022/11/Indias-LT-LEDS.pdf
52. MoEFCC. (2023). India: Third National Communication and Initial Adaptation Communication
to the United Nations Framework Convention on Climate Change. Ministry of Environment,
Forest and Climate Change, Government of India. https:// unfccc.int/sites/default/files/
resource/India-TNC-IAC.pdf Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 70
References
53. MoEFCC. (2024). India Fourth Biennial Update Report. United Nations Framework
Convention on Climate Change. https://unfccc.int/sites/default/files/resource/ India%20
BUR-4.pdf.
54. MoF. (2024). Economic Survey of India 2023-24. Government of India. Ministry of
Finance, Department of Economic Affairs. India Budget. https://www.indiabudget. gov.in/
economicsurvey/doc/eschapter/echap01.pdf.
55. MoF. (2025). Economic Survey of India 2024-25. Government of India. Ministry of
Finance, Department of Economic Affairs. India Budget. https://www.indiabudget. gov.in/
economicsurvey/doc/echapter.pdf.
56. Mohanty, S., Swain, C. K., Sethi, S. K., Dalai, P. C., Bhattacharyya, P., Kumar, A., Tripathi, R.,
Shahid, M., Panda, B. B., Kumar, U., Lal, B., Gautam, P., Munda, S., & Nayak, A. K. (2017).
Crop establishment and nitrogen management affect greenhouse gas emission and
biological activity in tropical rice production. Ecological Engineering, 104, 80–98. https://
doi.org/10.1016/j.ecoleng.2017.03.014
57. MoJS. (2024). 5th Minor Irrigation Census (MIC). Department of Water Resources, River
Development and Ganga Rejuvenation, Ministry of Jal Shakti, Government of India. https://
mowr.nic.in/irrigationcensus/
58. MPI. (2017). New Zealand Agriculture: A Policy Perspective (Document No. 27282).
Ministry for Primary Industries, Wellington, New Zealand. https://www.mpi.govt.nz/
dmsdocument/27282-New-Zealand-Agriculture
59. NAAS. (2013). Livestock Infertility and Its Management (Policy Paper No. 59). National
Academy of Agricultural Sciences, New Delhi. https://naas.org.in/Policy%20 Papers/
policy%2059.pdf
60. Nirmala, B., Tuti, M. D., Kumar, R. M., Waris, A., Muthuraman, P., Parmar, B., & Singh, T. V.
(2021). Integrated assessment of system of rice intensification vs. conventional method of
transplanting for economic benefit, energy efficiency and lower global warming potential
in India. Agroecology and Sustainable Food Systems, 45(4), 475–495. https://doi.org/10.10
80/21683565.2020.1868648
61. NITI Aayog. (2022). A New Paradigm for Indian Agriculture: From Agroindustry to
Agroecology. Government of India. https://www.niti.gov.in/sites/default/files/2023-03/A-
New-Paradigm-for-Indian-Agriculture-from-Agroindustry-to-Agroecology. pdf.
62. NITI Aayog. (2024). NITI Aayog Working Group Report on Crop Husbandry, Agricultural
Inputs, Demand and Supply 2024. Retrieved January 30, 2025, from https://www.niti.
gov.in/sites/default/files/2024-02/Working%20Group%20 Report%20on%20Demand%20
%26%20Supply%20Final_V9.pdf .
63. Odisha Government (Mission Shakti). (2022). Mission Shakti: A Silent Revolution [Coffee-
table book]. Women & Child Development and Mission Shakti Department, Government of
Odisha. https://missionshakti.odisha.gov.in/sites/default/ files/2022-03/Coffee-table-book.
64. OECD. (2019). Enhancing Climate Change Mitigation through Agriculture. OECD Publishing,
Paris. https://doi.org/10.1787/e9a79226-en
65. Parthasarathi, T., Vanitha, K., Mohandass, S., & Vered, E. (2019). Mitigation of methane
gas emission in rice by drip irrigation. F1000Research. https://doi. org/10.12688/
f1000research.20945.1 Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 71
References
66. Pathak, H. (2015). Greenhouse gas emission from Indian agriculture: Trends, drivers and
mitigation strategies. Proceedings of the Indian National Science Academy, 81(5), 1133–1149.
https://doi.org/10.16943/ptinsa/2015/v81i5/48333
67. Patange, O., Purohit, P., Avashia, V., Klimont, Z., & Garg, A. (2024). Mitigation of non-CO2
greenhouse gases from Indian agriculture sector. Environmental Research Letters, 9. https://
doi.org/10.1088/1748-9326/ad4e4e
68. PIB. (2011). Foodgrain Production Reaches Record 241.6 Million Tonnes. Press Information
Bureau. https://www.pib.gov.in/newsite/PrintRelease.aspx?relid=75978
69. PIB. (2019). 4th Advance Estimates of production of major crops for 2018-19. https://www.
pib.gov.in/Pressreleaseshare.aspx?PRID=1582362
70. PIB. (2021). Productivity of Dairy Animals. Press Information Bureau. https://pib.gov.
in/PressReleaseIframePage.aspx?PRID=1707187#:~:text=As%20per%20Integrated%20
Sample%20Survey,(as%20per%20FAO%20Statistics).
71. PIB. (2022a). Milk Production in India: The Journey of India’s Dairy Sector. N.p.: Press
Information Bureau. https://pib.gov.in/FeaturesDeatils. aspx?NoteId=151137®=3&lang=1.
