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Disclaimer
The report covering projections of Demand and Supply of Crops and Livestock Products
and Agriculture Inputs for 2025-26, 2030-31, 2035-36, 2040-41 and 2047-48 has been
prepared by the experts of the Working Group.Every effort has been made to ensure the
correctness of data/ information used in this report and the sources are mentioned in
the report. NITI Aayog does not accept any legal liability for the accuracy or inferences
drawn from the material contained therein or for any consequences arising from the use
of this material.
Crop Husbandry,
Agriculture Inputs,
Demand & Supply
Working Group Report on ii iii
Working Group Members
S.No. Name & Organisation Role
1. Prof. P. S. Birthal, Director, ICAR - NIAP, New DelhiChairman
2. Dr. C.S.C. Sekhar , Professor IEG, New DelhiMember
3. Dr. N. Sivaramne. Principal Scientist, ICAR-NAARM, Hyderabad Member
4. Dr. Vijay Laxmi Pandey, IGIDR, Mumbai, CESSMember
5. Dr. Shivendra Kr. Srivastava, ICAR-NIAP, New DelhiMember
6.
Joint Secretary (Crops), Ministry of Agriculture & FW, Krishi
Bhavan, New Delhi
Member
7.
Joint Secretary (MIDH), Ministry of Agriculture & FW, Krishi
Bhavan, New Delhi
Member
8. ADG (Seeds), ICAR, New DelhiMember
9.
Animal Husbandry Commissioner, Ministry of AHDF, Krishi
Bhavan, New Delhi
Member
10.
Joint Secretary, Department of Fertilizers, Shastri Bhavan,
New Delhi
Member
11. Pr. Secretary (Agri), Govt. of Madhya PradeshMember
12. Pr. Secretary (Agri), Govt. of HaryanaMember
13. Pr. Secretary (Agri), Govt. of Andhra Pradesh Member
14. Pr. Secretary (Agri), Govt. of Rajasthan Member
15. DG, Fertilizer Association of IndiaMember
16. Sr. ESA, DACFW, Krishi BhavanMember
17. Representative of DG, CSO, SP Bhavan, New DelhiMember
18. Dr Raka Saxena, Principal Scientist, ICAR-NIAP, New Delhi Co-opted Member
19.
Dr A K Dixit, Principal Scientist, ICAR-Central Central Institute
for Research on Goats, Makhdum, Uttar Pradesh
Co-opted Member
20.
Dr Ranjit Kumar Paul, Senior Scientist, ICAR-Indian
Agricultural Statistical Research Institute (IASRI), , New Delhi
Co-opted Member
21. Director, ICMR-National Institute of Nutrition, Hyderabad Co-opted Member
22. Commissioner, Department of Fisheries, MoAH&DCo-opted Member
23. Dr. Neelam Patel, Sr. Adviser (Agriculture), NITI Aayog Member Secretary iv
Table of Contents
S. No.TitlePage No.
Prefaceix
Executive summaryx
1. Background1
2. Changes in consumer preferences3
2.1 Changes in consumption pattern: HCE surveys from 1972-73
to 2011-12
3
2.2 Changes in food consumption expenditure: PFCE from 2011-12
to 2019-20
7
3 Food demand and supply9
3.1 Food demand9
3.2 Food supply17
3.2.1 Supply/availability of food commodities17
3.2.2 Production performance of food commodities 19
3.2.3 Production potential for major food commodities 26
4 Normative food requirements 29
4.1 Normative demand
versus actual demand and production 30
5 Food demand supply projections 33
5.1 Food balance sheet for 2011-1233
5.1.1 Estimating components of food demand 34
5.2 Estimation of household and other food demand in 2019-20 and
testing the model accuracy
36
5.2.1 Food demand in 2019-20 36
5.2.2 Estimation of other food demand for 2019-20 38
5.2.3 Model accuracy 38
5.3 Projections for production of food commodities39
5.3.1 Production forecast scenarios 39
5.3.2 Crop acreage forecast 39
5.3.3 Crop yield forecast 40
5.3.4 Production forecast 41
5.4 Food demand projections 43
5.4.1 Alternate scenarios for direct food demand43
5.4.2 Projections of household and other food demand 43
5.4.2.1Household food demand43
5.4.2.2Other food demand 46
5.4.2.3Total food demand (household demand + other demand)46
5.5 External validation 50
5.6 Demand-supply gap51
6 Export potential60
6.1 The approach61
6.2 Commodity prospects64
6.2.1 Rice64
6.2.2 Wheat65
6.2.3 Dairy66 v
6.2.4 Bovine meat67
6.2.5 Eggs68
6.2.6 Fish and crustaceans69
7 Input demand projections71
7.1 Fertilizers71
7.2 Pesticides75
7.3 Seed75
7.4 Credit76
References78
Appendix80
Annexure-1112 vi
S. No.TitlePage No.
2.1 Trend in household consumption expenditure in India4
2.2
Changes in food preferences based on value addition to food
commodities
5
3.1
Trends in household consumption of different food commodities
in rural and urban areas
15
3.2 Availability of major food commodities in 2019-2018
3.3
Annual growth in area, yield and production of food commodities
during 2011-12 to 2019-20
25
3.4
India’s position in world production in 2019 and realizable yield
potential for major crops
27
4.1 Population weighted RDA norms for a balanced diet29
4.2 Estimated normative requirement of food commodities30
5.1 Estimated balance sheet of food production for the year 2011-12 34
5.2
Projected demand and actual availability of food commodities in
India in 2019-20
37
5.3
Forecast of crop acreage in India under Business-as-Usual (BAU)
Scenario
39
5.4
Forecast of yield under Business-as-Usual (BAU) and High Yield
Growth (HYG) Scenario in India
40
5.5
Forecast of production under Business-as-Usual (BAU) and High
Yield Growth (HYG) Scenario in India
42
5.6 Alternate scenarios for food demand projections43
5.7
Projected household food demand (home food +FAFH) in India
under Business-as-Usual (BAU) scenario
44
5.8
Projected household food demand (home food +FAFH) in India
under High Income growth (HIG) scenario
45
5.9 Other food demand projections under BAU scenario47
5.10
Projected total food demand (household + Others) in India under
Business-as-Usual (BAU) scenario
48
5.11
Projected total food demand (household + Others) in India under
High Income growth (HIG) scenarios
49
6.1
Export surplus assessment (Food demand: Business as usual
(6.34%) & Production: Business-as-usual)
60
6.2 Prospects for rice exports (million tonnes)64
6.3 Prospects of wheat exports (million tonnes)66
7.1 Projected demand for fertilizers72-73
7.2 Projected demand of pesticides75
7.3 Seed demand to 2047-4876
7.4 Credit demand to 2047-4877
List of Tables vii
List of Figures
S. No.TitlePage No.
2.1 Composition of consumption expenditure, 1972-73 to 2011-123
2.2 Composition of food expenditure4
2.3 Changes in food preferences of rural and urban consumers6
2.4 Expenditure class-wise consumption preferences7
2.5
Compound growth rate in consumption expenditure (at 2011-12
prices) in India during 2011-12 to 2019-20
8
3.1
Changesin household consumption of different food
commodities
10-11
3.2
Expenditure class-wise changes in consumption of different
food commodities
12-15
3.3 Trends in per capita food production19
3.4 Annual growth in food production20
3.5 Trends in production of food commodities21-24
4.1
Normative requirements versus actual consumption and
production in India in 2019
31
5.1
Comparison of projected food consumption and normative
requirement (moderate activity) at aggregate level
50
5.2
Comparison of projected per capita food consumption and
normative requirement (moderate activity) at disaggregate level
51
5.3a Demand-supply gap: Foodgrains and Cereals52
5.3b Demand-supply gap: Rice and Wheat53
5.3c Demand-supply gap: Nutri-cereals and Maize54
5.3d Demand-supply gap: Pulses54
5.3e Demand-supply gap: Vegetables and Fruits55
5.3f Demand-supply gap: Sugar & Products and Edible Oils56
5.3g Demand-supply gap: Milk and Eggs57
5.3h Demand-supply gap: Eggs and Meat58
6.1
Export prospects of dairy products, milk equivalent (million
tonnes)
67
6.2 Prospects of bovine meat exports (million tonnes)68 viii
S. No.TitlePage No.
2.1 Classification of products based on value addition80
2.2
Divergence between the NSS and NAS estimates of consumption
expenditure and food share
80
4.1
Age and gender wise recommended dietary allowance (RDA) for
a balanced diet
81
4.2 Age and gender wise distribution of the population in India 81
4.3 Population weighted RDA norms for the balanced diet in India 82
5.1 Crop area, seed rate and seed replacement rate in India83
5.2 Post-harvest losses in farm operations and marketing in India 83
5.3
Per capita consumption of food at household and away from
home in India in 2011-12
84
5.4
Estimated expenditure elasticities of food commodities in India
from the available studies
84
5.5
Range of published expenditure elasticities and their smoothen
values for future
85
5.6 Population estimates used to project food demand 85
5.7
Actual and forecasted values of area, yield and production of food
commodities in India
86-94
6.1
Export surplus assessment (food demand (6.34%) & production:
yield potential realization)
95
6.2
Export surplus assessment (food demand (7%) & production:
business as usual)
95
6.3
Export surplus assessment (food demand (7%) & production:
yield potential realization)
96
6.4
Export surplus assessment (food demand (8%) & production:
business as usual)
96
6.5
Export surplus assessment (food demand (8%) & production:
yield potential realization)
97
7.1 Methodological approach for projection of fertilizer and pesticide 98
7.2
Government initiatives for reducing the usage of pesticides and
fertilizers
98-102
7.3a Crop-wise seed demand in 2025-26103
7.3b Crop-wise seed demand in 2030-31 104
7.3c Crop-wise seed demand in 2035-36105
7.3d Crop-wise seed demand in 2040-41106
7.3e Crop-wise seed demand in 2047-48107
Office memorandum on constitution of the working group108-111
Minutes of the meetings of the working group113-115
List of Appendix ix
Preface
Over the past five decades, the technological change supported by investment in
irrigation and infrastructure, institutions and incentives have led to significant increases
in food production, ensuring affordable access to food for all. Nevertheless, the need
to produce more food remains as urgent as in the past to feed the ever-increasing
population, and under the growing resource constraints of land and water, and weather
aberrations.
To adequately feed the people in future requires information on the likely demand
and supply of different food commodities to devise appropriate strategies and policy
support for their production, distribution, and trade. To generate such information, the
National Institution for Transforming India (NITI) Aayog constituted a Working Group
deriving members from the academic and research organizations, concerned Ministries
of the Central and State Governments, and the commodity-specific associations of
manufacturers.
For smooth functioning of the Working Group, it was divided into three sub-groups
to generate futuristic scenarios on ‘demand and supply of food commodities’; ‘input
demand’; and ‘agricultural exports’. Each sub-group was headed by an expert, and
had the flexibility to co-opt any expert from outside the constituted Working Group,
if required. Dr. Shivendra Kumar Srivastava, Senior Scientist, ICAR-National Institute
of Agricultural Economics and Policy Research, New Delhi, steered the sub-group
on ‘demand and supply’. The sub-group on ‘agricultural exports’ was led by Dr. Raka
Saxena, Head, Division of Technology and Sustainable Agriculture, ICAR-National
Institute of Agricultural Economics and Policy Research, New Delhi. Professor C.S.C.
Sekhar from the Institute of Economic Growth, led the sub-group on ‘input demand’.
Dr. N. Sivaramane, Principal Scientist, ICAR-National Academy of Agricultural Research
Management, Hyderabad, and Dr. Ranjit Kumar Paul, Senior Scientist, ICAR-Indian
Agricultural Statistics Research Institute, New Delhi, provided significant support in
empirical analysis. I profusely appreciate their hard work and patience, and thank all of
them for accomplishing this arduous task.
The Working Group has immensely benefitted from the inputs, information and
suggestions received from several other professionals, especially from the Indian Council
of Agricultural Research, the National Institute of Nutrition, and Fertilizer Association of
India.
Finally, I place on record my sincere gratitude to Professor Ramesh Chand, Member,
NITI Aayog, who provided valuable inputs to the Working Group that helped us refine
the estimates of demand and supply presented in this Report. My special thanks are to
Dr. Neelam Patel, Senior Advisor, NITI Aayog, Member Secretary to this Working Group,
and Dr Tanu Sethi, Senior Associate, NITI Aayog for facilitating the functioning of the
Working Group and arranging meetings and consultations which helped us draw various
inputs required for the Report.
Pratap Singh Birthal
Chairman, Working Group x
India is envisioned to be in the league of developed nations by 2047, the centenary year
of its Independence. To realize this vision, the economy has to grow at an accelerated
rate of about 8% per year or so, from the 6.34% realized in the recent decade. In 2047,
India’s population will cross the 1.6 billion mark, and about half of it is expected to be
urbanized. There will be a demographic transition, in terms of age, literacy, and work-
force participation. These trends will cause a significant change in dietary patterns and
an increase in demand for different food commodities although differentially, depending
on the consumer preferences. Besides the food demand for human consumption, there
will be an increasing demand for food commodities in feed, fuel, and pharmaceutical
industries.
On the other hand, the country has limited land and water resources, which will shrink in
future on account of their competing demand for domestic, energy and industrial uses.
Concurrently, the food production system will also come under a confluence of several
biotic and abiotic pressures, including climate change and infestation of insect pests
and diseases, which may adversely affect crop yields and food supplies in the absence
of remedial measures. Therefore, managing food in the future, from both demand and
supply sides, will be a major concern for policy makers and the scientific community.
To assess the demand and supply of different food commodities towards 2047, the
National Institution for Transforming India (NITI) Aayog, the Government of India vide
OM dated 29th August, 2022 constituted a Working Group on
Crop Husbandry, Agriculture
Inputs, Demand and Supply
under the Chairmanship of Prof Pratap Singh Birthal, Director,
ICAR-National Institute of Agricultural Economics and Policy Research, New Delhi, with
the following terms of reference:
i. to study and analyze the trends in demand and supply of major food commodities
and examine the changing consumer preferences for food and related items;
ii. to assess the demand and supply of various food commodities and farm inputs
namely fertilizer, seeds, credit, feed and fodder for 2025-26, 2030-31, 2035-36,
2040-41, and 2047-48;
iii. to estimate the normative requirements of rice, wheat, maize, nutri-cereals,
pulses, foodgrains, oilseeds, sugarcane, fruits, vegetables, and animal products,
viz., milk, meat, eggs, and fish; and
iv. to estimate the feasible level of export of the above-mentioned commodities for
the years 2025-26, 2030-21, 2035-36, 2040-41, and 2047-48
The Working Group critically assessed and examined the data requirements and
methodological issues in arriving at realistic estimates of demand and supply of food
commodities, input demand, and feasible levels of exports. One of the main limitations
for estimating the food demand is the non-availability of data on food consumption after
2011-12. Nonetheless, the Group has tried to overcome this limitation by cross-validating
Executive Summary xi
the projected food demand for 2019-20 with actual availability, and supplementing with
other data sources such as private food consumption expenditure of National Accounts
Statistics from 2011-12 to 2019-20, Consumer Pyramid Surveys, 2016-2022 of Centre for
Monitoring Indian Economy (CMIE), etc.
Key Highlights
1. Changes in food preferences and demand
• There is an increasing trend in the total household expenditure, but the share
of food expenditure in it has declined considerably, from 69% in 1972-73 to
44% in 2011-12, and the decline is observed across all expenditure classes and
in rural as well as urban areas.
• Food commodities are demanded for direct human consumption and for their
other uses such as seed, feed, and intermediate inputs in food processing and
other industries. Nevertheless, household demand has the largest share (61%)
in the total demand for food commodities.
• Demand for cereals has declined due to changing consumer preferences
for nutritious foods, and also due to reduced energy requirements. Rice
and wheat have increasingly substituted nutri-cereals and maize. Further,
the consumption of nutri-cereals has been shifting from lower expenditure
classes to higher expenditure classes and from rural to urban areas. With
the recent focus on nutri-cereals, their demand is expected to increase in
the future. The average per capita consumption of cereals is more than their
recommended minimum requirement.
• There is a significant change in food preferences across all expenditure classes
and in rural and urban areas, away from staple foodgrains towards high-
value food commodities such as fruits, vegetables, animal-source foods, and
processed foods and beverages. Thus, the household demand for pulses and
high-value food commodities, including fruits, vegetables, and animal-source
foods, has been increasing faster compared to other food commodities.
• The household demand for edible oils has increased significantly. Refined oil
is emerging as the most consumed edible oil substituting groundnut oil and
Vanaspati ghee. On the other hand, the demand for sugar and sugar products
has declined although at the margin.
2. Trend in production of food commodities
• India is a major producer of most food commodities. The domestic production
sufficiently meets the demand for most food commodities, except edible oils
and pulses.
• The per capita total food production has increased considerably, leading to an
improvement in the national food security. The growth trajectory of different xii
food commodities, however, is different. The share of nutri-cereals in the
cereal basket has declined sharply on account of the steady increase in the
production of rice, wheat and maize. The area under cereals, except maize,
has remained either stagnant or declined, in recent years. Yield improvements
have been the main contributors to their incremental production.
• After stagnating for long, pulses production increased considerably in recent
years, but mainly due to area expansion.
• India imports about 60% of its edible oil demand. The matter of concern
is the deceleration in the growth of oilseeds production on account of the
stagnation in their area. Approximately two-third of the edible oil production
comes from primary sources (i.e., oilseeds), and the rest from secondary
sources, including trees.
• Production of fruits and vegetables has increased steadily. However, the
growth in fruit production has decelerated due to stagnation in the area.
Production of vegetables has increased, largely due to area expansion.
• Owing to improvements in the yield of sugarcane and sugar recovery rate,
India is self-sufficient in sugar, despite a slight decline in sugarcane area.
• Driven by changes in herd composition in favour of crossbred cows, and
improvements in milk yield of almost all milch species, milk production
has increased significantly over the past three decades. The production of
other animal products, including eggs, meat and fish, has also increased
considerably.
• India occupies the top position in area and production of several crops, but
lags far behind in terms of yield. There exists a huge scope to increase food
production to meet the rising food demand by harnessing yield potential and
improving land utilization efficiency.
3. Projections of food demand and supply
• In a business-as-usual (BAU) scenario, that is the continuance of the recent
economic growth (6.34%) in the future as well, the overall food demand is
expected to grow at an annual rate of 2.44% by 2047-48. It will accelerate up
to 3.07% if the economic growth accelerates.
• In a BAU scenario, demand for foodgrains is estimated at 402 million tonnes
in 2047-48, and to 415-437 million tonnes in high income growth (HIG)
scenario. Growth in demand for maize, pulses and nutri-cereals will be higher
as compared to rice and wheat. Demand for pulses is expected to be 49-57
million tonnes by 2047-48 under different income growth scenarios.
• By 2047-48, the demand for vegetables is expected to increase to 365 million
tonnes, and of fruits to 233 million tonnes in the BAU, and 385-417 million
tonnes and 252-283 million tonnes in HIG scenarios, respectively.
• By 2047-48, demand for sugar and its derivative products is estimated at 44-
45 million tonnes, and for edible oils at 31-33 million tonnes. xiii
• Demand for milk is projected at 480 million tonnes in 2047-48 in the BAU,
and at 527-606 million tonnes in HIG scenarios. By 2047-48, demand for
eggs, meat and fish is estimated at 16, 21 and 37 million tonnes, respectively
in the BAU scenario, which, in a HIG scenario, will be 18-21, 24-29 and 41-48
million tonnes, respectively.
• Between 2019-20 and 2047-48, gross cropped area is expected to expand
at annual growth of 0.45%, but would be driven primarily by the cropping
intensity. Hence, the additional production to meet the domestic demand has
to come from yield improvements. There exists a considerable yield gap in
most crops, which offers scope to accelerate growth in crop yields.
• By 2047-48, production of food grains will surpass their demand, but
the surpluses will be primarily for rice and wheat. With the government’s
promotional efforts, the demand for nutri-cereals will increase and their
production will be insufficient in the absence of area expansion and yield
improvements.
• In a BAU scenario, maize production will fall short of its demand. However, in
high yield growth (HYG) scenario, its production is expected to be sufficient
to meet the demand. Similarly, pulses production if following its historical
trend growth, will be insufficient to meet their demand. There is a possibility of
achieving self-sufficiency in pulses, if the current trend in their area expansion
continues, and the yield growth accelerates.
• Presently, production of fruits and vegetables is short of their demand, and
the shortfall may remain in future in the absence of a significant acceleration
in their yield growth and area expansion.
• Likewise, edible oils production will remain short of their demand at least in
the short-run. Yield improvements in cultivated oilseeds, and harnessing the
potential of secondary edible oil sources can help achieve self-sufficiency in
the long-run.
• Production of sugar and its derivative products will remain higher than their
demand.
• Domestic production of animal source-foods, including milk, eggs and fish,
but not of meat, will be adequate to meet their demand in a BAU scenario.
However, their domestic production may fall short of demand if the economy
grows faster.
4. Normative food demand
• The minimum requirement of food varies considerably across age, gender,
and physical level of activities. With the rising population, total normative
food demand is expected to rise in future.
• Food production is sufficient to meet the normative demand. However, the
present level of food consumption is inadequate and imbalanced to meet
nutrients’ requirement for a healthy life. xiv
• The actual aggregate food demand for human consumption was 31% short of
the normative demand, based on recommended dietary allowance in 2011-12,
and the gap reduced to 22% in 2019-20. By 2030-31, both are expected to
converge, and the actual demand is likely to be 20% more than the normative
demand by 2047-48. However, by commodity, pulses, fruits, and vegetables
will remain insufficient by 2030-31, but not by 2047-48. If fact, actual demand
for all food commodities is expected to be either at par or higher than their
normative demand in 2047-48.
• Adequacy of production is a necessary condition but not sufficient condition
to improve the nutritional security. This necessitates strengthening of
accessibility and affordability dimensions of food and nutritional security.
5. Status of agricultural exports
• Agricultural exports have been rising steadily, and the export basket is also
changing. India, with a share of 40% in global rice (Semi-milled) exports, is
the largest exporter, and is highly competitive in the global market.
• India is also a significant exporter of sugar and its derivative products. Its
exports of bovine meat and fish and fish products are competitive in the
international market, offering an opportunity to enhance their exports.
• India is not a major exporter of wheat, dairy products and eggs because of
lack of competitiveness. Importantly, their exports are volatile.
6. Feasible level of exports of selected commodities
• The projected rice exports (based on historical data) portray a gradual
increase, culminating at 30.07 million tonnes by the year 2047. Moreover, the
potential for export expansion appears promising, as the surplus available for
export is expected to surge significantly, starting at 26 million tonnes in 2025
and reaching an impressive 40 million tonnes by 2047. This clearly signals a
favorable environment for further augmenting the country’s rice exports.
• Given India’s historical position as a relatively intermittent participant in the
global wheat export market, the extent of its wheat export potential remains
largely underestimated. Thus, the projected exports for wheat indicate a
gradual rise from 3.27 million tons in 2030 to 4.5 million tons in 2047. However,
the surplus determined by estimates of demand and supply, is projected
to experience modest growth increasing from 11 million tons in 2025 to 42
million tons in 2047.
• The projections indicate that the dairy exports would be less than one million
tonnes in terms of milk equivalent. The country has been able to harness
approximately 80% of export potential in bovine meat. The bovine meat is
expected to hover between 1-1.5 million tonnes. The exports of crustaceans
are promising. xv
7. Projected demand for agricultural inputs
Given the limited scope for area expansion, future growth in food production has
to come from intensification of the existing cropland, using more of inputs such
as fertilizers, pesticides and quality seeds, and also in improvements in irrigation
coverage and its efficiency.
• Fertilizers: In the most pessimistic scenario wherein the drivers (i.e., irrigated
area, fertilizer price, and output price) of growth in fertilizer consumption
are assumed to accelerate by 10%, the demand for fertilizers is expected to
increase to 396 lakh tonnes by 2030-31 and 640 lakh tonnes by 2047-48. The
corresponding increase in their per hectare consumption will increase from 193
kg by 2030-31 to 300 kg in 2047-48.
Nevertheless, the Government of India has initiated several schemes (i.e., Soil
Health Card, micro-irrigation including fertigation, Neem coated urea, natural
farming, biofertilizer, etc.) to reduce the use of chemical fertilizers. Assuming
that their successful implementation leads to a deceleration in growth in
fertilizer consumption by 50%, while growth in its drivers accelerates by 10%,
the demand for fertilizers is projected to be less; 339 lakh tonnes in 2030,
and 432 lakh tonnes in 2047-48. Accordingly, their per hectare consumption
is expected to be 165 kg in 2030-31 and 202 kg in 2047-48.
• Pesticides: In the BAU scenario, the demand for pesticides is projected to
increase to 79,233 tonnes in 2030-31 and to 1,18,405 tonnes in 2047-48. The
per hectare consumption is estimated at 0.39 kg in 2030-31 and 0.55 kg in
2047-48. Cotton is the largest consumer of pesticides. In recent years, cotton
area, however, has stagnated. On the assumption of a decline of 10% in the
growth in cotton area, the demand for pesticides will be less; 68,062 tonnes
in 2030-31 and 83,209 tonnes in 2047-48. Accordingly, their per hectare
consumption is projected at 0.33 kg in 2030-31 and 0.39 kg in 2047-48.