72. PIB. (2022b). Increased foodgrain production in India: Six-fold rise in foodgrain production
since independence. Press Information Bureau, Government of India. https://static.pib.gov.
in/WriteReadData/specificdocs/documents/2022/jul/ doc202272874801.pdf
73. PIB. (2022c). Cabinet approves India’s updated nationally determined contribution to
be communicated to the United Nations Framework Convention on Climate Change.
Press Information Bureau, Government of India. https://pib.gov.in/PressReleasePage.
aspx?PRID=1847813
74. PIB. (2023). Press release. Government of India. https://pib.gov.in/PressReleseDetailm.
aspx?PRID=1939473®=3&lang=1
75. PIB. (2024). 8,875 FPOs have been registered across the country. Press Information Bureau,
Government of India. https://www.pib.gov.in/PressReleaseIframePage. aspx?PRID=2040845
76. PIB. (2025a). India submits its 4th Biennial Update Report to the United Nations Framework
Convention on Climate Change. Press Information Bureau, Government of India. https://
www.pib.gov.in/PressReleasePage.aspx?PRID=2089589
77. PIB. (2025b). India’s renewable revolution: Building clean power, made in India [Factsheet
No. 149232]. Press Information Bureau, Government of India. https:// www.pib.gov.in/
FactsheetDetails.aspx?Id=149232
78. PMO. (2023). PM launches ‘Viksit Bharat @2047: Voice of Youth’. Prime Minister’s Office,
Government of India. https://www.pmindia.gov.in/en/news_updates/pm- launches-viksit-
bharat-2047-voice-of-youth/
79. Prabhu, S., & Chitale, V. (2024). Decoding India’s changing monsoon patterns – A tehsil-level
assessment. Council on Energy, Environment and Water. https://www. ceew.in/sites/default/
files/decoding-how-climate-change-is-changing-monsoon- rainfall-patterns-in-india.pdf
80. Rajasthan Organic Farming Policy. (2017). Rajasthan organic farming policy 2017. Department
of Agriculture, Government of Rajasthan. https://cuts-cart.org/pdf/ Rajasthan_Organic_
farming_Policy-2017.pdf
81. Ramesh, T., & Selvaraj, R. (2020). Evaluation of rice cultivation systems for greenhouse gas
emissions and productivity. Tamil Nadu Agricultural University. https://www. researchgate. Scenarios Towards Viksit Bharat and Net Zero - Sectoral Insights: Agriculture 72
References
net/publication/342347798_Evaluation_of_rice_cultivation_systems_ for_greenhouse_
gases_emission_and_productivity
82. Rao, A. (2024). Farm mechanisation in India’s agriculture sector: Challenges and opportunities.
India Briefing. https://www.india-briefing.com/news/india-farm- mechanisation-sector-
opportunities-challenges-31243.html
83. Rath, I., Pradhan, P. L., Dash, R. C., Mahapatra, M., Sahoo, P. K., Behera, D., Behera, A.,
& Kamendra. (2024). Mapping the dynamics of agriculture mechanisation: Present
dynamics and future trajectories. International Journal of Agriculture Extension and Social
Development, 7(3), 181–186. https://doi.org/10.33545/26180723.2024. v7.i3c.425
84. Reddy, D. N., & Motkuri, V. (2013). SRI cultivation in Andhra Pradesh: Achievements, problems
and implications for GHGs and work (MPRA Paper No. 52115). National Institute of Rural
Development (NIRD). https://mpra.ub.uni-muenchen.de/52115/
85. Richards, M., & Sander, B. O. (2014). Alternate wetting and drying in irrigated rice. CGIAR
Research Program on Climate Change, Agriculture and Food Security (CCAFS). https://www.
researchgate.net/publication/306372935_Alternate_wetting_ and_drying_in_irrigated_
rice_Implementation_guidance_for_policymakers_and_ investors
86. Sharma, B., Gulati, A., Mohan, G., Manchanda, S., Ray, I., & Amarasinghe, U. (2018). Water
productivity mapping of major Indian crops. National Bank for Agriculture and Rural
Development (NABARD) & Indian Council for Research on International Economic Relations
(ICRIER).https://www.nabard.org/auth/writereaddata/tender/1806181128Water%20
Productivity%20Mapping%20of%20 Major%20Indian%20Crops,%20Web%20Version%20
(Low%20Resolution%20 PDF).pdf
87. Sharma, H. R. (2023). Patterns, sources and determinants of agricultural growth in
India. Indian Journal of Agricultural Economics, 78(1). https://isaeindia.org/wp- content/
uploads/2023/04/2-H-R-SHARMA-KEYNOTE-PAPER.pdf
88. Sharma, S., Das, P., Chaturvedi, C., & Malyan, A. (2024). Sustainable rice cultivation in India.
Council on Energy, Environment and Water (CEEW).
89. Shukla, A. K., Behera, S. K., Chaudhari, S. K., & Singh, G. (2022). Fertiliser use in Indian
agriculture and its impact on human health and environment. Indian Journal of Fertiliser,
18(3), 218–237
90. Singh, B. (2023). Nitrogen use efficiency in crop production in India: Trends, issues, and
challenges. Agriculture Research, 12, 32–44. https://link.springer.com/ article/10.1007/
s40003-022-00626-7
91. Singh, V., Rastogi, A., Nautiyal, N., & Negi, V. (2017). Livestock and climate change: The key
actors and the sufferers of global warming. Indian Journal of Animal Sciences, 87(1), 11–20.
https://doi.org/10.56093
92. Tiwari, P. S., Singh, K. K., Sahni, R. K., & Kumar, V. (2019). Farm mechanization – Trends and
policy for its promotion in India. Indian Journal of Agricultural Sciences, 89(10), 1559–1565.
https://doi.org/10.56093/ijas.v89i10.94575