• Seeds: Given the projected seed replacement rates (SRR) for different crops,
the demand for certified seeds is estimated at 34,068 thousand quintals
in 2030-31 and at 49,701 thousand quintals in 2047-48. The corresponding
requirement for foundation seeds will be 1030 and 1531 thousand quintals,
and for breeder seeds 37,649 quintals and 55,483 quintals in 2030-31 and
2047-48, respectively.
By 2030, if the SRR reaches 100%, then the demand for certified seeds will
increase to 78,571 thousand quintals, and further to 92,335 thousand quintals
in 2047-48. Accordingly, the foundation seed requirement is projected at
2509 thousand quintals in 2030-31 and 2981 thousand quintals in 2047-48,
and the breeder seed requirement at 97,589 quintals and 1,17,669 quintals.
• Credit: With moderate growth in credit supply, the total credit (short-term
and long-term) requirement in agriculture is estimated at Rs 42,60,769 crores xvi
in 2030-31 and Rs 1,31,51,319 crores in 2047-48. The demand for long-term
credit will increase faster, consolidating its share in the total credit from 64%
in 2030-31 to 81% in 2047-48 from its current share of 45%.
Recommendations
Owing to the sustained rise in per capita income, changing lifestyles, and increasing
consumer preferences for nutritious foods, the consumption basket has been diversifying
away from staple cereals towards high-value food commodities. This shift is likely to be
more prominent in future, propelling a disproportionately high growth in their demand.
In view of this, the following recommendations merit attention.
1. Land use planning: Given the disproportionate increase in the demand for
fruits, vegetables, pulses, edible oils, nutri-cereals and maize compared to
rice and wheat, it is important to evolve economically feasible cropping
patterns suited to the resource endowments of different agro-ecological
zones. Changing demand preferences and rising surplus might pave the
way for diverting some of the rice and wheat acreage towards nutri-cereals,
pulses, and oilseeds.
2. Revisit price policy: The open-ended procurement of rice and wheat at
minimum support prices acts as a disincentive for diversification towards
high-value and riskier crops. It is, therefore, important to re-think about the
policy of open-ended procurement, and restrict the procurement of rice
wheat to the requirements of country’s food security and welfare schemes.
For the additional marketed surplus, farmers can be compensated through
price deficiency scheme. If they diversify away from rice and wheat, they can
be compensated for the revenue foregone from these, if any.
3. Invest in infrastructure and value chains for perishable commodities:
The existing infrastructure for storage, transportation, and processing of
perishable commodities is grossly inadequate given their levels of production.
It is, therefore, recommended to aggressively invest in infrastructure required
for perishable commodities to avoid post-harvest losses and reduce high
price volatility. Private investment in value chains can address some of the
infrastructural bottlenecks.
4. Promote millet consumption and production: Consumption of millets has
declined considerably. There is a need to keep the momentum of promotion
of millets to create awareness about their nutritional benefits among the
masses. There is also a need to accelerate production by increasing area and
improving yield, and promote the value chains of millets.
5. Reduce consumption of edible oils: Consumption of edible oil is more
than its recommended intake, which may adversely affect human health.
India imports 60% of its edible oil demand. Hence, creating awareness at
recommended level is beneficial for human health, and it will also reduce
fiscal burden owing to their imports. xvii
6. Enhance pulses production: Pulses will remain one of the key components of
Indian diet. Although there has been a significant increase in their production
in recent years, it remains short of the demand. There is a need for a
technological breakthrough in pulses, and for exploring possibilities of their
cultivation in rice-fallow areas.
7. Establish seed hubs: Seed is the most crucial input in agriculture. The seed
replacement rate need to be enhanced. To produce the required quantity of
seed of different food crops, there is a need to establish commodity-specific
seed hubs in their niche production regions of different pulse crops.
8. Rejuvenation of soil health: There are considerable regional disparities in
fertilizer consumption and imbalances in fertilizer nutrients so much so that
their adverse effects on soils, water, and the environment have now become
visible. Their nutrient use efficiency is also very low. Reducing the fertilizer
consumption and improving nutrient-use efficiency requires a multipronged
strategy, including the parity in prices of different nutrients, linking their
provision with their recommended usage, and promotion of bio-fertilizers,
integrated nutrient management, etc. The other option is to link agricultural
incentives to the adoption of sustainable agricultural practices that generate
ecosystem services and evolve a mechanism for their payment to farmers.
The recently announced Green Credit Scheme has considerable potential to
incentivize farmers for their adoption of such practices.
9. Promote climate-resilient technologies and practices: Climate change is
emerging a big threat to agriculture, which, in the absence of adaptation
and mitigation, will adversely affect crops yields and food supplies. Although,
India is proactive in addressing the climate change issues, the need for a
greater policy focus on adaptation and mitigation cannot be discounted.
10. Improve credit flow for capital investment: Credit plays an important role
in agricultural development. It alleviates liquidity constraints on the farmers’
short-term financial requirements for operational expenses and for capital
investment in farm assets, mechanization, land management and water
conservation, etc. Currently, the flow of short-term credit outweighs the long-
term credit flow. Given the low level of gross capital formation in agriculture,
there is a need to accelerate the flow of long-term credit for capital investment
to introduce private investment.
11. Invest in agricultural research: Agricultural research is crucial for addressing
the multiple challenges of climate change, resource degradation, environmental
pollution, malnutrition and poverty while enhancing agricultural productivity.
Although over time, there has been considerable improvement in spending
on agricultural research, it remains much less—0.5% of the agricultural gross
domestic product—than in several developed and developing countries as
well (2-3%). In the absence of adequate funding for agricultural research,
its outputs and outcomes may remain muted. Therefore, the need for more
allocation of resources for agricultural research should not be discounted. xviii
Note that returns on investment in agricultural research are significantly
higher than on the spending on input subsidies.
12. Expand the extension system: The future of agriculture will be knowledge
and information intensive, leading to an exponential growth in farmers’
demand for information on seeds, fertilizers, agronomic practices, weather
forecasts, markets, prices, trade, etc. However, currently, the outreach of the
formal extension system (including government extension systems, research
institutes, agricultural universities, mass media and ICTs) is limited. Hence,
there is a need to improve technology, input and information delivery systems
and establish a single window for providing all types of information. Notably,
the potential of technologies remains unrealized due to information and
capital constraints, as is evident from the large yield gap in in many crops.
13. Improve compliance towards food safety standards for exports: Food safety
standards in the international markets are becoming stringent. To harness the
export potential of agricultural commodities, it is imperative to strengthen
international market intelligence to identify market destinations, and their
tariff and non-tariff measures, and comply with these by promoting good
agricultural practices (GAP), good manufacturing practices (GMP), and good
handling practices (GHP).
14. Robust data systems: Robust data systems have become indispensable
in agriculture, providing a comprehensive understanding of the dynamic
environmental trends and facilitating in-depth analyses. These systems enable
researchers, farmers, policymakers, and other stakeholders to gain valuable
insights into the critical aspects of agriculture. Continuously updated and
systematic databases on household consumption pattern would be critical
in understanding the market signals and analyzing the demand dynamics.
The commodity balance sheets from nationally acclaimed institutions like the
Ministry of Statistics and Programme Implementation would be instrumental
in comprehensively scrutinizing commodity plans and formulating effective
strategies.
15. Upscale digital innovations: Digital innovations hold the promise of
improving efficiency, sustainability and inclusiveness of food systems, and
improving transparency and traceability along the food value chains from
upstream to downstream. In recent years, several digital innovations have
come up for irrigation optimization, aerial application of agro-chemicals, soil
and water mapping and testing, forecast and delivery of weather advisories,
disease diagnosis, marketing, customized crop insurance, etc. These need to
be upscaled incentivizing farmers and other stakeholders. 1
Background
Chapter 1
Owing to technological advancements and enabling policies and institutions, India has
made tremendous progress in food production during the past five decades, making
the country self-sufficient in food and even an exporter of food commodities like
rice, crustaceans, and bovine meat. In 2021-22, India produced 330 million tonnes of
foodgrains, 221 million tonnes of milk, 317 million tonnes of fruits and vegetables, and
16 million tonnes of fish. It also exported agricultural commodities worth US$50 billion.
It is important to note that India accounts for 40% of the global exports of rice. During
the Covid-19 pandemic, India’s exports of food commodities helped several food-deficit
countries fight against hunger and manage extreme price rise. Nevertheless, India is
deficit in edible oils and pulses, and imports these to meet their domestic demand.
Nevertheless, the need to produce more food remains as urgent as ever. According to
the National Family Health Survey 2019-20, about 32% of the children under five years of
age are underweight, 35% are stunted, and 19% are wasted. The Government of India is
committed to ensure an affordable access to nutritious and healthy food to all to achieve
the goal of zero hunger by 2030 as enshrined in the Sustainable Development Goals of
the United Nations.
India, by 2047, the centennial year of its independence, is envisioned to enter the league
of developed nations. To realize this vision, the economic growth has to be accelerated
to about 8% over the next 25 years, from 6.34% in the recent decade. The people,
thus, will be more affluent and demand more of nutritious, safe and processed foods.
Importantly, India’s population will cross 1.6 billion mark by 2047, and about half of it
will be living in cities and towns. The growing urbanization, changing demographics,
increasing participation of women in workforce, and improvements in storage and
logistics will accelerate the pace of diversification of food basket. Additionally, the
food commodities will be increasingly used as feed, fibre, fuel, and in nutraceutical &
pharmaceutical industries. These trends suggest a significant increase in the demand for
food commodities over the next 25 years.
At the same time, enhancing farmers’ income remains one of the important goals of
India’s agri-food policy. Indian agriculture is dominated by small landholdings, with 70%
of the holdings not exceeding one hectare, and their further fragmentation is inevitable,
restricting realization of the scale economies. Concurrently, the food production system
will come under a confluence of biotic and abiotic pressures. For the past three decades,
India’s net cropped area has been hovering around 139 million hectares; and there is little,
if any, scope of bringing additional land under agriculture, except through intensification
of the existing cropland. The water resources are limited, and the growing water scarcity 2
has been posing a serious challenge to the intensification of the existing cropland.
Groundwater in the intensively cultivated regions, as in Punjab and Haryana, has been
over-extracted. Besides the quantitative limits on the utilization of these resources,
their quality has also been deteriorating due to crop intensification. Further, pre- and
post-harvest losses in food commodities continue to be large, especially in perishable
commodities such as fruits, vegetables and milk. More importantly, climate change has
emerged a significant threat to the sustainability of food production systems, and the
threat is likely to be more pronounced in the plausible future climate scenarios, which in
the absence of adaptation and mitigation, will threaten the food and nutrition security of
all from upstream to downstream of the food supply chain. Nevertheless, supported by
the enabling policies and institutions on agricultural research offers considerable scope
to improve efficiency and resilience of agriculture.
Thus, an assessment of the current and projected demand and supply of food commodities
will help policymakers and scientific community to take informed decisions for food
management system, in terms of production, trade and distribution, to ensure food
and nutrition security of all. In this regard, the NITI Aayog constituted a Working Group
to assess the future food demand and the prospects of meeting it through domestic
production with the following terms of reference (ToR).
1. To study and analyze the trends in demand and supply of major food commodities
and examine the changing consumer preferences for food and related items.
2. To assess the demand and supply of various food commodities and farm inputs
namely fertilizer, seeds, credit, feed and fodder for 2025-26, 2030-31, 2035-36,
2040-41, and 2047-48.
3. To estimate the normative requirements of rice, wheat, maize, nutri-cereals,
pulses, foodgrains, oilseeds, sugarcane, fruits, vegetables, and animal products
viz., milk, meat, eggs & fish.
4. To estimate the feasible level of export of the above-mentioned commodities for
the years 2025-26, 2030-21, 2035-36, 2040-41, and 2047-48.
The Report is organized as follows: Chapter 2 presents changing consumers’ preferences
of food commodities. Past trends and present status of demand and supply of food
commodities are discussed in Chapter 3. Projections of the normative requirement of food
are presented in Chapter 4. Chapter 5 presents projected demand and supply of food
commodities. The estimates of feasible level of exports of selected food commodities are
discussed in Chapter 6. Projected demand for key agricultural inputs is given in Chapter 7. 3
Changes in Consumer
Preferences
Chapter 2
0
10
20
30
40
50
60
70
80
90
100
1972-731977-781983-841987-881993-942004-052011-12
69
62 62
60 62
50
44
31
38 38
40 38
50
56
Per cent
Food share Non-food share
Figure 2.1 Composition of consumption expenditure, 1972-73 to 2011-12
Food preferences evolve in response to changes in income, prices, demographics,
lifestyles, and the diversity in available foods. This chapter analyzes the changes in food
preferences of rural and urban consumers and of different expenditure or income classes,
using data from different rounds of the quinquennial ‘Household Consumer Expenditure
(HCE)’ surveys conducted by the National Sample Survey Office (NSSO) of the Ministry of
Statistics and Programme Implementation, Government of India. These surveys provide
detailed information on the consumption of food and non-food commodities, in quantity
as well as value. The latest available HCE survey is for 2011-12. For the later years, the
Group has relied on data on private final consumption expenditure (PFCE) from the
National Accounts Statistics for extrapolating food demand from 2011-12 onwards.
2.1 Changes in consumption pattern: HCE surveys from 1972-73 to 2011-12
There has been a rising trend in consumption expenditure, and being accompanied
by significant changes in its composition (Figure 2.1). The per capita consumption
expenditure (at 2011-12 prices) increased by 62.87% between 1972-73 and 2011-12 (Table
2.1), largely driven by non-food commodities. Food accounted for a lion’s share (69%) in
the total consumption expenditure in 1972-73, but after remaining around 62% between
1977-78 to 1993-94, it declined drastically to 44% in 2011-12. While the total consumption
expenditure (in real terms) has grown at an accelerated rate, the food expenditure has
not exhibited a similar trend. The food expenditure experienced a negative growth during
1972-73 to 1983, and 1993-94 to 2004-05. 4
49
45 44
36
34
30
22
6
7
6
7
6
6
6
12
13
13
15
16
16
19
6
6
7
8
7
8
7
4
5
5
5
6
6
7
66
8
9
10
11
9
223
34
4
5
998
99
8
8
6678911
15
0
10
20
30
40
50
60
70
80
90
100
1972-73 1977-78 1983 1987-88 1993-94 2004-05 2011-12
Per cent
Cereals & Substitutes Pulses & Products Milk & products
Edible oilEggs, meat, fish Vegetables
Fruits & nutsSugar, salt & spices Beverages and fast food
Table 2.1. Trend in household consumption expenditure in India
Rs/capita/month
Year
Total consumption expenditure
Food
expenditure
(at 2011-12
prices)
Non-food
Expenditure
(at 2011-12
prices)
At current
prices
At 2011-12
prices
Expenditure level
1972-7351983680303
1977-7879975609366
1983-84131994621373
1987-881781044630415
1993-943251093679414
2004-056841233618614
2011-1215991599708891
Compound growth (% per annum)
1972-73 to 19839.90.11 -0.90 2.08
1983 to 1993-9410.61.071.001.18
1993-94 to 2004-05 7.71.21 -0.90 3.99
2004-05 to 2011-12 12.93.791.93 5.49
*Current expenditure deflated by consumer price index for agricultural labourers (CPI-AL) for rural
sector, and by consumer price index for industrial workers (CPI-IW) for urban sector. To arrive at
the average expenditure, rural and urban expenditures were weighted by the number of rural and
urban households, respectively. CPI-AL (1987-88=100) and CPI-IW (1987-88=100) were rebased at
2011-12=100.
Source: Consumption Expenditure Surveys
Figure 2.2. Composition of food expenditure
Significant changes have taken place in the food basket. Cereals which accounted
for about half of the total food expenditure in 1972-73, have gradually lost their
share, declining to 22% in 2011-12 (Figure 2.2). On the other hand, the shares of high- 5
Food category
Real expenditure
(Rs/capita/month
at 2011-12 prices)
Compound
growth rate
(%)
Share in total
food expenditure
(%)
2004-05 2011-12
2004-
05
2011-12
Primary products82 99 2.9 14 15
First-processed low value- added 241 229 -0.5 42 35
First-processed high value- added 198 237 2.5 34 36
Second-processed products54 95 9.5 9 14
value commodities, including the fruits, vegetables, milk, meat, fish and eggs, in the
food expenditure have increased substantially from 24% in 1972-73 to 40% in 2011-12.
Disaggregated by commodity, the share of animal-source foods increased from 16% to
26 %, and of fruits and vegetables from 8% to 14%. Interestingly, there has been a notable
surge in the share of processed foods (including beverages and fast foods) from 6% in
1972-73 to 15% in 2011-12.
The other way to examine the change in food preferences is to analyze the change in
the food basket in terms of consumption of foods based on the extent of value addition
to them. Following Morisse and Kumar (2011), the food basket comprises (i) primary
products, (ii) first-processed low value-added products, (iii) first-processed high value-
added products, and (iv) second-processed products.
•
Primary products are consumed as produced without any processing (e.g. fresh
fruits, vegetables, eggs, and fluid milk).
•
First-processed low value-added products are the primary products with minimal
level of processing (upto 5%), in terms of shelling, hulling, husking, milling, drying
and grinding (e.g. rice, flour, pulses, spices, and dry fruits).
•
First-processed high value-added products are the primary products that
have undergone sophisticated processing in terms of pasteurization, heating,
fermentation, slaughtering and crushing, adding 5-15% value to them but without
any other ingredient (e.g. butter, curd, meat, fish, and sugar).
•
Second-processed products are the products manufactured from the first-
processed products adding other ingredients such as flavors and preservatives
(e.g. biscuits, bread, ghee, ice-cream, and jam).
The food items reported in the NSS-HCE survey 2011-12 have been classified into the
above four categories and are listed in Appendix 2.1.
Table 2.2 Changes in food preferences based on value addition to food commodities
Source: Estimates based on HCE surveys
Table 2.2 presents the expenditure on different food categories as classified above. The
expenditure share of first-processed low value-added foods has declined from 42% in
2004-05 to 35% in 2011-12. While, the expenditure on second-processed, primary, and
first-processed high value-added foods have increased at annual growth of 9.5%, 2.9%
and 2.5%, respectively, resulting in a decline in the share of first-processed low valued- 6
added products, and an increase in the share of second-processed foods to 14% in
2011-12 from 9% in 2004-05. This indicates growing preference for second-processed
food products, including the edible oils, fats, cold beverages, salted refreshments,
cookies, cooked meals consumed outside home, etc. The real expenditure on primary
foods has also increased, but the increment is far less than for the second-processed
products.
Figure 2.3 presents the changes in food preferences of rural and urban consumers. The
rural consumers allocated a higher share of food expenditure to the first-processed
high value-added and second-processed foods in 2011-12 than in 2004-05. For urban
consumers, the share of second-processed products increased from 14% in 2004-05 to
21% in 2011-12. These changes can be attributed to a sustained rise in per capita income,
increasing participation of women in workforce, and changing lifestyles. Nevertheless,
this transition in food preferences indicate existence of significant latent demand for
high-value and processed foods.
14151515
45
3735
30
34
37
36
34
7
1114
21
0
10
20
30
40
50
60
70
80
90
100
2004-052011-12 2004-052011-12
RuralUrban
Per cent
Primary productsFirst processed products (low)
First processed products (high) Second processed products
Figure 2.3 Changes in food preferences of rural and urban consumers
Income is one of the key determinants of food consumption and dietary preferences.
The data from the HCE surveys reveal a signifcant difference in the dieteray preferences
of consumers in different expenditure classes (Figure 2.4). The poor consumers
spend proportionately more on first-processed low value-added foods than their rich
counterparts. On the other hand, the share of first-processed high value-added, and
second-processed foods is signficiantly higher forthe rich consumers.
Nevertheless, share of second-processed foods has increased for all expenditure classes.
The share of first-processed high value-added foods has increased but only upto
seventh-decile expenditure classes. The dominance of high-value and processed foods
in the food basket of the rich consumers indicates their strong positive association with
household income. 7
0
20
40
60
80
100
17 16 16 16 15 15 15 15 15 15 15 14
52
48
46
43
41
39 37 35
33
30
27
22
24
28
31
33
35
36
37
38
39
39
38
33
7 7 8 8 9 10 11 12 13
16
20
31
Share in food expenditure
(%)
Expenditure classes
Primary productsFirst processed products (low)
First processed products (high)Second processed products
2.2 Changes in food consumption expenditure: PFCE from 2011-12 to 2019-20
Besides the household surveys, the macro estimates of the annual private final
consumption expenditure (PFCE) are generated by the Central Statistics Office (CSO)
for preparing the National Accounts Statistics (NAS). Both the HCE surveys and
NAS provide information on the final consumption of goods and services in resident
households. However, due to differences in the methodological approach and coverage
of households, there is a divergence in their estimates (GoI, 2015). Yet, the trends are
similar (Appendix 2.2). Since, the HCE survey data are not available after 2011-12, the
PFCE estimates provide insights into the macro dynamics for recent years.
Between 2011-12 and 2019-20, the total PFCE (at 2011-12 prices) increased at annual rate
of 7%. The growth has been higher for the non-food consumption expenditure (7.7%)
than the food expenditure (5.1%) (Figure 2.5). The higher growth in non-food expenditure
indicates a similar trend as obtained from the HCE data.
0
20
40
60
80
100
14 14 14 14 14 14 14 14 14 14 15 15
64
60
57
53 50
47
45 42
39
35 32
26
18
22
25
28
30
33
35
36
38
40
39
37
3 4 4 5 5 6 6 7 9 11
14
22
Share in food expenditure
(%)
Expenditure classes
Primary productsFirst processed products (low)
First processed products (high) Second processed products
2004-05
2011-12
Figure 2.4 Expenditure class-wise consumption preferences 8
Total Expenditure
Non-food
Food
Edible oil
Foodgrains
Vegetables
Fruit
milk & milk
products
Restaurants &
Hotels
Non-veg
Processed
products
7.0
7.7
5.1
0.8
3.4
3.9 4.0
4.8
7.4
8.1
10.2
CGR (%)
Figure 2.5. Compound growth rate in consumption expenditure (at 2011-12 prices) in
India during 2011-12 to 2019-20
Further, the growth in expenditure differs across food groups. It has been the lowest for
edible oils. The expenditure on processed foods registered the highest growth (10.2%).
The expenditure on food consumed in the restaurants, and also the animal-source
foods registered faster growth of 7.4% and 8.1%, respectively. These trends suggest that
demand for high value and processed products has been growing faster than for staple
foods. The PFCE based post 2011-12 evidence on food preferences are also consistent
with those obtained from the HCE until 2011-12.
HIGHLIGHTS
♦The spending of Indian households is increasing over the years and a major part
of incremental consumption expenditure is spent on non-food items. Allocation
of household budget on food is declining.
♦Consumer preferences are changing steadily away from staple to high value
added and processed food products in both rural and urban areas and across
all the expenditure-classes. This indicate existence of huge demand of these
products and market for the food processing industry in the country.
♦Rising consumer preferences towards high value food products have become
more pronounced in the recent years. The estimates of consumption expenditure
based on NSS-HCE surveys and NAS diverge in magnitude due to methodological
differences, but both sources provide similar trends in consumption pattern. 9
Food Demand and Supply
Chapter 3
3.1 Food demand
The total food demand comprises the direct demand for human consumption and the other
uses for seed, feed, and non-food (industrial) uses, besides the food loss. It is estimated that
61% of the food demand (at aggregate level) comprises the meals prepared in the household
premises and restaurants. The remaining represents the seed, feed, loss/wastages, and raw
material for food processing (second-processed products) and industrial uses (pharmaceutical,
cosmetic, ethanol, etc.). The pattern, however, varies across food commodities.
The household food demand dominates the total food demand, but it varies across expenditure
classes, and between rural and urban areas. The temporal changes in the household demand of
different food commodities have been examined and compared (based on uniform reference
period of 30 days) between 1993-94 and 2011-12 using the HCE data.
Foodgrains: Foodgrains include the cereals and pulses. Cereals comprise the main staple food
(Figure 3.1). Rice and wheat are the most consumed cereals, accounting for more than 90% of
the total cereal consumption. Consumer preference for these cereals appear to have become
stronger, as is indicated by an increase in the number of their consumers. The households
consuming coarse cereals (millets and maize) have declined between 1993-94 and 2011-12. In
2011-12, the average per capita consumption of cereals (357grams/day) was 27% more than the
recommended allowance of 281 grams/capita/day. On account of the dietary diversification
and the reduced energy requirement for physical activities, the average per capita cereal
consumption has declined by 16%. The decline was significant for maize (70%) and millets
(67%), as compared to rice (14%) and wheat (1%).
In 2011-12, the consumption of cereals was more in rural areas (Table 3.1). Expenditure class-
wise analysis, however, indicates weakening of the positive association between income and
cereal consumption, primarily due to a steeper decline in their consumption by the rich (Figure
3.2).These changes, however, differ across cereals.
The per capita consumption of rice has increased in the bottom five decile classes, but has
declined in the others. Wheat consumption increased in the bottom six decile classes, while
it reduced in the top four. The consumption of nutri-cereals was significantly higher among
the poor and in the rural areas in 1993-94 (Figure 3.2 and Table 3.1). But thereafter, their
consumption declined significantly (upto 93%) among the poor and also in the rural areas
(66%). The corresponding changes for higher expenditure classes and urban areas are not so
glaring. These evidences indicate a significant negative preference for nutri-cereals, especially
in the lower expenditure classes and in the rural areas. The consumption of nutri-cereals
appears to be moving towards the rich and urban areas. Nonetheless, in the International Year
of Millets 2023, there has been an increasing emphasis on promotion of consumption of nutri-
cereals. 10
25.5
1.5
8.6
3.7
4
3.4
27.4
4.1
8
3.33.5
3
0
5
10
15
20
25
30
Pulses Gram Arhar Moong Masur Urd
Grams/capita/day
1993-94 2011-12 (type-I)
98
92
75
8
18
98
96
88
5
15
0
10
20
30
40
50
60
70
80
90
100
Cereals &
millets
Rice Wheat Maize Nutri-
cereals
Per cent of households (%)
1993-94 2011-12 (type-I)
424
220
148
10
45
357
190
147
3
15
0
50
100
150
200
250
300
350
400
450
Cereals &
millets
Rice Wheat Maize Nutri-
cereals
Grams/capita/day
1993-94 2011-12 (type-I)
98
92
75
8
18
98
96
88
5
15
0
10
20
30
40
50
60
70
80
90
100
Cereals &
millets
Rice Wheat Maize Nutri-
cereals
Per cent of households (%)
1993-94
2011-12 (type-I)
95
19
55
46
41
36
97
53
58
51
44
40
0
20406080
100120
Pulses Gram Arhar Moong Masur Urd
Per cent of households (%)
1993-94 2011-12 (type-I)
Consuming households (%)
Per capita consumption
(grams/capita/day)
Figure 3.1 Changes in household consumption of different food commodities 11
97
70
77
60
98
82
87
67
0
20
40
60
80
100
120
VegetablesFruitsMilk & productsNon-veg
Per cent of households (%)
1993-94 2011-12 (type-I)
96
50
30
5.0
18
5
98
52
6
5.0
9
46
0
20
40
60
80
100
120
Edible oil Mustard oil Groundnut
oil
Coconut oil Vanaspati Refined oil
Per cent of households (%)
1993-94 2011-12 (type-I)
Consuming households (%)
Per capita consumption
(grams/capita/day)
13.9
5.5
5
0.400
1.21
0.6
22.1
8.8
1.6
0.4500.58
8.4
0
5
10
15
20
25
Edible oil Mustard oil Groundnut
oil
Coconut oil Vanaspati Refined oil
Grams/capita/day
1993-94 2011-12 (type-I)
162.6
19.4
147.6
12.8
186.2
23
165.5
15.8
0
20
40
60
80
100
120
140
160
180
200
VegetablesFruitsMilk & productsNon-veg
Grams/capita/day
1993-94 2011-12 (type-I)
Figure 3.1 Changes in household consumption of different food commodities 12
326
381
400
421
430
437
445 448 447 443
422
409
341
351
358 361 366 370 367
364
357 350
339
327
0
50
100
150
200
250
300
350
400
450
500
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Cereals
1993-94 2011-12
RDA
281
142
187
212
234
242
237 239 236
222
215
197 195
210 208
206
201 198
195 191
186 179
175
169
156
0
50
100
150
200
250
300
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Rice
1993-94 2011-12
92
118 120
122
131
141
152
160
174
183
190 190
120
133
136
139
147
151 153
152
156 155 154 156
0
20
40
60
80
100
120
140
160
180
200
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Wheat
1993-94 2011-12
Figure 3.2 Expenditure class-wise changes in consumption of different food commodities
Cereals
Rice
Wheat 13
76
59
54
50
46
48
44
42
39
34
26
18
5 6
11
16 16
20 19
21
18
16
12 11
0
10
20
30
40
50
60
70
80
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Nutri-cereals
1993-942011-12
13
16
19
20
22
24
25
27
29
33
37
44
18
20
21
24
25 26
27
29
31
34
37
41
0
10
20
30
40
50
60
70
80
90
100
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Pulses
1993-942011-12
RDA 97
17
31
48
67
88
110
137
170
207
267
316
400
30
51
72
98
121
146
171
188
226
264
304
353
0
50
100
150
200
250
300
350
400
450
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Milk & products
1993-94 2011-12
RDA 364
Figure 3.2 Expenditure class-wise changes in consumption of different food commodities
Nutri-cereals
Pulses
Milk & products 14
6
8
8
10
11
12
13
15
17
19
23
29
12
14
16
18
20
21
23
24
26
28
30
32
0
5
10
15
20
25
30
35
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Edible oils
1993-94 2011-12
RDA 27
90
115
126
138
147
157
164
173
182
196
214
268
103
131
144
158
168 180
188
198
208
224
245
307
0
50
100
150
200
250
300
350
400
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Vegetables
1993-94 2011-12
RDA 361
4 5 6 8 10 11 12 15 16
19
22
30
5 7 9 11 12 14 16 18
20
23 26
32
-20
30
80
130
180
230
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Non-veg
1993-94 2011-12
RDA
227
Figure 3.2 Expenditure class-wise changes in consumption of different food commodities
Edible oils
Non-veg
Vegetables 15
Figure 3.2 Expenditure class-wise changes in consumption of different food
commodities
4
5
7
9
11
13
16
19
24
32
44
74
5
7
10
12
15
17
20
25
30
38
48
67
-15
5
25
45
65
85
105
0-5
5-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-95
95-100
grams/capita/day
Expenditure class
Fruits
1993-94 2011-12
RDA
103
Table 3.1 Trends in household consumption of different food commodities
in rural and urban areas
Grams/capita/day

The average per capita consumption of pulses was 27 grams/day in 2011-12, which was far
less than their normative requirement of 80-97 grams/day. The consumption of pulses,
however, has increased over time. Further, the consumption of pulses is more diversified
as compared to that of cereals. Arhar comprises 30% of their total consumption, followed
by gram and masoor (15% each), and moong & urd (11% each). Between 1993-94 and
2011-12, the consumption of gram increased the most. The rich and urban households
consume more pulses compared to their poor and urban counterparts. Notably, pulses
consumption has increased for all, indicating its positive association with income.
Commodity
1993-942011-12
Compound growth
rate (%)
Rural Urban Rural Urban Rural Urban
Cereals 448 351 375 312 -0.98 -0.65
Rice234 176 204 155 -0.76 -0.70
Wheat146 153 148 145 0.08 -0.30
Nutri-cereals 53 20 18 10 -5.82 -3.78
Pulses 25 28 26 30 0.22 0.38
Meat, egg and fish 12 16 15 19 1.25 0.96
Milk and products 139 174 154 194 0.57 0.61
Vegetables159 163 186 171 0.88 0.27
Fruits15 31 19 32 1.32 0.18
Sugar26 32 26 29 0.00 -0.55
Edible oil12 19 20 26 2.88 1.76
Fruits 16
Plant-source high-value food commodities: The consumption of fruits and vegetables
has also increased. The households consuming fruits increased from 70% in 1993-94
to 82% in 2011-12. Notably, between 1993-94 and 2011-12, the per capita consumption
of fruits increased by 21%, more so in the rural areas. Yet their level of consumption
has remained far below the recommended allowance of 103 grams/capita/day. Further,
there is a significant difference in their consumption across expenditure classes, and
also between rural and urban consumers. The rich and urban households consume
more than the poor and rural consumers. Thus, there is a strong positive income effect
on fruit consumption.
Vegetables are an indispensable component of Indian diet, as every household consumes
these. Their per capita consumption increased by 14% between 1993-94 and 2011-12,
and the increase was more prominent in rural areas. Yet, their level of consumption has
remained below their recommended allowance of 361 grams/capita/day. Notably, their
consumption is more in the higher expenditure classes.
Animal-source foods: Between 1993-94 and 2011-12, the proportion of households
consuming milk and milk products increased by 10%, and their per capita consumption
by 12%. This change is observed in rural as well as urban areas, and in all expenditure
classes, except in the top two deciles. The households in the lower expenditure classes
consume less. In 2011-12, the average per capita consumption of milk was half of the
recommended allowance of 364 grams/capita/day.
The consumption of meat, egg, and fish has been increasing. In 1993-94, about 60% of
the households were non-vegetarian, and their proportion increased to 67% in 2011-12.
However, the quantity consumed is too less. Further, their consumption is more among
the rich and urban households. Nonetheless, their consumption has increased.
Edible oils: Edible oils are an important cooking medium. Notably, there is a noticeable
increase in the consumption of edible oils in all the expenditure classes and in both
rural and urban areas.Mustard oil, with a share of 40% in the total edible oils, is the
most preferred, followed by refined oil (38%), and groundnut oil (7%). The share
of vanaspati and coconut oil is less than 5%. Between 1993-94 and 2011-12, the
average per capita consumption of edible oils increased by 37%, from 13.9 grams/
day to 22.1 grams/day in 2011-12. Surprisingly, there is a significance change in edible
oil preference—consumers of refined oil have increased from 5% to 46%, whereas
consumers of vanaspati and groundnut oil have declined significantly. The per capita
consumption of mustard oil increased by 60%, from 5.5 grams/day in 1993-94 to 8.8
grams/day in 2011-12.
Sugar and sugar products: Sugar is an essential food item being consumed by more
than 90% of the households in one or another form. Between 1993-94 and 2011-12, the
average per capita consumption of sugar in urban areas declined by 9% and remained
almost unchanged in rural areas. Overall, the average per capita consumption of sugar
declined by 3.6%. 17
3.2 Food Supply
Food supply comprises the domestic production, net imports (exports minus imports)
and available stocks. For about two decades after Independence in 1947, India faced acute
food deficit. The onset of green revolution in the late 1960s accelerated food production
and made the country self-sufficient in several food commodities, especially wheat and
rice. India has also emerged as a net exporter of several agricultural commodities. In 2021-
22, it exported agricultural commodities worth US$52 billion. This section discusses the
components of food supply by commodity, and assesses their production performance
and potential.
3.2.1 Supply/availability of food commodities
Table 3.2 presents the availability of different food commodities in 2019-20. The
country produced 298 million tonnes of foodgrains (cereals and pulses), and after
accounting for 10.40 million tonnes of exports, 3.43 million tonnes of imports, and
11.23 million tonnes of stocks, their net availability for domestic use was 279 million
tonnes. Rice and wheat account for three-fourths of the available foodgrains, followed
by maize (10%), pulses (9%), and nutri-cereals (6%). Notably, rice accounts for more
than 90% of the foodgrain exports, while pulses are the major imported items.India is
the largest producer of pulses, still it imports - in 2019-20 about 11% of their domestic
demand was met through imports.
HIGHLIGHTS
♦Food is demanded for human consumption and other uses such as seed, feed, wastages
and manufacturing of industrial products. Household demand constitutes the largest share
in total food demand in India.
♦Household consumption of cereals is declining over time due to evolving consumer
preferences and reduced energy requirement. Over the years, fine cereals (rice and wheat)
have substituted the coarse cereals (nutri-cereals and maize). Average consumption of
cereals in India is higher than the recommended minimum requirements.
♦Consumer base of nutri-cereals is changing from rural and poor households to urban and
richer households. With the recent focus on nutri-cereals, their demand is expected to
increase in future.
♦Household consumption of pulses and high value food commodities such as fruits,
vegetables, milk and non-vegetarian products is increasing over time. Consumption of these
commodities is strongly associated with the income of the households. With the increase in
income, their demand is expected to increase at a faster rate as compared to cereals.
♦Refined oils have emerged as a major edible oils and have substituted other oils like vanaspati
and groundnut oil. The household demand of edible oils is increasing over time.
♦Household consumption of sugar decreased over time.
♦Total demand of food products in future will depend on change in per capita consumption,
population, income, difference between actual and normative requirements, and other uses. 18
Table 3.2 Availability of major food commodities in 2019-20
Million tonnes
NS: non-significant
The total at aggregate level may not tally due to rounding out of figures
With a production of 102 million tonnes in 2019-20, India was the second-largest producer
of fruits. It exported 0.83 million tonnes of fresh fruits, mainly grapes, pomegranates,
mangoes, bananas and oranges. Consumer preferences for fresh fruits have also
transformed in favour of exotic fruits, leading to a significant rise in their imports,
especially apples, oranges, kiwis, avocadoes, cherries, and blueberries. Imports of fruits
outweighed their exports.
India is also the second-largest producer of vegetables (188 million tonnes in 2019-20). It
exported 1.93 million tonnes of vegetables, much larger than their imports of a mere 0.15
million tonnes.The net availability of vegetables for domestic use was 186 million tonnes
in 2019-20.
India produced 12 million tonnes of edible oils in 2019-20 — 68% from the primary sources
(i.e. oilseeds) and 32% from the secondary sources (i.e. palm, cottonseed, rice bran,
coconut, solvent extracts, and trees and forest products). Their domestic production,
however, falls short of their demand, compelling their imports (>50% total supply of 24
million tonnes).
Commodity Production Export Import Change in stock Availability
Foodgrains298 10.40 3.43 11.23 279
Cereals274 10.17 0.47 11.23 254
Rice119 9.51 0.01 5.43104
Wheat108 0.22 NS 5.68102
Nutri-cereals 17 0.07 NS 0.1217
Maize29 0.37 0.46 -29
Pulses23 0.23 2.97 -26
Fruits102 0.83 0.99 -102
Vegetables188 1.93 0.15 -186
Edible oils12 0.98 13.42 -24
Sugar & products 32 5.80 1.12 -3.8431
Milk198 NS NS-198
Eggs6 NS NS-6
Meat9 1.17 0.002 -7
Fish14 1.33 0.072 -13 19
India with a total production of 32 million tonnes of sugar, including jaggery and khandsari
in 2019-20 was the largest producer. About 74% of the sugarcane output is used for
manufacturing of white sugar and the rest for other products (ISMA, 2022). In 2019-20, it
produced 27.4 million tonnes of white sugar and 4.2 million tonnes of gur and khandsari.
It exported 5.8 million tonnes of sugar.
India is the largest producer of milk—in 2019-20 it produced 198 million tonnes. The
production of fish, meat and eggs was 14, 9 and 6 million tonnes, respectively. A significant
amount of fish and meat is also exported.
3.2.2 Production performance of food commodities
Indian agriculture has made a significant progress, leading to manifold increase in
production of food commodities. During the last seven decades, the total food production
1

increased 8.5 times, much higher than 3.7 times increase in the population (Figure 3.3).
Accordingly, the per capita food production also increased, from 772 grams/day in 1950-
51 to 1713 grams/day in 2019-20.
The growth trajectory, however, has not been consistent (Figure 3.4). Before the advent
of green revolution (1950-51 to 1966-67), the total food production increased at annual
rate of 2.47% as compared to a 2.04% growth in country’s population. During 1966-67 to
1996-97, the growth in food production accelerated to 3.27% and remained higher than
the population growth (2.19%), resulting in an increase in per capita food production,
from 772 grams/day in 1950-51 to 1234 grams/day in 1996-97. Subsequently, the food
production came under a pressure of several biotic and abiotic factors, including weather
aberrations. The country experienced severe droughts in 1999-00 and 2002-03, causing
a deceleration in the growth of food production to 1.67 % during 1996-97 to 2005-06.
The per capita food production remained almost stagnant during this period. Since
2005-06, the per capita food production increased faster. Figure 3.5 shows the trends in
production of different food commodities since 1966-67.
1
Including cereals, pulses, edible oils, sugar, fruits, vegetables, milk, meat, fish and eggs
Figure 3.3 Trends in per capita food production
772
1234
1285
1713
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1950-51
1952-53
1954-55
1956-57
1958-59
1960-61
1962-63
1964-65
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
Grams/capita/day 20
Foodgrains: Cereals occupy more than half of the cropped area. In 1966-67, rice accounted
for 47 % of the total cereal production, followed by nutri-cereals (26%), wheat (17%) and
maize (7%). The production portfolio, however, has changed due to differential rates of
growth in the production of different crops (Figure 3.5). Between 1966-67 and 2019-20,
the production of wheat, maize, and rice increased 9.5, 5.9 and 3.9 times, respectively.
On the other hand, the production of nutri-cereals has remained almost stagnant at 17-
18 million tonnes. In 2019-20, the share of wheat increased to 39%, and of maize to 11%,
while that of nutri-cereals fell drastically to 6%. Nevertheless, the cereal production has
increased 4.2 times since 1966-67.
During the recent decade (2011-12 to 2019-20), the production of cereals increased at an
annual rate of 1.63% (Table 3.3). Cereal area either has remained almost constant (e.g.,
rice and wheat) or even declined (e.g., nutri-cereals). The increase in cereal production
has largely been driven by yield improvements. In case of nutri-cereals, even yield growth
could not negate the declining production. Maize production registered the highest
growth (3.71%), driven by both the area expansion and yield improvement.
On the other hand, pulses production remained almost stagnant for a long period (1966-
67 to 2002-03) because of an insignificant increase in their area as well as yield. Rather,
their area declined at an annual rate of 0.06%, and the yield improvement happened at
an insignificant rate of 0.77%. Nevertheless, in the recent decade (2011-12 to 2019-20),
pulses production grew at an appreciable rate of 4.43% a year (Table 3.3), due to growth
in area (3% a year) and yield as well (1.39%). Overall, pulses production increased 2.8
times between 1966-67 to 2019-20 which is far less as compared to the increase in the
production of cereals.
2.47
3.27
1.68
3.55
4.08
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
1950-51 to
1966-67
1966-67
to1996-97
1996-97 to
2005-06
2005-06 to
2015-16
2015-16 to
2019-20
%
Figure 3.4. Annual growth in food production 21
0
500
1000
1500
2000
2500
3000
0
20
40
60
80
100
120
140
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Kg/ha)
Production (mt), Area (Mha)
Rice
Production
Area
Yield (Axis-II)
0
500
1000
1500
2000
2500
3000
3500
4000
0
20
40
60
80
100
120
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Kg/ha)
Production (mt), Area (Mha)
Wheat
Production
Area
Yield (Axis-II)
Figure 3.5 Trends in production of food commodities
Rice
Wheat
0
500
1000
1500
2000
2500
3000
3500
0
5
10
15
20
25
30
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Kg/ha)
Production (mt), Area (Mha)
Maize
Production
Area
Yield (Axis-II)
Maize
0
200
400
600
800
1000
1200
1400
0
5
10
15
20
25
30
35
40
45
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Kg/ha)
Production (mt), Area (Mha)
Nutri-cereals
Production
Area
Yield (Axis-II)
Nutri-cereals 22
Figure 3.5 Trends in production of food commodities
0
500
1000
1500
2000
2500
3000
0
50
100
150
200
250
300
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Kg/ha)
Production (mt), Area (Mha)
Cereals
Production
Area
Yield (Axis-II)
Cereals
0
100
200
300
400
500
600
700
800
900
0
5
10
15
20
25
30
35
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Kg/ha)
Production (mt), Area (Mha)
Pulses
Production
Area
Yield (Axis-II)
Pulses
0
500
1000
1500
2000
2500
3000
0
50
100
150
200
250
300
350
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Kg/ha)
Production (mt), Area (Mha)
Foodgrains
Production
Area
Yield (Axis-II)
Foodgrains
0
200
400
600
800
1000
1200
1400
0
5
10
15
20
25
30
35
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Kg/ha)
Production (mt), Area (Mha)
Oilseeds
Production
Area
Yield (Axis-II)
Oilseeds 23
0
100
200
300
400
500
600
700
800
900
0
100
200
300
400
500
600
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Qtl/ha)
Production (mt), Area (0000 ha)
Sugarcane
Production
Area
Yield (Axis-II)
Sugarcane
0
20
40
60
80
100
120
140
160
0
20
40
60
80
100
120
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Qtl/ha)
Production (mt), Area (lakh ha)
Fruits
Production
Area
Yield (Axis-II)
Fruits
0
20
40
60
80
100
120
140
160
180
200
0
20
40
60
80
100
120
140
160
180
200
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Qtl/ha)
Production (mt), Area (lakh ha)
Vegetables
Production
Area
Yield (Axis-II)
Vegetables
0
1
2
3
4
5
6
0
20
40
60
80
100
120
140
160
180
200
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Yield (Kg/day/animal)
Production (mt), Animals (million)
Milk
Production
In-milk animal
Yield (Axis-II)
Milk
Figure 3.5 Trends in production of food commodities 24
Figure 3.5 Trends in production of food commodities
0
2
4
6
8
10
12
14
16
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Production (mt)
Fish
Fish (Total)Fish (Marine)Fish (Inland)
Fish
0
1
2
3
4
5
6
7
8
9
10
1967-68
1969-70
1971-72
1973-74
1975-76
1977-78
1979-80
1981-82
1983-84
1985-86
1987-88
1989-90
1991-92
1993-94
1995-96
1997-98
1999-00
2001-02
2003-04
2005-06
2007-08
2009-10
2011-12
2013-14
2015-16
2017-18
2019-20
Production (mt)
Eggs and Meat
Eggs
Meat
Eggs and Meat 25
Table 3.3 Annual growth in area, yield and production of food commodities during
2011-12 to 2019-20
Fruits and vegetables: The area under fruits increased significantly from 2.8 million
hectares in 1991-92 to 6.8 million hectares in 2019-20 at an annual rate of 2.4%. Their
yield also grew, but slowly (1.13 %). The production of fruits increased from 29 million
tonnes in 1991-92 to 102 million tonnes in 2019-20 at annual growth of 3.4%. In the recent
period (2011-12 to 2019-20), the average yield of fruit crops has grown at a rate of 3.82
% a year (Table 3.3), but their area has remained stagnant, slowing down growth in their
production.
The production of vegetables increased from 59 million tonnes in 1991-92 to 188 million
tonnes in 2019-20 at annual growth of 4.48%. During this period, their area and yield
increased at annual rate of 2.99% and 1.51%, respectively. The growth in their production,
however, has decelerated to 2.36% during the recent decade (Table 3.3). Comparatively
slow growth in their production is due to deceleration in growth of their area and yield
as well. Further, the yield has grown much less than the area, indicating that incremental
production has largely come from area expansion.
CommodityAreaYieldProduction
Foodgrains0.411.371.79
Cereals-0.271.911.63
Rice0.081.501.58
Wheat0.081.651.74
Nutri-cereals-2.661.31-1.38
Maize0.972.713.71
Pulses3.001.394.43
Fruits-0.503.823.30
Vegetables1.680.672.36
Oilseeds-0.531.440.90
Edible oils--1.70
Sugarcane-0.931.961.01
Sugar & products--1.20
Milk--5.87
Eggs--6.83
Meat--5.51
Fish--6.61 26
Edible oils: The production of oilseeds increased at annual rate of 3.13%, from 7 million
tonnes in 1966-67 to 33 million tonnes in 2019-20. Their area and yield increased at annual
rate of 1.41% and 1.97%, respectively. Notably, the oilseeds area increased until 1993-94
(from 15.95 million ha in 1966-67 to 26.89 million ha in 1993-94) and afterwards it has been
hovering around 26 million hectares. Their yield growth also decelerated. This has caused
a significant deceleration in their production growth, less than one percent (Table 3.3).
Cultivated oilseeds accounted for 76% of the total edible oil production in 2004-05,
which fell to 68% in 2019-20 because of the slower growth (1.03%) than the growth in
the contribution of secondary sources (1.84%).Currently, India is hugely deficit in edible
oils, and imports more than half of their total demand.
Sugar and sugar products: Sugarcane production has increased four-fold, from 93 million
tonnes in 1966-67 to 371 million tonnes in 2019-20 at annual growth of 2.48%. The area under
sugarcane increased from 2.3 million hectares in 1966-67 to 5.1 million hectares in 2006-07
but has remained stagnant thereafter. Rather from 2011-12 to 2019-20 the sugarcane area
experienced a negative growth of 0.93%. Nevertheless, its yield increased at an annual rate
of 1.96%. Given the high water use in sugarcane production, the stagnation in its area is
desirable from the perspective of water conservation. But the decline in production should
be compensated by improvements in yield and sugar recovery rate.
Animal source foods: Between 1992-93 and 2019-20, the total milk production increased
from 57.96 million tonnes to 198.44 million tonnes at an annual growth of 4.43%. Changes
in herd structure in favour of more productive crossbred or exotic cows is one of the
main factors for robust growth in milk production. The population of in-milk crossbred/
exotic cows increased at a rate of 6.21%, much higher than for in-milk buffaloes (2.27%),
and indigenous cows (0.97%).The share of crossbred cows in the total in-milk bovines
increased from 7% in 1992-93 to 21% in 2019-20, while the share of indigenous cows
declined from 50% to 35%. Buffaloes comprise 44% of the total in-milk bovines. Cross-
bred cows are high-producing (8.20 kg/day) than indigenous cows (3.08 kg/day) and
buffaloes (5.75 kg/day). Overall, the average milk yield increased from 2.83 kg/day/animal
in 1992-93 to 5.43 kg/day/animal in 2019-20 at annual growth of 2.19%. The growth in
milk production has accelerated in the decade beginning 2011-12.
The production of meat, egg and fish has increased considerably. Between 1991-92 and
2019-20, the production of eggs, fish and meat increased three to five times. In 1991-92,
to the total fish production, the marine and inland fish contributed 58.86% and 41.14%,
respectively. Over time, the inland fish production has registered a remarkable growth of
6.27% a year, as compared to only 1.38% growth in the marine fish production. This led to
a decline in the share of marine fish to 28.32%.
3.2.3 Production potential for major food commodities
India has 180 million hectares of agricultural land. It ranks high in production of several
food crops (Table 3.4). The scope for bringing more area under cultivation, is however,
limited because of the competing uses of land. Rather, agricultural land area seems
to have been diverted to non-agricultural purposes, — the agricultural land between
1991-92 and 2019-20 declined by about 5 million hectares. However, there is scope for
intensification of the existing agricultural land through multiple cropping.Currently, only
about 51% of the net sown area is cultivated more than once. 27
Table 3.4 India’s position in world production in 2019 and realizable yield potential
for major crops
*In top 20 major producing countries.
Source: @ Directorate of Economics and Statistics, # Indian Council of Agricultural Research,
$Food and Agriculture Organization of United Nations (FAO)
Given the limit on area expansion, technological change is the most promising approach
to augment food production in future. India, despite being one of the top producers of
several food commodities, lags far behind in their yields (Table 3.4). Across 20 major
producing countries, India ranks poor in yield of most crops. Also, within the country,
their yield is 24-54% less than the potential yield, and 33-74% less than the averages
for five major producing countries. This implies existence of a vast potential to improve
production by bridging the yield gaps.
Year
India’s rank in world Average
yield@
(kg/ha)
Realizable
potential
in India
(kg/ha)#
Average
yield of top
5 producing
countries
(Kg/ha)$
Area Production Yield*
Rice1 2 12 2722 5000 4342
Wheat1 2 11 3440 4500 5527
Jowar3 6 18 989 2000 3872
Maize4 6 19 3006 5500 8512
Gram1 1 13 1142 2000 1696
Arhar1 1 16 859 1500 1364
Lentil2 2 11 847 1400 1584
Groundnut1 2 9 2063 3000 3158
Soybean4 5 19 921 2000 3180
Fruits2 2 12 15090 27150 22638
Vegetables2 2 16 18373 36090 36266 28
HIGHLIGHTS
♦Significant progress in agriculture sector over the years has transformed India from a
food deficit economy to one which is not only food sufficient but also a net exporter of
agricultural commodities at aggregate level.
♦India is a major producer of most of the food commodities in the world. Domestic
production sufficiently meets the demand of most of the food commodities except
edible oils and pulses. There exists large exportable surplus in several commodities
such as rice, sugar, fish, meat, etc.
♦Rising per capita food production (at aggregate level) indicates improving status of food
security in the country. Growth in per capita food production is at historically highest
level during the recent years. Trajectories of the production vary at disaggregated level.
♦Nutri-cereals have witnessed a sharp decline in their share in cereals production basket
during the last five decades on account of steady increase in production of rice, wheat
and maize against the decline in nutri-cereals production. Area under the cereals crops
except maize has remained either stagnant or declined in the recent years and yield is
a main contributor to the incremental production.
♦After a long phase of stagnation, pulses production is rising during the recent years,
but mainly on account of area expansion. It is essential to sustain the growth in area
and accelerate yield of pulses.
♦Stagnation in area has reduced positive yield effect and decelerated the growth in
oilseed production during the recent years. Efforts are needed to expand area and
harness the potential of both primary and secondary sources of edible oils in order to
reduce import dependency in edible oils.
♦Production of fruits has increased steadily over the years. Area under fruits, however,
has become stagnant in the recent years leading to deceleration in the production
growth.Amidst the changing consumer preferences towards exotic fruits, efforts are
needed to diversify production basket towards these fruits.
♦Production of vegetables has increased significantly over the years. The incremental
production during the recent years is largely on account of area expansion. Improving
yield and sustaining rising diversification towards vegetables are necessary.
♦With the increasing production over time, the country has surplus sugar availability.
Area under sugarcane is declining in the recent years which can be seen as a desirable
trend in the context of water resources sustainability. Any adverse effect of area
reduction on production shall be compensated by improving yield and sugar recovery.
♦Improving feeding and livestock management, and changing herd composition towards
more productive cross-bred/exotic cattle has significantly raised the milk production.
The growth in the production of milk and non-vegetarian products such as eggs, meat
and fish has accelerated in the recent years.
♦India occupies a top position in area and production of several crops, but lags far
behind in terms of yield. Food production needs to grow at sufficient pace for meeting
the rising food demand by improving land utilization efficiency and harnessing yield
potential. 29
Normative Food
Requirements
Chapter 4.
For a healthy and active life, a human being requires a certain minimum consumption
of different food commodities, defined as their normative requirements. The normative
requirement of a food commodity, however, varies across individuals depending on their
age, sex, and physiological and work status. The Indian Council of Medical Research
(ICMR) has recently updated the Recommended Dietary Allowances (RDA) of nutrients
and has suggested required norms of intake of food commodities for persons by their
age, sex (male/female) and activity status (sedentary/moderate) (Appendix 4.1). Using
population of each category as weight (Appendix 4.2), the average national level RDA
norms for different food commodities have been estimated for the sedentary and
moderate activity for 2011 and 2019 (Table 4.1). The share of adults and elderly persons in
the total population will increase, and of children will decline. RDA norms for 2025, 2030,
2035, 2040 and 2047 adjusted to these demographic changes are given in Table 4.1
Table 4.1 Population weighted RDA norms for a balanced diet.
Grams/capita/day
Notes:*For non-vegetarian persons, 30 grams of pulses may be substituted with 70 grams of meat.
20-30% of cereals intake shall be of nutri-cereals.
The aggregate normative demand for different food commodities has been arrived by
multiplying the RDA norms with population (Table 4.2). For 2019-20, the normative
demand for cereals has been estimated at 114 and 142 million tonnes for the sedentary
and moderate activity status populations, respectively. This is expected to increase to
125-156 million tonnes in 2030 and 133-168 million tonnes in 2047.
Daily required intake of pulses for a person engaged in a sedentary and a moderate
activity is 79 and 99 grams, respectively. Accordingly, the normative demand for pulses
is estimated at 40-49 million tonnes for 2019, which will increase to 43-54 million tonnes
in 2030 and 47-59 million tonnes in 2047.
Year
Cereals & Millets Pulses*
Milk
Vegeta-
bles
Fruits
Fat/Edi-
ble oil
Seden-
tary
Moder-
ate
Seden-
tary
Moder-
ate
2011 231 281 80 97 364 361 103 27
2019 230 285 79 99 359 366 104 27
2025 228 285 79 99 357 369 105 27
2030 228 285 79 99 356 372 106 27
2035 227 284 79 99 355 374 107 26
2040 226 284 79 99 355 376 108 26
2047 224 283 79 99 354 379 110 26 30
As per the ICMR, a person to derive same quantity of nutrients from 30 grams of pulses
should consume 70 grams of meat. If pulses consumption were to be substituted by
meat, then the country would have required 92-115 million tonnes of meat in 2019-20.
However, as the Indian population consumes pulses as well as non-vegetarian products,
the actual normative demand for non-vegetarian products will be much less.
Table 4.2 Estimated normative requirement of food commodities
Million tonnes
*For non-vegetarian persons, 30 grams of pulses may be substituted with 70 grams of meat.
The average daily per capita requirement of milk has been estimated at 364 grams in
2011. Children and elderly persons are required to consume relatively more compared to
adults (Appendix 4.3). With an increasing proportion of adults in the total population,
the estimated average RDA norm for milk will reduce to 354 grams by 2047. Accordingly,
the total normative demand for milk is estimated at 179 million tonnes in 2019, which
will gradually increase to 210 million tonnes by 2047. Notwithstanding, the normative
requirement of milk represents the liquid milk to be consumed directly by the human
beings. It does not include the consumption of processed milk products.
The average daily per capita requirement of vegetables and fresh fruits (pulp portion)
respectively has been estimated as 361 and 103 grams for 2011, which is expected to
increase over time (Table 4.1). In 2019, this translated into normative demand 183 million
tonnes of vegetables, and 52 million tonnes of fruits. By 2047, the normative demand for
vegetables will increase to 225 million tonnes, and of fresh fruits to 65 million tonnes.
For a balanced and healthy diet, daily intake of 27 grams of edible oils and fats is
recommended per person. Accordingly, the total normative demand for edible oils and
fat has been estimated at 12 million tonnes for 2011, which will gradually increase to 15
million tonnes by 2047.
4.1 Normative demand versus actual demand and production
For food management, it is imperative to know whether available food is sufficient to meet
the normative demand, and to what extent the actual demand deviates from it. Figure
4.1 compares the normative requirement (for moderate activity) of food commodities
with that of their production and actual consumption in 2019. A person engaged in a
moderate activity requires 1265 grams of food per day. The food produced (1721 grams/
capita day) was 36% higher than the required. However, the actual consumption of food
Year
Cereals & Millets Pulses*
Milk
Vegeta-
bles
Fruits
Fat/Edi-
ble oil
Seden-
tary
Moder-
ate
Seden-
tary
Moder-
ate
2011 105 128 36 44 166 165 47 12
2019 114 142 40 49 179 183 52 13
2022 118 146 41 51 184 188 54 14
2025 120 150 42 52 188 195 55 14
2030 125 156 43 54 195 204 58 15
2035 128 161 45 56 201 212 61 15
2040 131 165 46 58 206 219 63 15
2047 133 168 47 59 210 225 65 15 31
1721
1265
1000
0
200
400
600
800
1000
1200
1400
1600
1800
2000
ProductionNormative demand Actual consumption
Grams/capita/day
Total food
550
24
63
285
2726
357
3028
0
100
200
300
400
500
600
CerealsFat & Edible oilSugar&products
Grams/capita/day
ProductionNormative demand Actual consumption
Figure 4.1 Normative requirements versus actual consumption and production
in India in 2019
103
398
377
205
98
359
366
104
46
209
276
53
0
50
100
150
200
250
300
350
400
450
Pulses & equivalanet
non-veg
MilkVegetablesFruits
Grams/capita/day
Production Normative demand Actual consumption 32
HIGHLIGHTS
♦RDA norms of food varies considerably across age, gender and physical level of
activities. With the rising population, total normative food demand is expected to
increase in future in the country.
♦Food production is sufficient to meet the normative requirement. However, present
level of food consumption is inadequate and imbalanced to meet to nutrients’
requirement for the healthy life.
♦Adequacy of production is a necessary but not s ufficient condition to improve
nutritional security. This necessitates strengthening of accessibility and
affordability dimensions of food and nutritional security.
was about 20% less than its requirement possibly due to inefficient distribution and lack
of affordability of food.
The consumption of cereals, edible oils/fats and sugar was higher than their requirements,
while the consumption of pulses and pulses-equivalent non-vegetarian products, milk,
fruits and vegetables was less than their requirements.Overall, these findings suggest
that production is a necessary but not sufficient condition to improve the nutrition
security of the population. 33
Food Demand and Supply
Projections
Chapter 5
The estimates of future food demand and supply, guide planning and implementation
of the food management strategies. Food demand comprises the direct demand as
food and the other uses such as seed, feed, and raw material for processing and other
industries.The availability of food comprises domestic production, carry-over stock and
imports.
At any point in time, the demand and supply should be equal, and any deviation from
the equilibrium is corrected by price changes. In case of demand being more (less) than
supply of a commodity, its price is expected to rise (fall) in the absence of any market
intervention.
The following procedure has been adopted to project food demand and supply.
i. Construct a food balance sheet and estimate components of demand and supply
for the base year, i.e. 2011-12.
ii. Estimate direct demand for human consumption and indirect demand as seed,
feed, wastages and other uses for 2019-20.
iii. Compare the projected demand for 2019-20 with the actual availability, and
validate accuracy of the estimates.
iv. Project crop area and yield of crops, and derive production estimates for future,
i.e., for 2025-26, 2030-31, 2035-36, 2040-41, and 2047-48. Plug these estimates
into the demand core system for estimating the demand for seed and feed.
v. Develop future scenarios and project the total demand and production under
these scenarios.
vi. Externally validate projected demand by comparing it with normative demand.
vii. Estimate demand-supply balance to estimate potential surplus or short fall.
Direct demand for human consumption is the largest component of the total food
demand. The HCE surveys provide estimates of the food consumed by the resident
households. The latest HCE data is available for 2011-12; hence it has been taken as the
base for projections. The unavailability of the latest estimates, helped in testing the
model for its accuracy by comparing the projected food demand for 2019-20 with the
actual availability. Further, the projected food demand is compared with the normative
requirement for external validation of the projections.
5.1 Food balance sheet for 2011-12
The food balance sheet provides a snapshot of the sources of food and its utilization 34
(Table 5.1). The availability of a commodity depends on its production, net export and
change in stocks. In 2011-12, India produced 261 million tonnes of foodgrains, of which
12 million tonnes were exported and 6 million tonnes were stocked (public). India also
imported 3.5 million tonnes of pulses. Thus, the net availability of foodgrains was 246
million tonnes. The production and net availability of different food commodities are
given in Table 5.1. Including other foods, a total of 669 million tonnes of food was available
in 2011-12.
Table 5.1 Estimated balance sheet of food production for the year 2011-12
Millon tonnes
* Home food + food away from home (FAFH)
# include the seed, wastage, chewing, etc.
The estimates of utilization of food commodities are not readily available, except per
capita household home food consumption. The utilization pattern of different food
commodities for food, seed, feed, wastages, and other uses has been derived using the
available information. Other food uses include raw material for food processing and
other industries. These are estimated as residuals, that is, the difference between actual
availability and consumption as food, seed, feed and wastages. Accordingly, 61 % of the
total available food in 2011-12 was consumed directly as food (Table 5.1).
5.1.1 Estimating components of food demand
The household food demand comprises the demand for home food and food away from
home (FAFH), the demand for feed, seed, wastages and other uses.
Food item
Prod-
uction
ImportExport
Stock
chan-
ge
Total
avail-
ability
Food
demand
SeedFeedWastage
Other
uses
Total
demand
Food-
grains
261 3.50111.9476.070246 177 5.7117 12.9633.5246
Cereals 2440.00511.7726.070226 164 4.9017 11.7328.4226
Rice 1050.0017.1761.940 96 88 1.312 4.82 0.1 96
Wheat 950.0000.7414.130 90 68 2.62 2 4.6812.990
Nutri-
cereals
20 - - 20 7 0.121.0 1.1410.920
Maize 220.0043.856 18 1.6 0.0912 1.013.7 18
Pulses 173.4960.174 20 13 0.800.30 1.23 5.1 20
Animal
products
Eggs 3 0.0000.030 3.3 2.00.24 1.13.3
Meat 5.50.0020.997 4.5 3.20.26 1.0 4.5
Fish 9 0.0340.902 7.8 4.00.68 3.1 7.8
Milk 1280.0040.000 128 711.1855.3128
Veget-
ables
1560.0052.040 154 10512.7936.3154
Fruits 760.7230.488 77 197.4550.6 77
Sugar &
products
320.1002.7410.747 29 12- 16.9#29
Edible oil109.9430.946 19 12 0.24 0.56 6.4 19
Overall 681 14 20 7 669 406 6 17 36 204 669 35
Seed demand: Farmers use either purchased seeds or seed saved from previous harvests.
The seed demand from a home-produced crop depends on its cropped area, seed rate
and seed replacement rate. The seed demand is estimated as:
Area under crops has been compiled from the Directorate of Economics and Statistics
(DES) of the Ministry of Agriculture and Farmers Welfare (MoAFW). The average seed rate
of a crop at national level is weighted average of its seed rate in major producing states
with cropped area as weight. The state-wise seed rate has been taken from the cost of
cultivation (CoC) scheme for 2011-12. The seed replacement rate (SRR) is the rate at which
farmers replace home-grown seeds with certified seeds. The SRR differs across crops, and
it has increased over time, meaning a decline in the demand for home-grown seeds. The
estimated seed demand for different commodities is presented in Appendix 5.1 and Table 5.1.
Feed demand: Feed consists of green and dry fodders, and concentrates, in varying
proportion from 40 to 80% for crop residues, 10 to 30% for green fodder and 10 to
30% for concentrates (Roy et al. 2019). Green and dry fodders, obtained from arable
lands, common property lands (permanent pastures, grazing land, etc.), crop residues
and by-products, are the main source of energy for animals. Concentrate feed consist
of oilseed cakes, crushed pulses, grains, wheat and rice brans, mineral mixtures, etc.
The ICAR-National Institute of Animal Nutrition and Physiology (NIANP) estimated
demand for concentrates at 56.2 million tonnes for 2011-12, of which grains constituted
30%. Accordingly, 16.9 million tonnes of grains were used as feed. Further, feedgrain
comprised 53% of maize, 5% of nutri-cereals, and 2% of rice, wheat and pulses. The
contributions of crops to feedgrains in 2011-12 are presented in Table 5.1.
Wastages: Post-harvest loss considered as a component of the total demand. The loss
differs across food commodities, depending on their perishability and post-harvest
processes of conversion of raw material into final product. The ICAR-Central Institute
of Post-Harvest Engineering and Technology (CIPHET) and the NABARD Consultancy
Services (NABCONS) have estimated post-harvest loss for various agricultural
commodities (Jha et al, 2015; NABCONS, 2022), which are given in Appendix 5.2. Utilizing
the loss coefficient, the total output loss in crop has been estimated for 2011-12 (Table
5.1).
Home food and food away from home (FAFH) demand: Food cooked within household
premises constitutes the largest component of food demand. The household demand
for home food has been estimated using the per capita consumption reported in type-
II (mixed recall reference period) schedule of the HCE survey, 2011-12 (Appendix 5.3).
The HCE survey also provides expenditure on meals consumed outside the home. In
2011-12, of the total food expenditure, 8.5% was towards the processed foods and the
foods consumed outside home. The cost of food cooked at home is approximately 30%
of the cost incurred outside. Therefore, to estimate food consumed outside home, the
expenditure share of the outside food has been adjusted by a factor of 0.3. Accordingly,
the food away from home accounted for 2.59% of the total food consumed. This
proportion is close to the estimate of 3.7% on foods taken in restaurants as provided by
the Consumer Pyramid Surveys conducted by the Centre for Monitoring Indian Economy 36
(CMIE) during 2016-2019. It is mentioned that the estimates of consumption outside
home is not available for individual food commodities. Therefore, the aggregate estimate
of 2.59% has been taken to estimate the food away from home demand for individual
food commodities. The estimates of per capita and total household food demand (home
food+ FAFH) are presented in Appendix 5.3 and Table 5.1, respectively.
Other demand: The other food demand has been estimated as the difference between
the availability of food and its use for food, seed, feed, and wastages (Table 5.1).
Notwithstanding the accounting errors, other food demand includes the quantiles used
as raw material in food processing and other industries.
5.2 Estimation of total household food demand in 2019-20 and testing the model accuracy
5.2.1 Food demand in 2019-20
Due to unavailability of estimates of the actual food consumption post 2011-12, the total
household food demand for 2019-20 has been estimated following the behavioristic
approach. This approach assumes income as an important determinant of food
consumption and predicts consumer response to changes in income through expenditure
elasticities. The elasticity provides for percent change in the quantity consumed due to a
one-percent change in the total consumption expenditure (proxy for income).
The coefficients of expenditure elasticities of different food commodities have been taken
from the published sources (Appendix 5.4). The expenditure elasticity of a commodity
is found to differ across sources due to the differences in estimating methodologies
and the datasets used. Since, some existing studies have already estimated expenditure
elasticities for food commodities from the latest available Household Consumption
Expenditure (HCE) survey data for 2011-12, the same has not been estimated by us.
Instead, a meta-analysis of the existing elasticities has been undertaken and the best
estimate has been taken for the demand projection. The best estimate is the one
which provides the least deviation between projected demand of a commodity and its
availability in 2019-20.
There is a biological limit for consumption of a food commodity; hence as a consumer
approaches the satiation level, the effect of income on its consumption declines. In other
words, the propensity to consume should decline over time. This has been captured
by smoothening the elasticity coefficient using rate of reduction in the gap between
the actual consumption and normative consumption. This implies that future demand
projections be based on varying expenditure elasticity rather than the its constant value.
Further, it is also shown in the studies that elasticity does not remain constant over time,
and changes due to factors other than income.
The following formulae have been used to compute varying expenditure elasticity ( ).
where, is the elasticity of commodity ‘i’ obtained either through the meta-analysis of
published elasticities, ri = rate of change of elasticity, which is estimated as: 37
where, and are the constants estimated by projecting and matching the household
food consumption for 2011-12 and 2019-20. The constants, viz., K1 & K2, are estimated to
be 0.5 and 0.025, respectively during this period.
Appendix 5.5 presents the expenditure elasticities of different commodities from different
sources, their best estimates (as discussed above) and the smoothened estimate to be
used for projecting demand for 2019-20 and onwards.
The demand for a food commodity has been projected as :

Table 5.2 Projected demand and actual availability of food commodities
in India in 2019-20
Million tonnes
*includes total household food demand;# includes demand for seed, wastages, chewing, etc.
where, D
t
is the food demand in future (‘t’ period ahead); D0 is the per capita food
consumption (home food + FAFH) in 2011-12; y is the rate of growth in per capita income,
v
it
is the expenditure elasticity; t represents the year of projection, and Nt is projected
population in year t (Appendix 5.6).
Food item
Projected demand
Production
Actual
availability
Deviation
between
demand
and
availa-
bility(%)
Food *Seed Feed WastageOthersTotal
Foodgrains 194.85.3 25.5 13.8 38.0277.3 299.2 281.0 -1.3
Cereals 177.94.6 25.1 12.3 31.3251.2 276.2 255.3 -1.6
Rice 93.4 1.3 2.4 5.7 0.1102.8 118.9 103.9 -1.1
Wheat 76.32.4 2.2 4.5 14.299.5 107.9 102.0 -2.4
Nutri-
cereals
6.60.09 1.5 0.98 10.0 19.2 19.0 18.8 1.9
Maize 1.60.0725.5 1.12 5.126.9 28.8 28.9 -6.6
Pulses 16.90.70 0.5 1.4 6.6 26.1 23.0 25.8 1.3
Animal-
source
food
14.20.32 1.6 7.9 23.7 28.5 26.1 -9.0
Eggs 3.10.34 1.6 5.0 5.7 5.7 -12.3
Meat 5.00.34 1.6 6.9 8.6 7.4 -7.7
Fish 6.20.96 4.7 11.8 14.2 12.9 -8.2
Milk 1041.7 80.3186.4 198.4 198.4 -6.1
Vegetables 137.814.0 47.2199.0 188.1 186.4 6.8
Fruits 26.69.1 71.8107.6 102.0 102.2 5.3
Sugar &
products
14.1- 19.4#33.5 33.7 32.9 2.0
Edible oils14.00.32 0.57 7.5 22.5 11.6 24.1 -6.7
Overall 506 6 26 41 272 850 862 851 -0.1 38
Between 2011-12 and 2019-20, net national income (at constant 2011-12 prices) and
population grew at annual rate of 6.34 and 1.12 %, respectively. This resulted in a 5.17%
annual growth in per capita income during this period.
The projected food demand in 2019-20 includes the home food as well as FAFH demand.
To segregate the food demand into home food and FAFH demand, one can first extrapolate
FAFH demand from 2011-12 to 2019-20 at an annual growth of 7.4%. Then, the FAFH
demand (for 2019-20) is subtracted from the projected food demand (home food + FAFH)
to derive the household food demand. As per the National Accounts Statistics, the private
final consumption expenditure (at 2011-12 prices) on hotels and restaurants grew at 7.4%
annually during 2011-12 to 2019-20. This approach of first estimating the food demand
(household + FAFH) and then segregating it into home food and FAFH addresses an
important issue that the consumers forego household food consumption whenever they
consume food outside. The projected food demand in 2019-20 is presented in Table 5.2.
5.2.2 Estimation of indirect food demand for 2019-20
Demand for seed in 2019-20 has been estimated using information on area under a crop,
its seed rate, and seed replacement rate (Appendix 5.1).
Demand of food for feed purpose is assumed to be dependent on the demand for animal-
source foods, (milk, eggs, meat and fish). Between 2011-12 and 2019-20, the demand for
animal-source foods grew at an annual rate of 5.33 %. Accordingly, the food demand for
feed purpose in 2019-20 has been estimated at 26 million tonnes (Table 5.2). Rice, wheat
and pulses each contributed 2 % of their production to feed demand. The use of nutri-
cereals as concentrate feed is also estimated using growth in demand for animal-source
foods. The rest of the feedgrains come from maize.
The wastage in post-harvest farm operations and marketing of food commodities for
2019-20 has been estimated using their actual production and loss coefficients reported
in NABCONS (2022). Accordingly, about 41 million tonnes of total food has been
estimated to be lost post-harvest.
The food demand for other indirect uses in 2019-20 has been derived by multiplying the
projected household food demand by the ratio of ‘other uses to the household demand in
2011-12’. This assumes that demand for other indirect uses remains the same throughout.
5.2.3 Model accuracy
At any point in time, quantity demanded should be equal to its availability. This condition
is used to test accuracy of the model used for demand projections. The projected
demand for 2019-20 is compared with actual availability. The deviation between the
two is less than 10% for most commodities, except eggs (Table 5.2). For foodgrains,
projected demand is 1.3% less than their availability—1.1% for rice and 6.6% for maize. For
vegetables and fruits, projected demand is 6.8% and 5.3% more than their availability.
The deviation is -6.1% for milk and -12.3% for eggs. For sugar, the projected demand is
2% more than its availability, while for edible oils it is 6.7% less. The deviation between
projected demand and availability is in a small range, which indicates robustness of the
model used for future demand projections. 39
5.3 Projections for production of food commodities
Production forecasts of food commodities are based on the assumption of continuance
of the past trends in their production. In case of crops, the area and yield are forecasted
first and then production is estimated by multiplying the two. The data on area, yield,
and production of crops from 1966-67 to 2019-20, except fruits, vegetables, eggs, meat,
fish and milk, were compiled from the Directorate of Economics and Statistics, MoA&FW,
Government of India.Data on fruits and vegetables is available for a shorter period. For
animal products, it is the production which is forecasted directly.
Four techniques have been applied viz., Autoregressive Integrated Moving Average
(ARIMA), Artificial Neural Network (ANN), Holt’s smoothing, and exponential growth
rate (during the last 10 years) model; and based on the expert judgement, the best
performing has been retained for each commodity (Appendix 5.7).
5.3.1 Production forecast scenarios
Forecast based on time series is termed as the ‘Business-as-Usual (BAU)’ scenario. High
growth in crop yield is taken as an alternate scenario, which assumes closing the gap
between the existing and realizable potential yield. The higher of the realizable potential
yield at present level of technology adoption, and the average yield of top 5 major producing
countries has been taken as the targeted yield to be achieved by 2047-48 (Table 3.4). In this
scenario, area forecasted under a crop is assumed to remain same as in the BAU scenario.
Thus, a scenario of high crop yield and usual growth in its cropped area is termed as the
‘high yield growth (HYG)’ scenario.
5.3.2 Crop acreage forecast
Past values of crop acreage along with its projected estimates obtained from the selected
model are presented in Appendix 5.7. Table 5.3 presents area forecasts for 2025-26, 2030-
31,2035-36, 2040-41 and 2047-48. The cropped area is not expected to increase in future. The
gross cropped area (GCA) is expected to increase at annual growth of 0.45 % during 2019-20
to 2047-48. The incremental acreage will come from improvements in cropping intensity.
Crops
2019-20
(actual)
2025-262030-312035-362040-412047-48 CGR
Foodgrains 128 128 131 133 133 136 0.23
Cereals 100 98 99 99 98 98 -0.06
Rice44 44 44 44 44 45 0.08
Wheat31 31 33 34 34 34 0.28
Nutri-cereals 14 12 11 9 8 7 -2.76
Maize10 10 11 11 12 13 1.01
Pulses28 30 32 33 35 38 1.10
Vegetables 10 11 12 13 14 15 1.34
Fruits7 8 8 9 10 11 1.67
Sugarcane5 5 5 5 5 5 0.49
Oilseed27 28 29 30 31 33 0.70
Total *176 181 186 190 193 199 0.45
GCA#211 217 222 227 231 239 0.45
*Area excludes crops not listed in the table; #Gross cropped area
Table 5.3 Forecast of crop acreage in India under Business-as-Usual (BAU) Scenario.
Million hectare 40
Foodgrains occupy more than half of the gross cropped area. In the BAU scenario, the cereal
acreage is likely to remain stagnant or even may decline. So is the sugarcane area. Rice and
wheat will remain dominant crops. Nutri-cereals will lose a significant area. However, the
recent efforts of the Government of India for the promotion of nutri-cereals can arrest the
decline. Maize, pulses and oilseeds area will increase. Vegetables and fruits too are expected
to gain in their area
5.3.3 Crop yield forecast
Given the limited scope for area expansion, the additional production to meet the domestic
demand will come from yield improvements. The likely changes in crop yields in the BAU
and HYG scenarios are shown in Table 5.4. In the BAU scenario, the rice yield is expected
to increase from 2722 kg/ha in 2019-20 to 3454 kg/ha in 2047-48 at annual growth rate
of 0.88 %. However, there exists a large yield gap, which if abridged, the yield may go upto
5000 kg/ha in 2047-48. Wheat yield is forecasted to reach to 4737 kg/ha by 2047-48 in the
BAU scenario, and to 5527 kg/ha in the HYG scenario.By 2047-48, the average yield of nutri-
cereals will increase to 2001 kg/ha in the BAU scenario and 2801 kg/ha in the HYG scenario.
Maize yield will experience a significant increase, reaching to 6355 kg/ha in 2047-48 in the
BAU scenario and to 8512 kg/ha in the HYG scenario. Pulses yield in India is currently low,
which is projected to increase to 1258 kg/ha in the BAU scenario and 1485 kg/ha in the HYG
scenario. The average yield of vegetables and fruits was 18373 and 15090 kg/ha in 2019-20,
respectively, which is projected to increase to 25039 and 20182 kg/ha by 2047-48 in the BAU
scenario, and to 36266 and 27150 kg/ha in the HYG scenario.
Sugarcane yield will increase to 100000 kg/ha by 2047-48. By 2047-48, the average yield of
oilseeds is expected to increase to 1776kg/ha in the BAU scenario, and to 2706 kg/ha in the HYG
scenario.
Crops
2019-20
(Actual)
Business As Usual (BAU)High Yield Growth (HYG)
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
CGR*
2025-
26
2030-
31
2035-
36
2040-
41
2047-48CGR*
Rice 2722 301932743394343834540.8831013457385342955000 2.19
Wheat 3440 371639484180441247371.1938084144451049095527 1.71
Nutri-cereals1316 1387 15261666180620011.5615471771202723192801 2.73
Maize 3006 352940344611527063552.8137574525544965628512 3.79
Pulses 823 901 9721049113112581.589341038115312811485 2.13
Vegetables 18373 20026211652230523444250391.152125423999270973059636266 2.46
Fruits 15090 16167170801799218905201821.0817194191692137223828271502.20
Sugarcane 80497 83995874049081394223989950.77843278765891121947211000000.78
Oilseed 1224 1358 14531548164317761.3914511672192622192706 2.87
Table 5.4 Forecast of yield under Business-as-Usual (BAU) and High Yield Growth
(HYG) Scenario in India
Kg/ha
*Compound growth rate between 2019-20 and 2047-48 41
Overall, even if the past trends were to continue, crop yields will improve significantly.
However, there exist considerable yield gap in most crops, which offer scope to accelerate
growth in the yield of most crops.
5.3.4 Production Forecast
The estimates of the forecasts of production of crops and animal food products under
the BAU and HYG scenarios are presented in Table 5.5.
Foodgrains: India produced 299 million tonnes of foodgrains in 2019-20, which by 2047-
48 is projected to increase to 457 million tonnes in the BAU scenario and 594 million
tonnes in the HYG scenario.Production of rice will increase to 154 million tonnes and
223 million tonnes in the BAU and the HYG scenarios, respectively. Wheat production is
expected to increase to 160-187 million tonnes by 2047-48. Production of nutri-cereals is
projected to decline in the BAU scenario, and also in the HYG scenario. This necessitates
arresting area decline under nutri-cereals through diversification. Maize production is
projected to increase to 80 million tonnes in the BAU scenario and to 107 million tonnes
in the HYG scenario. By 2047-48, pulses production is likely to be more than double to
47-56 million tonnes.
Plant-source high-value food commodities: In the BAU scenario, production of fruits and
vegetables by 2047-48 is projected to grow at an annual rate of 2.50% and 2.78 %,
respectively, reaching to 214 and 367 million tonnes. However, in the HYG scenario, their
production can grow by 4% per annum.
Sugar and products: Production of sugar and other products depends on cane production
and sugar recovery rate. According to the Indian Sugar Mills Association, in 2019-20
about 74% of the sugarcane output was utilized for manufacturing white sugar, and 11%
for gur, khandsari, etc (ISMA, 2022). With an average recovery rate of 10.1%, in 2019-
20 the estimated production of sugar, and other products was 27.4 million tonnes and
6.3 million tonnes, respectively. Since 2001-02, the sugar recovery rate has increased
at an annual rate of 0.15%, and it is expected to improve to 11.15% by 2047-48. Using
the projected production of sugarcane and sugar recovery rate, the total production of
sugar and sugar products is likely to increase to reach 50 million tonnes in 2047-48.
Edible oils: Production of edible oils (from primary and secondary sources) is projected
to double to 24 million tonnes in 2047-48 in the BAU scenario. An average recovery of
24% is assumed for forecast of the edible oils from the oilseed crops. The edible oil from
the secondary sources is assumed to grow at an annual rate of 3.76%; the rate at which
it increased during 2011-12 to 2019-20. Relatively higher growth in oilseeds yield (2.87%),
and oils from secondary sources (4.51%) is assumed in the HYG scenario. Accordingly,
edible oil production may increase to 33 million tonnes by 2047-48.
Animal-source foods: In the BAU scenario, milk production is projected to increase to 478
million tonnes by 2047-48 as compared to 198 mt in 2019-20. If the past yield trends were
to continue, the average milk yield is likely to increase from 5.4 kg/day in 2019-20 to 8.32
kg/day in 2047-48. In the BAU scenario, the number of in-milk animals is forecasted at
157 million in 2047-48 from the current 100 million. In the HYG scenario, milk yield may
increase to 10.11 kg/day in 2047-48, and accordingly the total milk production to 581
million tonnes. 42
By 2047-48, in the BAU the production of eggs, meat and fish is forecasted to grow at
annual growth of 4.56, 2.71 and 3.66% respectively. As for crops and milk, it is difficult to
arrive at the targeted yields of these commodities.
Table 5.5 Forecast of production under Business-as-Usual (BAU) and High Yield
Growth (HYG) Scenario in India
Million tonnes
Crops
2019-20
(Actual)
Business As Usual (BAU)High Yield Growth (HYG)
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
CGR*
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
CGR*
Foodgrains 299 3323683964174571.583433924445005942.57
Cereals 2763053373613784091.473153594054555382.50
Rice 1191331451501531540.971371531711912232.36
Wheat 108 1171311411471601.481201381531661872.06
Nutri-cereals19 1716161514-1.231919 19 19 190.00
Maize 29 3643 5162803.843848 61 771074.98
Pulses 23 27313540472.70283339 45 563.33
Animal source
food
28 38465563743.624049 63 781004.76
Eggs6 9 111316194.5610 12 15 18 215.00
Meat9 10121415182.711114 1823 30 4.71
Fish14 19232732373.66192330 37 494.70
Milk 1982583083584084783.312533103754525814.06
Vegetables 1882242542853183672.502382883464155313.92
Fruits 102 1221411611822142.781301581912292873.91
Sugar &
products
33.742434549501.504343 45 49 511.78
Edible oils 12 14151820242.691417 2124 333.97
Overall 862103011751316145716642.47105912541479172121743.50
For fish, the HYG scenario has been constructed by fixing the potential marine fish
production at 5.3 million tonnes (GoI, 2020), and the inland fish production at a one-
percent higher growth over the existing growth of 4.24%. Based on these assumptions,
the targeted growth in fish production in the HYG scenario is estimated at 4.70% (as
compared to 3.66% in the BAU scenario) until 2047-48. Accordingly, the fish production
has been estimated to reach 49 million tonnes in 2047-48.
The number of eggs per layer is 104 under the backyard and 286 under the commercial
production system. Nevertheless, there is a potential to obtain140 eggs/layer under the
backyard system and 300 under the commercial system. Harnessing this potential by 2047-
48 will require the egg yield to grow at an annual rate of 0.43 %. This has been added to the
expected growth of 4.56% in the egg production. Thus, with a growth rate of 5.0%, the total
egg production in the HYG scenario will increase to be 21 million tonnes by 2047-48.
Considering the rising demand for meat and its exports, a 2% higher growth is assumed
over the expected growth of 2.71% in the BAU scenario. The meat production, thus,
can be increased to 30 million tonnes in 2047-48.
*Compound growth rate between 2019-20 and 2047-48 43
5.4 Food demand projections
This section presents the projected household food (home food and FAFH) demand. The
home food and FAFH demand has been projected in the Business-as-Usual (BAU) and
the High Income Growth (HIG) scenarios. For projecting indirect demand, that is seed and
wastages, the projected area and production of food crops have been plugged into the
demand core system. Feed demand has been projected based on the growth in the projected
direct demand for animal-source food. Similarly, the demand for other uses depends on the
projected household demand.
5.4.1 Alternate scenarios for direct food demand
Using the expenditure elasticities of food commodities, their demand in base year and
the projected population, the direct demand for food commodities has been projected
for different income growth scenarios (Table 5.6). During 2011-12 and 2019-20, gross
value added (GVA)/net national income (NNI, at constant prices) increased at annual
rate of 6.34%, which is used to project food demand in a BAU scenario. Food demand
has also been projected for HIG scenarios, i.e., 7% and 8%. These scenarios are relevant in
the context of India being envisioned to become a developed country by 2047-48. The
projections indicate that to achieve the status of a developed country, India must target
accelerating its economic growth to 7.6 to 9.0% (RBI, 2023, PTI, 2023). The demand
projections in this scenario will help understand implications of high economic growth
for food management. It is to be noted that food demand for 2019-20 has been projected
at actual economic growth of 6.34% during 2011-12 and 2019-20.
5.4.2 Projections of direct and indirect food demand
5.4.2.1 Household food demand
Projected household demand for food commodities for 2025-26, 2030-31, 2035-36,
2040-41 and 2047-48 in the BAU and HIG scenarios is given in Table 5.7 and 5.8. Varying
expenditure elasticities have been employed for projecting demand to account for
diminishing propensity to consume food over time (Appendix 5.5).
Table 5.6 Alternate scenarios for food demand projections
Particulars
2011-12
(Base
year)
2019-
20
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
Population (million)* 1250 1366 1445 1504 1554 1593 1629
Growth in population
over 2019-20
1.12 0.94 0.87 0.81 0.73 0.63
Growth in GVA/NNI
during 2011-12 and
2019-20 (%)
6.34
Growth in per capita income over 2019-20 (%)
BAU (6.34%)
#
5.17
5.35 5.42 5.49 5.57 5.67
HIG(7%)
#
6.07 6.14 6.22 6.33 6.33
HIG (8%)
#
7.06 7.14 7.21 7.32 7.32
* United Nations (2022) (as on 1st July) # Business-as-Usual, High Income Growth 44
Foodgrains: Given the declining trend in per capita foodgrain consumption, but it
remaining higher than the normative requirement, the per capita consumption of
cereals is not expected to increase significantly. The demand growth will primarily be
driven by population. In the BAU scenario, direct demand for rice will increase to 100
million tonnes in 2030-31, and further to 106 million tonnes in 2047-48. Note that the
expenditure elasticity for rice is negative. The household demand for wheat will be 86
million tonnes in 2030-31, and 96 million tonnes in 2047-48. The per capita consumption
of nutri-cereals has declined significantly over time. If these trends were to continue,
their total direct demand will gradually decline to 4.1 million tonnes by 2047-48.
However, with the increasing awareness of their health effects and the government’s
focus on their promotion, the declining demand can be reversed. Therefore, a positive
elasticity with small incremental change over time has been taken to project the
direct demand for nutri-cereals. Accordingly, their demand for human consumption
is projected to be 10.8 million tonnes in 2047-48. In the HIG scenarios, the demand of
nutri-cereals is expected to be more.The demand for maize for direct food consumption
is expected to grow slowly and will remain less than 2 million tonnes. Pulses demand
for direct consumption is projected to double from 17 million tonnes in 2019-20 to
34 million tonnes in 2047-48 in the BAU scenario. On the whole, direct demand for
foodgrains is expected to be 248-254 million tonnes in 2047-48.
Commodity 2019-20 2025-26 2030-31 2035-36 2040-412047-48 CGR#
Foodgrains 195 208 219 229 238 248 0.90
Cereals 178 188 195 202 208 214 0.69
Rice93 97 100 102 104 106 0.46
Wheat76 82 86 90 93 96 0.85
Nutri-cereals*
6.5
(6.6)
6.1
(7.0)
5.7
(7.5)
5.2
(8.2)
4.7
(9.2)
4.1
(10.8)
-1.71
(1.84)
Maize1.6 1.6 1.7 1.7 1.7 1.7 0.26
Pulses17 20 23 27 30 34 2.60
Animal source
food
14 19 24 30 37 46 4.48
Eggs3 4 5 7 8 10 4.48
Meat5 7 9 11 13 16 4.48
Fish6 8 11 13 16 20 4.48
Milk104 136 166 198 230 276 3.67
Vegetables 138 166 190 213 236 263 2.43
Fruits27 34 41 47 54 62 3.18
Sugar &
products
14 15 16 17 18 18 0.96
Edible oil 14 16 17 18 20 21 1.45
Overall 506 595 673 753 831 935 2.30
Table 5.7 Projected household food demand (home food + FAFH) in India under
Business-as-Usual (BAU) scenario
Million tonnes
*Figures within parentheses are projections using positive incremental expenditure elasticities
# Compound growth rate between 2019-20 and 2047-48 45
Plant-source high-value food commodities: Fruits and vegetables are more responsive to
income changes, and by 2047-48 their demand for direct consumption is likely to increase
at a much faster rate; 2.43% and 3.18% respectively in the BAU scenario. Their direct
demand will be higher in the HIG scenarios. By 2047-48, India’s demand for vegetables will
be in the range of 263-302 million tonnes, and fruits in the range of 62-75 million tonnes.
Sugar & products: Direct demand for sugar and sugar products is expected to grow
slowly due to rising health consciousness. Growth in direct demand for sugar and
products is expected to be 18-19 million tonnes with different income scenarios.
Comm-
odity
High Income Growth Scenario (7%) High Income Growth Scenario (8%)
2019-
20
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
CGR
#
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
CGR#
Foodgrains1952082202302392500.932092202322422540.99
Cereals 178188195202208 2140.691881952022082150.70
Rice 93 97 99 102103 1050.4396 99 1011031040.40
Wheat 76 82 87 91 94 960.8783 87 91 94 970.91
Nutri-
cereals*
6.67.07.58.39.4 11.21.987.07.68.49.711.92.18
Maize 1.61.61.71.71.7 1.70.211.61.61.71.71.70.15
Pulses 17 21 24 28 31 362.8321 25 29 33 393.17
Animal
source
food
14 20 26 32 40 524.9221 28 36 46 625.59
Eggs 3 4 6 7 9 114.925 6 8 10 135.59
Meat 5 7 9 11 14 184.92 7 10 13 16 225.59
Fish 6 9 11 14 17 234.929 12 16 20 275.59
Milk 1041401732102483034.021451852302773474.55
Vegetables138169195221246 2782.631732032342643022.94
Fruits 27 35 42 50 57 673.4836 45 54 63 753.92
Sugar &
products
14 15 16 17 18 180.9915 16 17 18 191.04
Edible
oil
14 16 17 19 20 211.5416 18 19 21 221.68
Overall 506603689779869 9892.5161571582293010802.85
*Figures within parentheses are projections using positive incremental expenditure elasticities
# Compound growth rate between 2019-20 and 2047-48
Table 5.8 Projected household food demand (home food +FAFH) in India under High
Income growth (HIG) scenario
Million tonnes 46
Edible oils: Direct demand of edible oils is projected to increase at annual growth rate of
1.45% in the BAU scenario, and 1.54% to 1.68% in the HIG scenarios.Accordingly, the direct
demand for edible oils is expected to be 21-22 million tonnes in 2047-48.
Animal-source foods: Animal-source foods have a strong positive association with
income; hence their direct demand is expected to increase at an annual growth of 3.67%
to 5.59% in different income growth scenarios over the next 25 years (Table 5.7 & 5.8).
For 2047-48, in the BAU scenario, direct demand for milk is projected at 276 million
tonnes, which could reach to 303-347 million tonnes if the economy grows faster. Direct
demand for meat is expected to be a minimum of 16 million tonnes, and a maximum of
22 million tonnes.
Demand for eggs will lie between 10-13 million tonnes, and for fish between 20-23 million
tonnes.
On the whole, between 2019-20 and 2047-48 the direct demand for food is projected to
increase at annual growth of 2.30% in the business as usual scenario, and 2.51 to 2.85 %
in high income growth scenarios.
5.4.2.2 Other food demand
The projected demand of food for other uses including seed, feed, wastages, and others is
presented in Table 5.9. Projected area/production/direct food demand in the BAU scenario
has been used to project indirect uses of food.
5.4.2.3 Total food demand (household + other demand)
The estimates of the total demand for food commodities in different income growth scenarios
are presented in Tables 5.10 and 5.11.
Foodgrains: Total demand for foodgrains is projected at 326 million tonnes in 2030-31, which will
gradually increase to 402 million tonnes in 2047-48 in the BAU scenario. In the HIG scenarios, it
is expected to reach 415 to 437 million tonnes by 2047-48. Amongst foodgrains, the growth in
demand for maize, pulses and nutri-cereals will be significantly higher than the growth in demand
for rice and wheat. Nevertheless, rice and wheat will remain the main constituents of diet. If the
declining trend in consumption of nutri-cereals is reversed, their demand may go upto 33 million
tonnes in 2047-48. Demand for maize, on account of its increasing use in feed and starch industries,
is expected to increase to 45 million tonnes in 2030-31 and 86 million tonnes in 2047-48 in the BAU
scenario. In the HIG scenarios, it may blow up reaching to 94 to 109 million tonnes.
Pulses demand is projected at 35 million tonnes in 2030-31 and at 49 million tonnes
in 2047-48 in the BAU scenario. In the HIG scenario, it will increase to 52 to 57 million
tonnes in 2047-48.
Plant-source high value foods: In the BAU scenario, total demand for vegetables is
projected to be 270 million tonnes in 2030-31 and to 365 million tonnes in 2047-48. In
the HIG scenarios, it may be as high as 385 to 417 million tonnes in 2047-48. Similarly,
demand of fruits is expected to be 160 million tonnes in 2030-31 and 233 million tonnes
in 2047-48 in the BAU scenario. In case of high income growth, their demand will be 252-
283 million tonnes in 2047-48. 47
YearFoodgrainsCerealsRiceWheat
Nutri-ce -
reals
MaizePulsesEggsMeatFishMilk
Vege -
tables
FruitsSugar
Edible
oil
Seed
2019-205.34.61.32.40.090.070.700.32
2025-265.214.491.222.410.060.090.730.35
2030-31 5.034.311.162.360.050.090.720.37
2035-36 4.764.031.092.190.040.090.730.39
2040-41 4.403.661.021.960.030.080.740.42
2047-483.843.090.901.590.020.080.750.44
Feed
2019-2025.5025.102.402.201.5019.100.50
2025-2634.3033.762.662.342.0026.760.54
2030-31 42.8842.272.892.622.5034.250.62
2035-36 57.5156.813.012.833.0647.910.70
2040-41 63.1462.343.062.933.6852.670.80
2047-4879.0878.143.083.204.6167.240.95
Wastages
2019-2013.812.35.74.500.981.121.400.340.340.961.7014.09.10.57
2025-2614.1312.605.914.500.841.281.530.470.381.222.1915.9110.550.62
2030-3113.6012.095.644.330.751.301.510.520.381.302.5016.6211.360.62
2035-3612.4110.955.053.900.671.281.450.520.361.332.7817.1312.060.61
2040-4112.4110.824.923.800.621.421.590.580.381.482.9918.8513.510.66
2047-4812.4710.694.663.790.561.631.780.660.391.693.2121.3415.650.74
Others
2019-2037.9531.340.0914.219.975.086.611.601.564.7080477219.437.55
2025-2641.5833.690.0915.0210.306.437.892.172.116.35104569121.958.39
2030-3145.3636.390.0915.4710.767.828.982.722.657.971266410823.238.97
2035-3649.3739.360.0915.6211.419.5110.023.343.269.791497012424.359.39
2040-4153.5542.610.0915.3712.2611.5710.954.023.9211.781717613925.269.58
2047-4859.1147.180.0814.1513.3615.2311.935.034.9014.732008115526.189.36
Table 5.9 Projections of other demand for food under BAU scenario 48
Table 5.10 Projected total food demand (household + other demand) in India under Business-as-Usual (BAU) scenario
Million tonnes
Commodity 2019-202025-262030-312035-362040-412047-48CGR#
Foodgrains2773033263533714021.39
Cereals2512722903133273531.27
Rice1031071101111131140.40
Wheat1001061111151171190.65
Nutri-cereals1920222326291.60
Maize2736456067864.39
Pulses2631354044492.38
Animal source
food
2432404959744.29
Eggs5.0781012164.32
Meat79121417214.31
Fish1216202429374.27
Milk1862432943494054803.56
Vegetables1992382703013303652.28
Fruits1081361601842062332.90
Sugar & products3437394143441.05
Edible oil2225272930311.23
Overall850101411571305144516302.44
# Compound growth rate 49
Table 5.11 Projected total food demand (household + other) in India under High
Income growth (HIG) scenarios
Million tonnes
Commodity
High Income Growth Scenario (7%)High Income Growth Scenario (8%)
2019-
20
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
CGR
#
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
CGR
#
Foodgrains277305329359379 4151.513073343703934371.70
Cereals 251273293318334 3631.382752963263443811.55
Rice 103107109111112 1140.371061091101121130.34
Wheat 100107112115118 1190.671071121161191200.71
Nutri-
cereals
19 20 22 24 27 31 1.7920 22 25 28 33 2.09
Maize 27 37 47 65 73 94 4.7539 50 72 82 1095.32
Pulses 26 32 36 41 46 52 2.6032 38 43 49 57 2.93
Animal
sourcefood
24 33 42 52 64 82 4.7334 45 58 73 98 5.39
Eggs 5.07 9 11 14 18 4.757 10 12 16 21 5.41
Meat 7 9 12 15 19 24 4.7510 13 17 21 29 5.42
Fish 12 16 21 26 32 41 4.7017 22 29 36 48 5.36
Milk 186249308371436 5273.922583294064896064.47
Vegetables199242277312345 3852.482472883293684172.78
Fruits 108139166193220 2523.201441762092422833.64
Sugar&
products
34 37 40 42 43 45 1.0838 40 42 44 45 1.13
Edible oil22 25 28 29 31 32 1.3226 28 30 32 33 1.47
Overall 850103011891358151917392.69105412401444164119213.07
# Compound growth between 2019-20 and 2047-48.
Sugar & products: Total demand for sugar and its products is projected at 39-40 million
tonnes in 2030-31 and 44-45 million tonnes in 2047-48 for different income growth
scenarios.
Edible oils: In the BAU, total demand for edible oils is expected to increase to 27 million
tonnes in 2030-31 and not much after that (31 million tonnes in 2047-48). In case of high
economic growth, it will be slightly more.
Animal-source foods: In the BAU scenario, demand for milk will increase to 294 million
tonnes in 2030-31 and further to 480 million tonnes in 2047-48. In case of high income
growth, it is projected to be 308-329 million tonnes in 2030-31 and to 527-606 million
tonnes in 2047-48.
Over the next 25 years, the demand for other animal-source foods is expected to grow
at an annual rate of 4.3 to 5.4 %. In the BAU scenario, by 2047-48 the demand for
eggs, meat and fish is estimated at 16, 21 and 37 million tonnes, respectively. In the HIG
scenarios, it is expected to be 18-21, 24-29 and 41-48 million tonnes in 2047-48. 50
Overall, by 2047-48 food demand is expected to grow at an annual rate of 2.44%.Further,
If the economy grows at a faster rate, the growth in demand will be higher, from 2.69 to
3.07%.
5.5 External Validation
Given the non-availability of reliable data required for demand estimation, and other
uncertainties, it becomes imperative to externally validate the demand projections.
Consumption of food is not expected to increase exponentially, and after meeting the
certain minimum dietary requirements, a rational consumer should reduce the intake of
a food commodity. Therefore, the demand estimates can be considered robust if these
are not significantly higher than the recommended dietary allowances.
1277
879
1000
1211
1530
0
200
400
600
800
1000
1200
1400
1600
1800
RDA 2011-12 2019-20 2030-31 2047-48
Grams/capita/day
Figure 5.1 Comparison of projected food consumption and normative requirement
(moderate activity) at aggregate level.
The aggregate normative daily requirement of food has been derived by summing
the intake of individual food commodities required for a balanced healthy diet for a
moderate activity, adjusting for the expected demographic changes by 2047 (Table 4.1).
This is then compared with projected food consumption in the BAU scenario (Figure
5.1). The quantity of daily food intake in 2011-12 was 31% less than the recommended
dietary allowance, and in 2019-20 it reduced to 22%. Projected per capita food demand
(direct) in 2030-31 is at par with the normative requirement. In 2047-48, it is expected
to be 20% more. As projected food demand falls within the realistic range of normative
requirement, the demand estimates can be considered robust.
At commodity level, per capita consumption of cereals, edible oils, and sugar in 2030-31
is estimated higher than their normative requirement, while of pulses (and equivalent
non-veg), fruits, vegetables, it remain lower. However, by 2047-48, the consumption of
all food commodities is expected to be either at par or higher than their normative
requirement. 51
5.6 Demand-Supply Gap
This section compares the projected demand and production to assess the extent of
surplus or deficit. It provides feedback for devising an effective food management
strategy.
283
2626
360
2727
357
3028
356
3330
360
37
31
0
50
100
150
200
250
300
350
400
Cereals Edible oils & fat Sugar
Grams/capita/day
RDA(moderate)
2011-12
2019-20
2030-31
2047-48
RDA(moderate)
2011-12
2019-20
2030-31
2047-48
99
354
379
110
37
157
230
4146
209
276
53
70
302
346
74
90
465
443
104
0
50
100
150
200
250
300
350
400
450
500
Pulses &
equivalent non-
veg
Milk Vegetables Fruits
Grams/capita/day
RDA(moderate)
2011-12
2019-20
2030-31
2047-48
RDA(moderate)
2011-12
2019-20
2030-31
2047-48
Figure 5.2 Comparison of projected per capita food consumption and normative
requirement (moderate activity) at disaggregate level 52
277
326
402
329
415
334
437
299
368
457
392
594
0
100
200
300
400
500
600
700
2019-202030-312047-48
million tonnes
Foodgrains
Demand (BAU):6.34% Demand (HIG):7%
Demand (HIG):8%Production (BAU)
Production (HYG)
251
290
353
293
363
296
381
276
337
409
359
538
0
100
200
300
400
500
600
2019-202030-312047-48
million tonnes
Cereals
Demand (BAU):6.34% Demand (HIG):7%
Demand (HIG):8% Production (BAU)
Production (HYG)
Figure 5.3a Demand-supply gap: Foodgrains and Cereals
Foodgrains: Total demand for foodgrains in 2030-31 is estimated between 326 to
334 million tonnes, and in 2047-48 between 402 to 437 million tonnes. The projected
production in the BAU scenario is 10-13 % (34-42 million tonnes) more than the demand
in 2030-31, and 5-14% (22-55 million tonnes) more in 2047-48. In the high yield growth
scenario, there will be large surpluses, which can be disposed offshore to earn foreign
exchange (Figure 5.3a).
In 2019-20, India produced 276 million tonnes of cereals, 25 million tonnes more than the
projected demand. The surplus is likely to remain in future as well.
Rice production in 2019-20 was sufficient to meet the domestic demand. Its demand
is expected to be 110 million tonnes in 2030-31 and 114 million tonnes in 2047-48 as
against the projected production of 145 million tonnes and 154 million tonnes in the BAU
scenario (Figure 5.3b).
Foodgrains
Cereals 53
Given the declining trend in consumption of nutri-cereals, their demand is projected
to decline to 18 million tonnes in 2030-31 and 14 million tonnes in 2047-48 (Figure
5.3c). Nevertheless, with the growing consumer awareness and the government
efforts to promote nutri-cereals, their demand can go up to 33 million tonnes by
2047-48. And, their production is expected to fall short of their demand because of
the decline in their area (Table 5.3). To meet their domestic demand, there is a need
to expand their area and improve yields.
Demand for maize has been growing fast in response to its growing demand in feed
and starch industries. Its demand as biofuel is also expected to increase. Maize demand
is expected to be 45-50 million tonnes in 2030-31 and further to 86-109 million tonnes
in 2047-48. In the BAU scenario, maize production will fall short by 2 million tonnes in
2030-31 and 6 million tonnes in 2047-48. However, in the HYG scenario, its production
is expected to be sufficient to meet the demand. This implies a need to harness its yield
potential, and allocate more area to its cultivation.
103
110
114
109
114
109
113
119
145
154153
223
0
50
100
150
200
250
2019-202030-312047-48
Production/Demand (MT)
Rice
Demand (BAU):6.34% Demand (HIG):7%
Demand (HIG):8% Production (BAU)
Production (HYG)
100
111
119
112
119
112
120
108
131
160
138
187
0
20
40
60
80
100
120
140
160
180
200
2019-202030-312047-48
Production/Demand (MT)
Wheat
Demand (BAU):6.34% Demand (HIG):7%
Demand (HIG):8% Production (BAU)
Production (HYG)
Figure 5.3b Demand-supply gap: Rice and wheat
Likewise, wheat production is expected to be sufficient to meet the future demand,
leaving a surplus of 19-26 million tonnes in 2030-31 and 40-67 million tonnes in 2047-48.
This suggests the need for reallocation of area from rice and wheat to other crops.
Rice
Wheat 54
Figure 5.3c Demand-supply gap: Nutri-cereals and Maize
Pulses demand is projected at 35 to 38 million tonnes in 2030-31 and 49-57 million tonnes
in 2047-48 (Figure 5.3d). Their present production is insufficient to meet the demand. This
gap may remain in future in the absence of yield improvements and acreage allocation to
them. In the HYG scenario, pulses production will suffice to meet the growing demand.
The area under pulses is projected to increase at 1.10 % per annum growth (Table 5.3) as
compared to 1.69 % growth during 2011-12 to 2019-20. If the current trend in pulses area
continues, and yield growth accelerates there is likelihood of achieving self-sufficiency
in pulses.
Figure 5.3d Demand-supply gap: Pulses
27
45
86
47
94
50
109
29
43
80
48
107
0
20
40
60
80
100
120
2019-202030-312047-48
Production/Demand (MT)
Maize
Maize Demand (BAU):6.34% Maize Demand (HIG):7%
Maize Demand (HIG):8% Maize Production (BAU)
Maize Production (HYG)
26
35
49
36
52
38
57
23
31
47
33
56
0
10
20
30
40
50
60
2019-202030-312047-48
Production/Demand (MT)
Pulses
Demand (BAU):6.34% Demand (HIG):7%
Demand (HIG):8% Production (BAU)
Production (HYG)
19
18
14
19
22
29
22
31
22
33
19
16
14
1919
0
5
10
15
20
25
30
35
40
2019-202030-312047-48
Production/Demand (MT)
Nutri-cereals
Demand (BAU):6.34% & no promotion Demand (BAU):6.34% & promotion
Demand (HIG):7%Demand (HIG):8%
Production (BAU)Production (HYG)
Nutri-cereals
Maize
Pulses 55
Plant-source high value foods: Production of vegetables was slightly less than their
demand in 2019-20. Without acceleration in growth in their area and yield, vegetable
supplies will be short of demand by 6-12% in 2030-31 (Figure 5.3e). However, in the
HYG scenario, their production will be sufficient to meet the demand. It is, therefore,
imperative to accelerate their yield, which has slowed down in recent years (Table 3.3).
In 2047-48, their production will be sufficient to meet their demand in the BAU scenario.
Nevertheless, with acceleration in economic growth, their production need to increase
at an accelerated rate. Note, there exists significant yield potential in most vegetables,
which need to be harnessed.
As for vegetables, the production of fruits was short of their demand in the year 2019-
20. The shortfall is likely to remain in future as well. However, in the HYG scenario, their
production may meet the demand in 2047-48.
199
270
365
277
385
288
417
188
254
367
288
531
0
100
200
300
400
500
600
2019-202030-312047-48
Production/Demand (MT)
Vegetables
Demand (BAU):6.34% Demand (HIG):7%
Demand (HIG):8%Production (BAU)
Production (HYG)
108
160
233
166
252
176
283
102
141
214
158
287
0
50
100
150
200
250
300
350
2019-202030-312047-48
Production/Demand (MT)
Fruits
Demand (BAU):6.34% Demand (HIG):7%
Demand (HIG):8%Production (BAU)
Production (HYG)
Figure 5.3e Demand-supply gap: Vegetables and Fruits
Sugar & products: Production of sugar and its products is expected to remain higher
than their demand throughout (Figure 5.3f), leaving a surplus of 3 million tonnes in
2030-31 and 6 million tonnes in 2047-48. The surpluses can be exported, and/or used for
ethanol production for blending with diesel and petrol.
Vegetables
Fruits 56
34
39
44
40
45
40
45
34
43
50
43
51
0
10
20
30
40
50
60
2019-202030-312047-48
Production/Demand (MT)
Sugar & Products
Demand (BAU):6.34% Demand (HIG):7% Demand (HIG):8%
Production (BAU) Production (HYG)
22
27
31
28
32
28
33
12
15
24
17
33
0
5
10
15
20
25
30
35
2019-202030-312047-48
Production/Demand (MT)
Edible oils
Demand (BAU):6.34%Demand (HIG):7%
Demand (HIG):8%Production (BAU)
Production (HYG)
Animal-source foods: In 2019-20, production of milk was sufficient to meet the domestic
demand. In 2030-31, the demand is likely to be met from domestic production (Figure
5.3g). However, if the economic growth accelerates, the production will be insufficient to
meet the demand.
Figure 5.3f Demand-supply gap: Sugar & Products and Edible Oils
Edible oils: In 2019-20, production of edible oils was about half of their demand
(Figure 5.3f), and this is expected to continue in 2030-31 as well. Augmentation of
oilseeds yield, and production from secondary sources can reduce the gap in the
short-run, and achieve self-sufficiency in the long-run. Nevertheless, it will require
significant technological intervention.
Sugar & Products
Edible oils 57
Egg production in the BAU scenario will exceed the projected demand in 2030-31(Figure
5.3g), and it may continue by 2047-48. However, the country may feel a shortage if
economic growth accelerates to 8%.
Presently, meat production surpasses its demand (Figure 5.3h). However, with increase
in income, its demand will increase faster than production. Production of meat in the
BAU scenario will be sufficient to meet the demand in 2030-31, but is likely to fall short
in 2047-48. However, in the HYG scenario, meat production in 2047-48 may surpass its
demand.
Fish demand is likely to be met by domestic production in 2030-31. But in the long
run, the growth in production needs to be augmented to meet the rising demand and
generate surpluses for exports.
Figure 5.3g Demand-supply gap: Milk and Eggs
5
8
16
9
18
10
21
6
11
19
10
21
0
5
10
15
20
25
2019-202030-312047-48
Production/Demand (MT)
Eggs
Demand (BAU):6.34%Demand (HIG):7%
Demand (HIG):8%Production (BAU)
Production (HYG)
186
294
480
186
308
527
186
329
606
198
308
478
198
310
581
0
100
200
300
400
500
600
700
2019-202030-312047-48
Production/Demand (MT)
Milk
Demand (BAU):6.34% Demand (HIG):7%
Demand (HIG):8%Production (BAU)
Production (HYG)
Milk
Eggs 58
Figure 5.3h Demand-supply gap: Eggs and Meat
7
12
21
12
24
13
29
9
12
18
14
30
0
5
10
15
20
25
30
35
2019-202030-312047-48
Production/Demand (MT)
Meat
Demand (BAU):6.34%Demand (HIG):7%
Demand (HIG):8%Production (BAU)
Production (HYG)
12
20
37
21
41
22
48
14
23
37
23
49
0
10
20
30
40
50
60
2019-202030-312047-48
Production/Demand (MT)
Fish
Demand (BAU):6.34%Demand (HIG):7%
Demand (HIG):8%Production (BAU)
Production (HYG)
Meat
Fish
HIGHLIGHTS
♦Food demand comprises the household demand and food away from home
(FAFH) demand, the demand for feed, seed, wastages and other uses. Food
cooked within household premises constitutes the largest component of total
food demand.
♦Overall food demand is expected to grow at an annual rate of 2.44% between
2019-20 and 2047-48. The growth will accelerate to 2.69 to 3.07% if the economy
grows at a faster rate. The growth would vary across the food commodities i.e
0.34% for rice to 5.42% for meat.
♦Total demand for foodgrains is projected at 402 million tonnes (mt) in 2047-48
under BAU scenario and 415-437 mt under HIG scenarios. Amongst foodgrains,
the growth in demand for maize, pulses and nutri-cereals will be significantly
higher than the growth in demand for rice and wheat. Pulses demand is projected
at 49-57 mt in 2047-48 under varied income growth scenarios. The demand for
vegetables and fruits is expected to be 365 mt and 233 mt, respectively in BAU
and 385-417 mt and 252-283 mt in HIG scenarios. The demand for sugar and 59
products is expected to remain at 44-45 mt in 2047-48. The demand for edible
oils is projected at 31-33 mt. The milk and milk products demand is projected
at 480 mt in BAU scenario and 527-606 mt in HIG scenarios in 2047-48. In the
BAU scenario, by 2047-48 the demand for eggs, meat and fish is estimated at
16, 21 and 37 million tonnes, respectively. In the HIG scenarios, it is expected to
be 18-21, 24-29 and 41-48 million tonnes in 2047-48.
♦At aggregate level, the quantity of daily food intake in 2011-12 was 31% less than
the recommended dietary allowance and the gap reduced to 22% in 2019-20.
By the year 2030-31, average daily food intake is likely to be at par with the
normative requirement and in 2047-48 it is expected to be 20% more. Intake of
few commodities like pulses, fruits, and vegetables will be insufficient in 2030-
31, whereas by 2047-48, consumption of all food commodities is expected to be
either at par or higher than their normative requirement.
♦The gross cropped area (GCA) is expected to increase at annual growth of
0.45 % during 2019-20 to 2047-48. The incremental acreage will come from
improvements in cropping intensity. Given the limited scope for area expansion,
the additional production to meet the domestic demand will come from yield
improvements. There exists considerable yield gap in most crops, which offers
scope to accelerate growth in the yield.
♦The foodgrains production is likely to be more than the demand in 2047-48
in BAU and HYG scenarios and the surplus can be disposed offshore to earn
foreign exchange. The surplus grains will be primarily contributed by rice
and wheat. With the growing consumers’ awareness and government focus,
demand of nutri-cereals is likely to go up and production will fall short of the
demand until area expansion and yield augmentation take place. In the BAU
scenario, maize production will fall short of their demand. However, in the HYG
scenario, its production is expected to be sufficient to meet the demand. This
necessitates harnessing yield potential in maize. Similarly, pulses production is
insufficient to meet the demand and the gap is expected to remain in BAU
scenario. Self-sufficiency in pulses is likely to be achieved if the current trend in
pulses area continues, and yield growth accelerates.
♦Presently production of fruits and vegetables fall short of their demand which
is expected to continue until acceleration in existing yield growth takes place.
Similarly, shortfall in the production of edible oils is expected to continue in
short run. Augmentation of oilseeds yield, and production from secondary
sources can reduce the gap in the short-run, and achieve self-sufficiency in the
long-run. Production of sugar and its products is expected to remain higher
than their demand. Domestic production will meet the demand of all animal-
source food except meat in BAU scenario. However, it will fall short of demand
if economy grows at higher than the usual rate. 60
Export Potential
Chapter 6
The recent period has observed a remarkable expansion in global agricultural trade, signaling
significant growth potential. This notable surge in agricultural trade holds the promise of
yielding substantial benefits, encompassing the facilitation of agricultural development,
alleviation of poverty, stabilization of prices, improvement in nutritional outcomes, and
optimization of resource utilization. The “Agricultural Export Policy 2018” is oriented towards
broadening the spectrum of the country’s export portfolio by fostering the promotion of
novel, indigenous, organic, and culturally distinctive agricultural products. This policy has
established the ambitious goal of achieving agricultural exports amounting to US$60 billion
by 2022 and further escalating to US$100 billion by 2025. As of 2021, India had already
surpassed the US$50 billion milestone in agricultural exports.
The earlier sections highlighting estimations of supply and demand suggest a probable
surplus that can be utilized to bolster exports. These projections outline diverse supply
possibilities across various scenarios, encompassing both business-as-usual conditions and
conditions fostering rapid growth. Within these scenarios, the potential for a surplus supply
beyond current demand exists, which could be channelized towards exports. To examine the
export prospects in rice and wheat, we have included the business-as-usual (BAU) approach
for assessing the available surplus for exports. Remaining surplus scenarios are given in
Appendix 6.1 to 6.5.
Table 6.1 Export surplus assessment (Food demand: Business as usual (6.34%) &
Production: Business-as-usual)
Surplus (Supply-Demand), Million tonnes
Product/ Commodities
2011-
12
2019-
20
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
Hypothesis
Foodgrains 17 22 28 42 43 46 54 Exportable
Cereals & Millets 18 25 32 46 47 50 56 Exportable
Rice 9 16 26 35 39 40 40 Exportable
Wheat 5 8 11 20 27 29 42 Exportable
Nutri-cereals 0 0 -3 -5 -8 -11 -16 Importable
Maize 4 2 0 -2 -9 -6 -6 Importable
Pulses -3 -3 -4 -4 -4 -4 -2 Importable
Animal Food 2 5 6 7 6 4 1 Exportable
Eggs 0 1 2 2 3 3 3 Exportable
Meat 1 2 1 1 0 -2 -4 Transitioning
Fish 1 2 3 3 3 2 1 Exportable
Milk 0 12 15 14 9 3 -2 Transitioning
Vegetables 2 -11 -14 -17 -16 -13 1 Importable
Fruits 0 -6 -13 -19 -23 -24 -19 Importable
Sugar & products 3 0 5 3 3 6 6 Exportable
Edible oil -9 -11 -12 -12 -11 -10 -7 Importable 61
Amid the ongoing emphasis on bolstering exports, significant shifts in the
composition of agricultural exports have emerged, driven by evolving global dietary
preferences. The categories experiencing steady expansion comprise rice, shrimps,
prawns, cane sugar, cotton, spices, among others. These commodities have not only
demonstrated consistent export growth over time but also hold a significant share
in the global export market.
Conversely, nutri-cereals, maize, and pulses are likely to fall into the category of
importable commodities due to changing consumer preferences favoring healthier
and more nutritious diets. Oilseeds will fall under importable hypothesis under all
possible scenarios. Eggs and fish also align with the exportable hypothesis. Fruits
and vegetables, driven by increasing demand, tend to be classified as importable
commodities. Dairy products also exhibit surplus in the business-as-usual scenario.
Finally, sugar and its derivatives emerge as commodities with long-term export
potential. These insights are examined in the subsequent sections, which delve into
the export potential of key agricultural commodities.
6.1 The Approach
1. The historical exports of selected commodities have also been modelled to
provide the futuristic trends in exports, if existing trends would prevail. Stochastic
models such as the autoregressive integrated moving average (ARIMA) model,
and machine learning techniques such as the artificial neural network (ANN)
method, have been employed for projecting the export trends
2
. For rice and
wheat, the projections are based on historical data on quantity from 1961 to 2021
from FAOSTAT. The projections of dairy and bovine meat are based on historical
data from 2001 to 2022 sourced from International Trade Statistics (INTRACEN).
ARIMA, being a linear time series model, is limited in its ability to effectively
capture the intricate nonlinear patterns present in a series. In contrast, ANN,
a data-driven machine learning technique, can comprehend the nonlinearity
inherent in the series
3
. Given the presence of such complexity and nonlinearity
within the export data, ANN has demonstrated superior performance in most
instances. Notably, ANN can be utilized for long-term forecasting as well
4
.
2. Export potential for selected commodities was drawn from the Export Potential
Map of the International Trade Centre (ITC). These assessments are based on an
2
Stationary of the series was checked by means of augmented dickey fuller (ADF) test. The series which were nonstationary
at level were undergone differencing to make them stationary. The order of auto regression (AR) and moving average (MA)
in ARIMA model have been selected based on the partial autocorrelation function (PACF) and autocorrelation function (ACF)
plots respectively. The best model was selected using the minimum information criterion value i.e. minimum value of Akaike
Information Criterion (AIC) and Baysian Information Criterion (BIC).
3
A series of algorithm is used to form a neural system of networks to act upon vast amount of data and process the data like
a human nervous system does. A multilayer ANN model consists of input, one or more hidden layer and output layer. Data is
fed to the input layer. By adjusting the connection weights between the input and hidden nodes data recess at hidden nodes.
After processing the data in hidden node, processed data is transferred to the output nodes through similar kind of inter-
connected network. From the output node final value is achieved. This is called feed-forward mode of the neural network
model. Thereafter, Back-Propagation Algorithm (BPA) starts to adjust the weight matrix between the input and hidden
layer and the hidden and output layer so that the output received from the whole ANN model meets our desired goal with
minimum error.
4
For ANN technique, the hyper parameter tuning was carried out to reach to the optimum combination resulting minimum
value of Root Mean Square Error (RMSE). Number of input lags in ANN has been decided using the autocorrelation structure
of the series. For the both the techniques, the residual diagnostic was carried out to check for adequacy of fitted model. The
assumptions of normality and independence of residuals have been checked. 62
export potential assessment
5
methodology developed by the ITC. The Export
Potential Indicator (EPI) signifies the total export potential for a given commodity
along with the potential harnessed. It helps countries to enhance exports in
existing markets and tap new markets. The facilitative measures for export by the
Government of India are anticipated to elevate the scale of exports and unlock
further levels of untapped potential. It is assumed that an additional 5 to 20% of
export potential will be harnessed between 2025 and 2047.
3. With the ongoing implementation of trade facilitation measures, a comprehensive
assessment of expected exports involves a calculation that combines the
projected exports with the additional potential that has been successfully realized
and harnessed. This calculation takes into account not only the anticipated
or projected export figures but also the capacity to unlock and capitalize on
additional export potential. It accounts for the potential growth and expansion
in exports that can be achieved by leveraging various trade facilitation strategies
and initiatives.
4. Anticipating an expansion of the surplus in the future, it is plausible that there
will be increased potential for further exports. Consequently, an evaluation of this
additional potential has been conducted by deducting the projected exports from
the projected surplus. Additionally, calculations have been made to determine the
extent to which the country will be able to utilize its potential by the year 2047.
5. The product mapping was done based on the Trade Balance Index (TBI) and
Revealed Symmetric Comparative Advantage (RSCA) of selected commodities.
The comparative advantage for a given product is based on the premise that the
trade pattern reveals the changes in relative price and non-price factors and is
indicative of the trade advantage and disadvantage. The revealed comparative
advantage (RCA) indices for selected commodities were calculated as
Where
evealed comparative advantage for i
th
country in j
th
product,
X
ij
value of export of j
th
product from i
th
country, = value of agricultural export of ith country,
X
wj
= value of global export of jth product, and = value of agricultural export globally.
5
Export potential assessments infer potential export values at ijk level from a multiplicative model based on two-dimensional
data:
where corresponds to the exporter i’s world market share in product The term is a measure of bilateral trade relative
to what trade would be if the exporter had the same share in world markets as it has in market while reflects the
total imports indicating that potential exports correspond to actual exports without friction (ITC, 2020). 63
RCA value lies between 0 and ∞. An i
th
country is said to have a comparative advantage
in the production of j
th
product if the value of exceeds ‘1.’ The revealed symmetric
comparative advantage (RSCA
ij
) index can be calculated as:
RSCA
ij
= (RCA
ij
-1) / (RCA
ij
+1)
The RSCA
ij
index varies from ‘-1’ to ‘+1.’ An RSCA
ij
value of “more than zero” indicates that
ith country has a comparative advantage in jth product. In contrast, an RSCA
ij
value of
“less than zero” indicates a comparative disadvantage.
The TBI helps analyze whether a particular country specializes in exports or imports for
a given crop or category. TBI is formulated as:
The TBI helps analyze whether a particular country specializes in exports or imports for
a given crop or category. TBI is formulated as:
TBI
ij
= (x
ij
-m
ij
) / (x
ij
+m
ij
),
Where,
TBI
ij
denotes a trade balance index of i
th
country for j
th
product,
x
ij
represents exports of j
th
product from i
th
country, and
m
ij
represents imports of j
th
product by i
th
country.
TBI values range from ‘-1 to +1.’ If the country is only importing, TBI is ‘-1.’ In contrast, if a
country only exports, TBI is ‘+1.’
The selected products were mapped based on the RSCA and TBI, and classified into
four quadrants (Box 1). Quadrant I, Group A comprises products with positive trade
balance and comparative advantage. This is the most favorable quadrant and represents
commodities highly suitable for exports. Quadrant II, Group B includes products with
a comparative advantage but without exportable surpluses (indicated by the negative
trade balance). Quadrant III, Group D is the most unfavorable group: it includes products
with no comparative advantage along with negative trade balance. Finally, Quadrant IV,
Group C comprises products with a positive trade balance but no comparative advantage
in exports. In the long run, commodity movements may happen from one Quadrant to
the other: a shift from Group B to Group A would require generating exportable surpluses
with appropriate technological interventions to enhance productivity and product
quality. In contrast, a shift from Group C to Group A would require policy facilitation to
harness the export potential and enhance comparative advantage.
Box 1. Product mapping scheme
Quadrant I (Group A)
TBI>0, RSCA>0
Net exporter
Comparative advantage
Quadrant II (Group B)
TBI<0, RSCA>0
Net importer
Comparative advantage
Quadrant IV (Group A)
TBI>0, RSCA<0
Net exporter
Comparative disadvantage
QuadrantIII(Group B)
TBI<0, RSCA<0
Net importer
Comparative disadvantage
Source: Widodo (2009). 64
6.2 Commodity Prospects
6.2.1 Rice
India’s strategic efforts to expand its rice exports by exploring new opportunities in
different countries and markets have begun to yield positive outcomes. Non-Basmati
rice exports also demonstrated growth. This remarkable progress can be attributed to
the effective synergy and collaboration among various stakeholders, including farmers,
exporters, and government agencies, all working together to boost exports.
The worldwide consumption of rice has shown a gradual increase in recent years,
reaching approximately 520 million tonnes in 2021-22, up from 437.18 million tonnes
in 2008-09. In 2021, the global rice export market was valued at US$ 27.13 billion, with
India leading at US$ 9.6 billion, followed by Thailand at US$ 3.3 billion and Vietnam at
US$ 3 billion. As the premier exporter, India has experienced a remarkable growth of 14%
in volume from 2017 to 2021, coupled with a 7% growth in value. In a historic milestone,
India achieved exports of 21.5 million tonnes of rice in 2021, surpassing the combined
shipments of the next four major rice-exporting nations: Thailand, Vietnam, Pakistan,
and the United States.
The continuous escalation of the revealed comparative advantage in rice exports serves
as a testament to India’s influential presence in the global market. In the initial stages,
these values demonstrated a downward trajectory, experiencing a decline from 7.31 to
4.62 in the year 2010. However, a notable and consistent upward trend has been observed,
signifying a substantial resurgence in India’s competitive advantage. Remarkably, India’s
comparative advantage in rice exports surged to an impressive 10.82 by the year 2021.
Table 6.2 Prospects for rice exports
Million Tonnes
6
NNETAR is the neural network based autoregressive model used for export projections. The figures in parenthesis represent
p, d, q parameters in autoregressive models.
 Particular Details  2025 2030 2035 2047
Supply (BAU)
Sourced from computa-
tions in previous section
A 133 145 150 154
Demand (BAU)
Sourced from computa-
tions in previous section
B 107 110 111 114
Surplus (Supply-Demand) 
C=A-B 26 35 39 40
Exports @ BAU Scenario
(Projected with NNETAR
6

(9,6,1))
Computed based on ma-
chine learning model
D 20.2 27.9 29.5 30.07
Export potential tapped
(%)
Sourced from INTRACEN
Trade Potential
E    
Tapping the untapped
potential (%)
Assumptions F 5 10 15 20
Potential targetted (%) ComputedG 60 65 70 75
Expected level of exports
Projected exports+extra
potential tapped
H 22.5 32.5 36.4 39.3
Further scope for exports Computed
I=C-H 3.5 2.5 2.6 0.7
Potential tapped with
additional surplus (%)
 As % of maximum
potential as of 2022 (46.15
million tonnes in this case)
J 56.3 75.9 84.5 86.7 65
To comprehend India’s potential in rice exports, an in-depth analysis was conducted. The
surplus, assessed on the basis of projected supply and demand, is poised for significant
expansion, surging from 26 million tonnes in 2025 to a formidable 40 million tonnes by
2047 (Table 6.2).
A neural network model has been applied using time series data, incorporating lagged
values as inputs, to forecast India’s prospects in rice exports within a “business as usual”
(BAU) scenario, which assumes the continuity of historical trends in food preferences.
The anticipated exports portray a gradual increase, culminating at 30.07 million tonnes
by the year 2047. Till date, India has harnessed only 55% of the total export potential in
rice. However, the yield advancements will generate huge surpluses to abridge most of
this potential by 2047.
While India’s recent accomplishments in rice exports are commendable, they raise
pertinent questions about the sustainability of rice exports, given the emphasis on a
“green supply chain” and diversification of rice for alternative uses. This stresses on the
need to explore untapped avenues to unlock India’s full export potential in this regard.
6.2.2 Wheat
Wheat stands as one of the most significant and extensively cultivated cereal crops
across the globe, serving as a fundamental grain in the diets of numerous nations.
Moreover, it ranks among the most traded agricultural commodities. Notably, the global
wheat market has experienced substantial growth over the past two decades, with
global wheat exports witnessing a remarkable surge of 98 million tonnes from 2003,
culminating in substantial export of 211.43 million tonnes in 2022.
A notable contributor to this recent expansion in wheat exports is the emergence of the
Black Sea countries, comprising Russia, Ukraine, and Kazakhstan, as key players in the
global wheat market. The leading wheat-exporting nations worldwide include Australia,
Canada, France, Russia, the United States, and Ukraine, collectively responsible for
approximately 77% of the total wheat exports (Table 6.3). Although Russia emerged as
a significant exporter post-2015, its export volumes have shown a gradual decline since
2020. Conversely, the USA and Australia have maintained a consistent presence in the
global market.
India, despite its status as the world’s second-largest wheat producer after China, contributing
13.53% to global wheat production, has held less than a 3% share of the global wheat exports
in 2022. Historically, India had played a relatively minor role in the global wheat trade until
the period of 2020-21, with wheat exports amounting to less than 0.3 million tonnes between
2016 and 2019. However, subsequent years have seen a notable surge in exports.
This upsurge in India’s wheat exports can be attributed to the trade opportunity arising
from global uncertainties triggered by the Russia-Ukraine conflict, coupled with surplus
production, leading to a significant boost in wheat exports during 2021-22. India, facing
the unique challenge of vulnerability to climate aberrations, fluctuates between the
roles of a net exporter and a net importer in the global wheat market. Continued global
population growth stresses on the pressing need to bolster wheat trade to ensure global
food security. In response to heightened international demand for wheat due to the
Ukraine conflict, India exported record-breaking quantity of wheat in 2022-23. 66
Table 6.3 Prospects of wheat exports
Million Tonnes
Table 6.3 Prospects of wheat exports
 Particular Details  2025 2030 2035 2047
Supply (BAU)
Sourced from previ-
ous section
A 117 131 141 160
Demand (BAU)
Sourced from previ-
ous section
B 106 111 115 119
Surplus (Supply-Demand)  C=A-B 11 20 27 42
Exports @ BAU Scenario (Pro-
jected with NNETAR (11,5,1))
Computed based
on machine learning
model
D 1.44 3.27 1.7 4.5
Export potential tapped (%)
Sourced from INTRA-
CEN Trade Potential
E    
Tapping the untapped potential
(%)
Assumptions F 5 10 15 20
Potential targeted (%)Computed G 66 71 76 81
Expected level of exports
Base exports+extra
potential tapped
H 2.0 4.3 3.3 6.6
Further scope for exportsComputed I=C-H 9.0 15.7 23.7 35.4
Potential tapped with addition-
al surplus (%)
 As % of maximum
potential as of 2022
(10.6 million tonnes in
this case)
J 103.4188.0253.8 394.8

As far as wheat export prospects are considered, the surplus, determined by estimates
of demand and supply, is projected to experience modest growth, increasing from 11
million tons in 2025 to 42 million tons in 2047. A neural network model was employed,
utilizing time series data with lagged values as inputs, to project India’s wheat export
possibilities while accounting for a business-as-usual (BAU) scenario. The anticipated
exports, however, suggest fluctuations over time, with estimates indicating a gradual rise
in India’s wheat exports from 3.27 million tons in 2030 to 4.5 million tons in 2047.
It is established that India has tapped approximately 60% of its potential in wheat exports.
Given India’s historical position as a relatively intermittent participant in the global wheat
export market, the extent of its wheat export potential remains largely underestimated.
Moreover, the potential for wheat exports from India is expected to experience a notable
upsurge in conjunction with the steady escalation in wheat surpluses within the country.
To fully leverage its competitive advantage, India must actively explore untapped avenues
to maximize its potential in the global wheat export market.
6.2.3 Dairy
The global dairy export market is highly concentrated. Germany remains the largest
exporter of dairy products with a share of 15%, which is followed by France, New Zealand,
the Netherlands, Belgium, USA and Denmark. Notably, Germany also holds the position
of the world’s primary dairy importer, commanding a significant 10% share. India has
traditionally focused on exporting skim milk powder, along with butter and fats. However,
there has been a recent surge in the export of cheese, indicating a diversification in
India’s dairy export portfolio. 67
Despite being the largest producer of milk globally, India’s contribution to the skim milk
powder market remains minimal, indicating a gap in the country’s processing capabilities.
The RCA values for skim milk powder have consistently remained below one between
2003 and 2022, highlighting India’s lack of competitiveness in this sector. While India
maintains a surplus, it has challenges in establishing a strong global competitive position.
The share of butter and fats in exports presents a consistent expansion over the years,
covering a major share in 2022 dairy exports. However, the RCA values for butter and
fats have consistently remained below one, indicating a lack of comparative advantage
for India in this segment.
The dairy exports are highly volatile. The projections indicate that the dairy exports
would be less than one million tonne in terms of milk equivalent (Figure 6.1). Expanding
into developing economies, comprehending indigenous preferences, and forging global
partnerships have the potential to enhance market penetration. Increasing exportable
surplus through enhanced breeding and feeding programs is pivotal in maximizing
foreign exchange earnings from the dairy sector. Nevertheless, the Indian dairy industry
faces constraints such as limited milk processing capabilities, elevated transportation
costs, and stringent food safety regulations, which require immediate attention for
sustainable growth.
Figure 6.1 Dairy Products, milk equivalent (Million Tonnes)

Note: The projections are based on NNETAR (9,5,1)
6.2.4 Bovine Meat
India’s vibrant livestock sector, buoyed by continual economic growth and a rise
in domestic income levels, has propelled the demand for livestock products to
unprecedented heights, underlining the country’s rich diversity in this domain. This surge
in demand has catalyzed a remarkable expansion in livestock production over the last
two decades, particularly geared towards meeting the requirements of the global export
market. Notably, India has established its position as the largest exporter of buffalo meat
globally, signifying its robust competitive advantage in this sector. 68
India’s RCA in the exports of bovine meat on the global stage is quite distinct. In 2000,
the world’s top five beef exporters were Australia, the United States, the European
Union, Canada, and Brazil. However, the landscape has evolved over time, with India
progressively overtaking and securing a leading position, alongside Australia, Brazil,
and the United States, within the top five exporters. The international market for Indian
bovine meat experienced a substantial upswing in exports from 2003 to 2012. However,
this growth trajectory was interrupted in 2012, after which they began to decline. The
momentum further gained in 2020 indicating an upsurge.
In 2022, global bovine meat production was projected to reach 73.9 million tonnes,
with India contributing 1.04 million tonnes. The projections follow the historical cyclical
pattern and do not indicate an appreciable increase (Figure 6.2), which may be quite
consistent with the domestically induced demand for livestock products.
Figure 6.2 Prospects of bovine meat exports (million tonnes)
Note: The projections are based on NNETAR (5,3,1)
Till date, the country has been able to harness approximately 80% of export potential in
this category, which is quite encouraging as compared to other exportable commodities.
Sustaining exports in this category would require adherence to improved food safety
measures, effective disease management, and more resilient supply chains.
6.2.5 Eggs
Eggs and egg-based products have gained widespread popularity worldwide due to
their nutritional value and adaptability. Notably, the top five fresh egg exporters are the
Netherlands, Poland, Turkey, Mainland China, and Germany, collectively accounting for
58.6% of the total fresh egg export in 2022. The poultry sector stands as one of India’s most
promising segments. India’s egg production has risen from 78.48 billion in 2014-15 to 129.60
billion in 2021-22.This growth has propelled India to become the world’s third-largest egg
producer, after China and the USA. Among the poultry products exported from India, whole
eggs in their shell occupied a central position, followed by liquid and dried egg products. 69
India’s involvement in global poultry trade has historically been quite limited. In 2003,
when worldwide poultry meat exports reached approximately 10 million tonnes, India’s
poultry exports amounted to just 6.9 thousand tonnes, representing a mere 0.07% of
the total global exports. There was sharp decline in the RCA after 2004 signifying the
diminishing competitiveness of eggs in the international market.
The mapping of trade balance and comparative advantages exhibits the transition
from the first quadrant to the second quadrant. In this quadrant, positive RSCA values
indicate a comparative advantage in the global market, but negative TBI values signify
a reduction in exportable surplus over time. A holistic approach to improving egg
production is crucial to fully harness India’s potential in this sector. A concerted effort,
leveraging innovation, technology, and strategic policies, is the key to unlocking India’s
untapped potential in this promising and dynamic sector.
6.2.6 Fish and Crustaceans
India’s crustacean sector, particularly its shrimp and prawn exports, has established
itself globally leveraging its natural resources and a robust aquaculture industry to
meet the international demand. India has made significant strides in crustacean exports,
experiencing a remarkable 20% surge in 2022. Frozen shrimp continue to dominate
exports, while dried fish items also demonstrating substantial growth. The country now
exports seafood to more than 130 countries. Our sustained partners in crustaceans
include the USA, China, Japan, the European Union, Southeast Asia, and the Middle East.
Indian seafood exports to the United States have witnessed a surge in recent years,
capturing a share of approximately 30%.
India’s competitive edge in global crustacean exports remains robust, as evidenced by
consistently high RCA values surpassing one. Though affected by the disruptions caused
by the Covid-19 pandemic, the trajectory has shown resilience, promising a positive
outlook in the long run.
Quality issues in India’s fish exports have been a concern. Inconsistencies at various
stages of the value chains have led to the concerns about the overall quality and safety
of the exported fish products. Salmonella remains one of the biggest reasons for export
rejection in crustacenas. The presence of veterinary drug residues is found the main
cause for the rejection of export consignments of shrimp and prawns. Veterinary drugs
are typically used for the treatment and prevention of parasitic and microbial diseases
in fishery and aquaculture. Misuse or overuse of these drugs can result in high levels of
residues in fishery products, leading to export rejections. 70
HIGHLIGHTS
♦India’s prominence in the global market is steadily gaining momentum, as evident from
its growing presence in exporting specialized products like Basmati rice, non-Basmati
rice, spices, and shrimps. The prevailing scenario stresses the importance of creating
an ecosystem that focuses on “market intelligence” tailored for specific sectors and
commodities. It is imperative to meticulously evaluate the competitiveness, market
dynamics and potential destinations, logistics, and traceability of value chains
and supply chains tailored to individual commodities. A meticulous evaluation of
competitiveness, market dynamics, potential target destinations, as well as the
intricacies of logistics and the traceability of value chains and supply chains for
export-oriented commodities, is of paramount importance.
♦Rice and wheat emerge as commodities with long-term export potential. These
commodities are crucial from food security angle and require strategic handling to
fully exploit their export capabilities, given the expected generation of significant
export surpluses due to evolving demand patterns and advancements in technology
and skills.
♦Nutri-cereals, maize, and pulses fall into the category of importable commodities
driven by a growing preference for healthier and more nourishing dietary choices.
Fruits and vegetables, driven by increasing demand, also fall under importable
hypothesis. Dairy products exhibit surplus in the business-as-usual scenario. Sugar
and its derivatives emerge as commodities with long-term export potential.
♦While India’s recent accomplishments in rice exports are commendable, they raise
pertinent questions about the sustainability of rice exports, given the emphasis on
a “green supply chain” and diversification of rice for alternative uses. The mounting
virtual water exports triggered by rice exports underscore the pressing need to
devise “regional crop plans” that can unlock India’s full export potential in rice.
♦Food safety issues are critical in sustaining exports. The rejection rates for agricultural
commodities and processed food exports from India to both the USA and European
Union (EU) countries, which are our major partners, have displayed an upward
trajectory. The major factors leading to the rejection of export consignments include
pesticide residues, microbial contaminations, heavy metals, the use of unsafe colors
or additives, inappropriate labeling or misbranding, filth, insanitary conditions or
controls, and more. Pesticide residues have emerged as a significant factor leading
to the rejection of exported shipments comprising rice, seed spices, vegetables,
fruits, oilseeds, herbs, etc in both the US and EU markets. The presence of veterinary
drug residues has been identified as the primary cause for the rejection of shrimp
and prawn exports. Salmonella continues to be a significant contributor to export
rejections.
♦Sensitization and capacity building at different stages of the value chain would
sustain the export trajectory. Research and development institutions can play a
vital role in strengthening the capabilities of value chain participants. Concurrently,
trade facilitating organizations such as APEDA and EIC must proactively address
these quality concerns, ensuring strict compliance with sanitary and phyto-sanitary
standards. 71
Input Demand Projections
Chapter 7
This chapter assesses the future demand for inputs including fertilizers, pesticides,
seeds and credit. The projection methods include combination of the univariate time
series models (based on exponential growth curves where input demand is modeled as
a function of its own lagged values), and the regression-based approach (where input
demand is modeled as a function of underlying explanatory variables).
7.1 Fertilizers
Fertilizer demand projections are made for 2025-26, 2030-31, 2035-36 and 2047-48
using the coefficients from Equation (1) given in the Appendix 7.1. Based on the following
assumptions four scenarios have been developed:
1. All drivers of fertilizer use (i.e., irrigated area, output prices and fertilizer prices) are
assumed to grow at their historical growth rates (2001-02 to 2018-19) (Business
as usual scenario).
2. Irrigated area is assumed to grow 10% higher than its historical growth rate (i.e.,
1.1*historical growth) and all other variables to grow as usual (Scenario 1).
3. Prices of food articles and fertilizer are assumed to grow 10% higher than their
historical growth rate, and all other variables to grow as usual (Scenario 2).
4. All the drivers of fertilizer consumption grow 10% higher than their historical
growth rate (Scenario 3).
The Government of India has been implementing several programmes to reduce excessive
use of fertilizers. Hence, in addition to the above scenarios, we also look for the likely
effect of such programmes on the reduction in fertilizer consumption, and consequently
in fertilizer demand.
The estimates of the projected demand are given in Table 7.1.
In the BAU scenario, the fertilizer demand is estimated to increase to 386 lakh tonnes in
2030-31, and further to 604 lakh tonnes in 2047-48. Their per hectare consumption is
projected to increase to 188 kg by 2030-31 and to 283 kg in 2047-48.
When the irrigated area increases 10% higher than its historical growth, fertilizer demand
increases marginally to 393 lakh tonnes in 2030-31 and 629 lakh in 2047-48. So does
their per hectare consumption, 191 kg in 2030-31 and 295 kg in 2047-48. This is because
the expansion of irrigation leads to an increase in the cropping intensity, hence more use
of fertilizers.
In the scenario when the prices of output and fertilizers are assumed to grow 10% higher
than the historical growth rates, the fertilizer demand will be slightly more than that in
the BAU scenario. So is their per hectare consumption. This is because an increase in
food prices induces more consumption of fertilizers, while an increase in fertilizer prices
has an opposite effect. 72
Further on the assumption that irrigated area, output prices, and fertilizer prices
experience a 10% higher growth over their historical growth rates, the estimated fertilizer
demand is more than in any other scenario; 396 million tonnes in 2030-31 and 640 million
tonnes in 2047-48. Their per hectare consumption is projected to be 193 kg in 2030-31
and 300 kg in 2047-48. This is because while expansion of irrigated area and increase in
food prices work in the same direction and reinforce each other, the increase in fertilizer
prices has an opposite effect.
Table 7.1: Projected demand for fertilizers
Baseline Scenario (all variables increase at historical growth rates)
year
Fertilizer demand (Lakh tonnes)Fertilizer use (kg/ha)
No ef-
fect of
fertilizer
reduc-
tion
pro-
grams
20%
lower
growth
infertil-
izer con-
sump-
tion
30% lower
growth in
fertilizer
consump-
tion
50%
lower
growth in
fertilizer
consump-
tion
No
effect of
fertilizer
reduc-
tion pro-
grams
20% lower
growth
infertilizer
consump-
tion
30%
lower
growth in
fertilizer
consump-
tion
50% lower
growth in
fertilizer
consump-
tion
2019-
20
289148.4
2025-
26
339 328 323 313 166.8 161.7 159.2 154.3
2030-
31
386 365 354 334 188.1 177.6 172.6 162.9
2035-
36
440 405 389 357 212.0 195.1 187.1 172.0
2040-
41
502 450 426 382 239.0 214.2 202.8 181.6
2047-
48
604 522 485 419 282.6 244.3 227.0 196.0
Scenario 1: Irrigation increases at 10% higher growth rate than baseline
year
Total Fert Cons (Lakh tons)Fert cons per ha (kg/ha)
No ef-
fect of
fertilizer
reduc-
tion
pro-
grams
20%
lower
growth
infertil-
izer con-
sump-
tion
30% lower
growth in
fertilizer
consump-
tion
50%
lower
growth in
fertilizer
consump-
tion
No
effect of
fertilizer
reduc-
tion pro-
grams
20% lower
growth
infertilizer
consump-
tion
30%
lower
growth in
fertilizer
consump-
tion
50% lower
growth in
fertilizer
consump-
tion
2019-
20
289148.4
2025-
26
342 331 325 315 168.5 163.1 160.4 155.2
2030-
31
393 370 359 338 191.3 180.1 174.8 164.4
2035-
36
451 413 395 362 217.2 199.0 190.4 174.3
2040-
41
518 462 436 388 246.6 219.8 207.4 184.7
2047-
48
629 540 500 428 294.6 252.6 233.9 200.4 73
The projected demand for fertilizers may change depending on the availability of their
substitutes, improvements in nutrient-use efficiency, and government policies and
incentives. Nitrogenous fertilizers play a key role in enhancing crop yields, but their
excessive use leads to atmospheric pollution, and N2O emission causing global warming.
It also causes nitrate pollution in the groundwater and marine ecosystems through
runoff. Nitrogen cycle management is, thus, an essential for sustainability of agriculture.
To reduce the excessive use of agrochemicals, there is a gradual shift in the policy to
reduce fertilizer consumption and improve the nutrient-use efficiency through several
nutrient management programmmes as listed in Appendix 7.2.Given these programmes,
Scenario 2: Input and Output prices increase at 10% higher growth rate than baseline
year
Total Fert Cons (Lakh tons)Fert cons per ha (kg/ha)
No ef-
fect of
fertilizer
reduc-
tion
pro-
grams
20%
lower
growth
infertil-
izer con-
sump-
tion
30% lower
growth in
fertilizer
consump-
tion
50%
lower
growth in
fertilizer
consump-
tion
No
effect of
fertilizer
reduc-
tion pro-
grams
20% lower
growth
infertilizer
consump-
tion
30%
lower
growth in
fertilizer
consump-
tion
50% lower
growth in
fertilizer
consump-
tion
2019-
20
289148.4
2025-
26
340 329 324 314 167.5 162.3 159.7 154.6
2030-
31
389 367 356 336 189.4 178.6 173.5 163.5
2035-
36
445 408 391 359 214.1 196.6 188.4 172.9
2040-
41
509 455 430 384 242.0 216.5 204.7 182.9
2047-
48
614 529 491 422 287.4 247.6 229.8 197.8
Scenario 3: Irrigation and Prices increase at 10% higher growth rate than baseline
year
Total Fert Cons (Lakh tons)Fert cons per ha (kg/ha)
No ef-
fect of
fertilizer
reduc-
tion
pro-
grams
20%
lower
growth
infertil-
izer con-
sump-
tion
30% lower
growth in
fertilizer
consump-
tion
50%
lower
growth in
fertilizer
consump-
tion
No
effect of
fertilizer
reduc-
tion pro-
grams
20% lower
growth
infertilizer
consump-
tion
30%
lower
growth in
fertilizer
consump-
tion
50% lower
growth in
fertilizer
consump-
tion
2019-
20
289148.4
2025-
26
343 332 326 316 169.2 163.6 160.9 155.5
2030-
31
396 372 361 339 192.7 181.2 175.6 165.1
2035-
36
456 417 398 364 219.4 200.6 191.8 175.2
2040-
41
525 467 440 391 249.8 222.1 209.4 186.0
2047-
48
640 547 506 432 299.6 256.1 236.8 202.1 74
including the reduction of subsidies and consequent rise in fertilizer prices, we develop
three plausible future scenarios for fertilizer demand with a 20%, 30% and 50% lower
growth of their consumption from their historical rates. The fertilizer demands for these
scenarios are given in Table 7.1.
• 20 % lower growth in fertilizer consumption
With a 20% lower growth in their consumption, the fertilizer demand is projected at 365
lakh tonnes in 2030-31, and 522 lakh tonnes in 2047-48 in the BAU scenario. The per
hectare consumption is estimated at 178 kg, gradually increasing to 244 kg in 2047-48.
If the irrigated area expands at 10% higher growth, then the fertilizer demand increases
marginally to 370 lakh tonnes in 2030-31 and 540 lakh tonnes in 2047-48. Accordingly,
their per hectare consumption will increase to 180 kg and 253 kg, respectively.
In case, the prices of output and fertilizer increase 10% higher than their historical growth
rates, the demand for fertilizers would decline marginally to 367 lakh tonnes in 2030-31
and 529 lakh tonnes in 2047-48, and their per hectare consumption to 179 kg in 2030-31
and 248 kg in 2047-48.
If the irrigated area, food prices and fertilizer prices grow 10% higher than their historical
growth, the fertilizer demand is expected to be 372 lakh tonnes in 2030-31 and 547
lakh tonnes in 2047-48; and their per hectare consumption will be 181 kg and 256 kg,
respectively.
• 30 % lower growth in fertilizer consumption
In the BAU scenario, further reduction in the growth of fertilizer consumption by 30%,
their fertilizer demand declines to 354 lakh tonnes in 2030-31, and gradually to 485 lakh
tons in 2047-48. Their per hectare consumption will be 173 kg in 2030-31 and 227 kg in
2047-48.
If the irrigated area were to expand at a 10% higher growth over its historical growth rate,
the demand for fertilizers will be slightly more; 359 lakh tonnes in 2030-31 and further to
500 lakh tonnes in 2047-48, and their per hectare consumption will be 175 kg and 234
kg respectively.
When the prices of output and of fertilizers increase at a 10% higher growth over their
historical growth rates, fertilizer demand is projected to be slightly less; 356 lakh tonnes
in 2030-31 and 491 lakh tons in 2047-48. The per hectare consumption will be 174 kg and
230 kg respectively in 2030-31 and 2047-48.
If the irrigated area, food prices and fertilizer prices were to grow at a rate 10% higher
than their historical growth, 361 lakh tonnes of fertilizers will be required in 2030-31 and
506 lakh tonnes in 2047-48. Their corresponding per hectare usage will be 176 kg and
237 kg respectively.
• 50 % lower growth in fertilizer consumption
If the government programmes are more effective in reducing the growth in fertilizer
consumption say by 50%, the demand for fertilizers is projected to be 334 and 419 lakh
tonnes in 2030-31 and 2047-48 respectively. Their per hectare consumption will be 163
kg in 2030-31 and 196 kg in 2047-48. 75
If the irrigated area were to increase at a growth 10% higher than its historical trend, the
country will require 338 lakh tonnes of fertilizers in 2030-31 and 428 lakh tonnes in 2047-
48, their per hectare consumption will be 164 kg in 2030-31 and 200 kg in 2047-48.
In case the prices of output and fertilizers were to increase at a rate 10% higher over their
historical rates, the projected demand for fertilizers will be 336 lakh tonnes in 2030-31
and 422 lakh tonnes in 2047-48.
If all the drivers of fertilizer consumption increase at a rate 10% higher over their historical
growth rates, the demand for fertilizers will be 339 lakh tonnes in 2030-31 and 432 lakh
tonnes in 2047-48.
7.2 Pesticides
The pesticide demand is projected using the coefficients from Equation (2) given in the
Appendix 7.1. In the BAU scenario, the demand for pesticides is projected to increase be
79233 tonnes by 2030-31 and 118405 tonnes by 2047-48 (Table 7.2). Accordingly, their
per hectare consumption will be 0.39 kg in 2030-31 and 0.55 kg in 2047-48.
Table 7.2 Projected demand of pesticides
Year
Total pesticide use (tonnes)Pesticide use (kg/ha)
Business as
usual
Cotton area declines at
10% from its historical
trend
Business as
usual
Cotton area declines
at 10% from its
historical trend
2019-20 61097-0.31-
2025-26 70403641560.350.32
2030-31 79233680620.390.33
2035-36 89170722050.430.35
2040-41 100353766010.480.36
2047-48 118405832090.550.39
However, if the growth in area under cotton, the main user of pesticides, declines by 10%
over its historical growth rate, the total consumption of pesticides will fall significantly
to 68062 tonnes in 2030-31, and further to 83209 tonnes in 2047-48. Accordingly, there
will be a decline their per hectare consumption.
7.3 Seed
Seed demand is projected for each crop using the following formulae:
Where, 76
Projections of seed demand for crops are presented in Appendix 7.3a to 7.3e for two
scenarios: the current SRR projected into future, and 100% SRR. Table 7.3. summaries the
total seed demand. In case of projected SRR, the demand for certified seeds in 2030-
31 is expected to be 34068 thousand quintals, which will increase to 49701 thousand
quintals in 2047-48. The quantity of foundation seed required is estimated at 1030
thousand quintals in 2030-31, and 1531 thousand quintals in 2047-48.The breeder seed
requirement is estimated at 37649 quintals in 2030-31, which will increase to 55483
quintals by 2047-48.
Table 7.3: Seed demand to 2047-48
000’ quintals
Projected SRR100% SRR
CertifiedFoundation Breeder CertifiedFoundation Breeder
2025-26 30710 925 34 75652 2403 93
2030-31 34068 1030 38 78571 2509 98
2035-36 37863 1151 42 81922 2628 103
2040-41 42213 1291 47 85795 2762 108
2047-48 49701 1531 55 92335 2981 118
With 100% SRR, the seed demand is much larger. The demand for certified seed in 2030-
31 at 78571 thousand quintals which will gradually increase to 92335 thousand quintals
by 2047-48.The foundation seed requirement will increase to 2509 thousand quintals in
2030-31 and 2981 thousand quintals in 2047-48.The breeder seed demand is projected
to be 93 thousand quintals in 2030-31 and 118 thousand quintals in 2047-48.
7.4 Credit
Demand for credit is projected based on its historical growth during 2001-02 to 2019-
20. Since, the purpose and drivers of the short-term and long-term credit are different,
a regression-based approach may not be appropriate to project their future demand.
Credit demand has been estimated on two assumptions. One, the continuance of the
past trend in the future as well. Two, the credit requirements moderate over the next
two decades, which is a more realistic assumption given the declining contribution
of agriculture to gross domestic product. On the assumption of the continuance of
historical trend in credit supply, the total demand for credit (short term plus long term)
is estimated at Rs 7022555 crores in 2030-31 and Rs 159936347 crores in 2047-48 (Table
7.4). The demand for short-term credit is projected at Rs 1981457 crores in 2030-31 and
to Rs 8228215 crores in 2047-48. The demand for long-term credit is likely to be Rs
5041098 crores in 2030-31 and to Rs 151708132 crores in 2047-48.
These estimates appear too steep after 2040-41 to be realistic. Thus, it is assumed that
the growth in credit demand to moderate to 70% of its historical growth between 2030-
31 and 2040-41, and later to 50%. Accordingly, the total credit demand (short term plus
long term) is estimated at Rs 4260769 crores in 2030-31 and Rs 13151319 crores in 2047-
48 (Table 7.4). For 2030-31, the short-term credit demand is projected at Rs 1530225
crores in 2030-31 and to Rs 2593467 crores in 2047-48. The long-term credit demand is
estimated at Rs 2730544 crores in 2030-31 and Rs 10557852 crores in 2047-48. 77
Table 7.4: Credit demand to 2047
Rs crores
Year
At historical rate of growth At moderating rate of growth
Short-term Long-term Total Short-term Long-term Total
2019-20 825151 567579 1392730 825151 567579 1392730
2025-26 1325573 1861869 3187442 1325573 1861869 3187442
2030-31 1981457 5041098 7022555 1530225 2730544 4260769
2035-36 2982932 13692362 16675294 2036979 5600437 7637416
2040-41 4525612 37265324 41790936 1937284 5065978 7003262
2047-48 8228215 151708132159936347 2593467 10557852 13151319
HIGHLIGHTS
♦In the scenario of 10% acceleration in the drivers of growth in fertilizer consumption
((i.e., irrigated area, fertilizer price, and output price)), the demand for fertilizers is
expected to increase to 396 lakh tonnes by 2030-31 and 640 lakh tonnes by 2047-48.
The corresponding increase in their per hectare consumption will increase from 193 kg
by 2030-31 and to 300 kg in 2047-48.
♦In the scenario of 50% deceleration in the growth of fertilizer consumption on accout
of several schemes (i.e., Soil Health Card, micro-irrigation including fertigation, Neem
coated urea, natural farming, biofertilizer, etc.) and 10% acceleration in the growth
in its drivers, the demand for fertilizers is projected to be less; 339 lakh tonnes in
2030, and 432 lakh tonnes in 2047-48. Accordingly, their per hectare consumption is
expected to be 165 kg in 2030-31 and 202 kg in 2047-48.
♦In the BAU scenario, the demand for pesticides is projected to increase to 79,233
tonnes in 2030-31 and to 1,18,405 tonnes in 2047-48. The per hectare consumption
is estimated at 0.39 kg in 2030-31 and 0.55 kg in 2047-48. On the assumption of
a decline of 10% in the growth in cotton area (largest consumer of pesticides), the
demand for pesticides will be less; 68,062 tonnes in 2030-31 and 83,209 tonnes in
2047-48. Accordingly, their per hectare consumption is projected at 0.33 kg in 2030-
31 and 0.39 kg in 2047-48.
♦Given the projected seed replacement rates (SRR) for different crops, the demand
for certified seeds is estimated at 34,068 thousand quintals in 2030-31 and at 49,701
thousand quintals in 2047-48. The corresponding requirement for foundation seeds
will be 1030 and 1531 thousand quintals, and for breeder seeds 37,649 quintals and
55,483 quintals in 2030-31 and 2047-48, respectively.
♦By 2030, if the SRR reaches 100%, then the demand for certified seeds will increase
to 78,571 thousand quintals, and further to 92,335 thousand quintals in 2047-48.
Accordingly, the foundation seed requirement is projected at 2509 thousand quintals
in 2030-31 and 2981 thousand quintals in 2047-48, and the breeder seed requirement
at 97,589 quintals and 1,17,669 quintals.
♦With moderate growth in credit supply, the total credit (short-term and long-term)
requirement in agriculture is estimated at Rs 42,60,769 crores in 2030-31 and Rs
1,31,51,319 crores in 2047. 78
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Appendix
Appendix 2.1 Classification of products based on value addition
CategoryFood items
Primary products
Eggs, Potato, Onion, Radish, Carrot, Pumpkin and Guard, Parwal,
Cauliflower, Cabbage, Brinjal, Bhindi, Palak, Beans, Tamato,
Peas, Green chilli, Lemon, Other vegetables, Banana, Jackfruit,
Watermelon, Pineapple, Guava, Sighara, Orange, Papaya, Mango,
Kharbooz, Pears, Berries, Leechi, Apple, Grapes, Other fruits,
Garlic, Ginger
First-processed low value-
added
Rice, Chira, Khoi, Muri, Other rice products, Wheat,Suji, Sewai,
Other wheat products, Jowar and products, Bajra and products,
Maize and products, Barley and products, Millets and products,
Ragi and products, Other cereal, Cereal substitutes, Arhar, Gramdal,
Gramwhole products, Moong, Masur, Urd Peasdal, Khesari, Other
pulses, Gram products, Besan, Dry coconut, Groundnut, Dates,
Cashew, Walnut, Other nuts, Kishmish, Other dry fruits, Salt,
Turnmeric, Blackpepper, Drychilly, Tamarind, Other spices
First-processed high value-
added
Milk, Curd, Butter, Mustard oil, Groundnut oil, Coconut oil,Fish
Prawn, Goat meat, Beef, Pork, Chicken, Other birds,Sugar products,
Gur, Honey, Tealeaf, Coffee powder
Second-processed
products
Refined oilVanaspati oil, Bread, Baby food, Condense milk, Ghee,
Ice-cream, Candy,Curry powder, Cold beverages, Juice, Other
beverages, Prepared sweet, Cake, Biscuits, Papad, Bhujia, Chips,
Pickle, Sauce, Jam, Other processed products, Snacks, Cooked
meals

Appendix 2.2 Divergence between the NSS and NAS estimates of consumption
expenditure and food share
Consumption Expenditure (Rs/
capita/month)
Food Share (%)
NSSNASNSS NAS
1972-73 (1970-71 base) 49527167
1977-78 (1970-71 base) 74836563
1983-84 (1980-81 base) 1261686459
1987-88 (1980-81 base) 1842376155
1993-94 (1993-94 base) 3325376355
1999-00 (1999-00 base) 59610475751
2004-05 (2004-05
base)
713* 1474 52*40
2009-10 (2004-05
base)
1466# 2651 49#37
2011-12 (2004-05 base) 1933# 3530 47#36
2019-20 (2011-12 base) -5164-31
* based on Uniform Reference Period (URP); # based on Modified Mixed Reference Period (MMRP)
Data source: Estimated using the data from the Report of the Committee on Private Final
Consumption Expenditure, Central Statistics Office, MoSPI, GoI, 2015 81
Appendix 4.1 Age and gender wise recommended dietary allowance (RDA) for a balanced diet
Appendix 4.2 Age and gender wise distribution of the population in India
Food group
Infants
6-12
months
1-3
years
4-6
years
7-9
years
10-12 years13-15years
16-18
years
Adult
Sedentary
Adult
Moderate
Elderly (>60
years)
GirlBoyGirlBoyGirlBoyWomanMan WomanMan WomanMan
Cereals 25100160200250290315390330450200270280390140180
Pulses1250606585951051301101506590951307080
Milk597361361412412412412412412412309309309309412412
Roots & tubers205050100100100100100100100100100100100100100
Green leafy
vegetables
205050100100100100100100100100100100100100100
Other
vegetables
25100100150200200200200200200200200200200200200
Fruits505075100100100100100150150100100100100150150
Fat10202025303035453055302530251520
*For non-vegetarian persons, 30 grams of pulses may be substituted with 70 grams of meat.20-30 % of the total cereals intake shall comprise of millets.
Source :ICMR-NIN, 2023. Nutrients Requirements for Indians, ICMR-National institute of Nutrition, Hyderabad.
P
opulation

I
nfants
6-12
months
1-3
years
4-6
years
7-9

years
10-12 years
13-15 years
16-18
Y
ears
A
dult
(19-59)
E
lderly
(>60
years
)
GirlBoyGirlBoyGirlBoyWomanManWomanMan
20114.74.75.85.22.62.92.62.94.75.324.625.74.54.4
20214.24.24.74.22.12.22.12.24.44.826.928.35.24.9
20263.83.84.54.01.92.11.92.14.04.327.729.05.95.5
20313.43.44.23.61.82.01.82.03.74.128.129.46.86.3
20363.13.13.93.31.71.81.71.83.53.928.129.67.97.1
20402.92.93.73.11.61.71.61.73.43.728.129.98.77.8
20472.42.43.32.61.41.51.41.53.13.428.230.310.29.0
Data source: National Commission on Population (NCP), 2019.
Notes:Age wise projected figures are available only up to 2036 (NCP, 2019).For 2040 and 2047, demographic changes are projected based on changes
between 2031 and 2036
Grams/capita/day
Per cent 82
Appendix 4.3 Population weighted RDA norms for the balanced diet in India
Year
Cereals & Millets Pulses*
MilkVegetables Fruits
Fat/
Edible oil
Sedentary Moderate Sedentary Moderate
2011 231 281 80 97 364 361 103 27
2019 230 285 79 99 359 366 104 27
2025 228 285 79 99 357 369 105 27
2030 228 285 79 99 356 372 106 27
2035 227 284 79 99 355 374 107 26
2040 226 284 79 99 355 376 108 26
2047 224 283 79 99 354 379 110 26
Notes:*For non-vegetarian persons, 30 grams of pulses may be substituted with 70 grams of meat.
20-30% of cereals intake shall be nutri-cereals.
Grams/capita/day 83
Appendix 5.1 Crop area, seed rate and seed replacement rate in India
Crop
Seed
rate
(kg/ha):
2011-12
Area
(Million ha)
Seed Replacement Rate
(%)
2011-
12
2019-
20
2025-
26*
2030
-31*
2035-
36*
2040-
41*
2047-
48*
2011-
12
2019-
20
2025-
26#
2030-
31#
2035-
36#
2040-
41#
2047-
48#
Foodgrains -125128128131133133136- - - - -
Cereals - 101100989999 98 98 - - - - -
Rice 714444444444 44 45363840 43475156
Wheat 1303031313334 34 343342 41 45505664
Nutri-cereals11181412119 8 7424155 58 616570
Maize 24 91010 111112 135768 64 66687073
Pulses 44 2428303233 3538254244 48505154
Oilseeds 66 2627282930 31334844 45 45464647
Sugarcane28325.04.65.45.25.15.45.31010 10 10101010
*Projected area based on time series analysis (ARIMA/ANN/CGR)
#Project SRR based on CGR between 2011-12 and 2021-22
Seed rate: State area weighted seed rate based on Cost of Cultivation Surveys, DES
Appendix 5.2 Post-harvest losses in farm operations and marketing in India
% of production
Food item
ICAR-CIPHET
(2015)
NABCONS
(2022)
2025-26 2030-31 2035-36 2040-41 2047-48
Paddy 5.53 4.77 4.44 3.90 3.36 3.22 3.02
Wheat 4.93 4.17 3.84 3.30 2.76 2.59 2.36
Nutri-
cereals
5.61 5.15 4.95 4.61 4.28 4.21 4.11
Maize 4.65 3.89 3.56 3.02 2.48 2.30 2.05
Pulses 7.20 6.13 5.68 4.91 4.15 3.99 3.78
Animal
Food
6.60 5.61 5.18 4.48 3.77 3.62 3.39
Eggs 7.19 6.03 5.53 4.70 3.88 3.70 3.45
Meat 4.73 3.99 3.67 3.14 2.61 2.44 2.21
Fish 7.88 6.81 6.35 5.59 4.83 4.70 4.51
Milk 0.92 0.87 0.85 0.81 0.78 0.73 0.67
Vegetables 8.18 7.42 7.10 6.56 6.01 5.93 5.82
Fruits 9.74 8.96 8.62 8.06 7.49 7.42 7.32
Oilseeds 5.65 4.88 4.55 4.00 3.45 3.31 3.12
Projected wastages is based on %age change between 2015 and 2022 84
Appendix 5.3 Per capita consumption of food at household and away
from home in India in 2011-12
FoodConsumption
Foodgrains11.82
Cereals & Millets10.96
Rice5.85
Wheat4.53
Nutri-cereals0.47
Maize0.10
Pulses0.86
Animal Food0.62
Eggs0.13
Meat0.22
Fish0.27
Milk4.76
Vegetables7.00
Fruits1.24
Sugar and products0.83
Edible oil0.78
Data source: NSS-Household Consumption Expenditure Survey, 2011-12 (type-II Schedule)
Appendix 5.4 Estimated expenditure elasticities of food commodities in India
from the available studies
StudyCerealsRiceWheat
Nutri-
cereals
PulsesMilkNon-veg
Edible
oil
Vegetables Fruits
NITI working
group (2018)
-0.100.490.690.69 0.72 0.72 0.72
Kumar and Joshi
(2016)
0.030.08-0.150.210.380.65 0.26 0.26 0.37
Kumar et al (2011)0.190.721.64 0.77 0.82
Kumar et al (2011) 0.020.08-0.130.220.430.67 0.30 0.26 0.36
Kumar et al (1998) 0.05-0.07-0.160.280.440.79 0.35 0.35 0.42
Kumar, P. (2013)-0.23-0.18-0.21-0.680.390.74 1.01 0.74 0.78 1.53
Mittal (2006) 0.170.591.191.30 0.55 0.72 0.72
IFPRI (2012) -0.21-0.13 -0.240.55 1.170.90 0.64
Srivastava and
Sivaramane (2020)
0.370.530.890.96 0.42 0.58 1.25
Srivastava et al
(2013)
0.210.530.950.96 0.53 0.44 1.25
Radhakrishna
and Ravi (1990)
0.401.040.84 0.68
Bhalla et al
(1999): for 1993-
94
0.261.370.93
Bhalla et al
(1999): for 1987-
88
0.291.350.97
Bhalla et al (1999):
for 1983-84
0.301.140.65
Bhalla et al (1999):
for 1972-73
0.381.430.68
Kg/capita/month 85
Appendix 5.5 Range of published expenditure elasticities and their
smoothen values for future
Commodity
Published elasticities
Selected
2019-
20
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
Min MaxAverage
Rice -0.210.05-0.08-0.08-0.07-0.06-0.05-0.04-0.04 -0.03
Wheat -0.210.08-0.060.08 0.070.060.050.04 0.04 0.03
Nutri-cereals -0.68-0.13-0.40-0.40-0.370.000.050.10 0.15 0.20
Maize -0.16-0.16-0.16-0.16-0.13-0.11-0.10-0.09-0.08 -0.07
Pulses -0.240.720.48 0.48 0.440.410.390.37 0.35 0.33
Non-veg (Eggs,
meat, fish)
0.651.300.98 0.90 0.840.790.750.72 0.69 0.65
Milk 0.791.64 1.2 0.79 0.720.670.630.59 0.55 0.51
Vegetables 0.260.820.54 0.54 0.450.410.380.36 0.33 0.30
Fruits 0.441.530.98 0.750.660.600.560.52 0.48 0.43
Sugar & products0.2 - 0.20 0.20 0.170.080.070.06 0.06 0.05
Edible oil 0.260.900.58 0.26 0.220.20 0.180.17 0.15 0.13
Appendix 5.6 Population estimates used to project food demand
Million
Particular
2011-12
(Base year)
2019-20 2025-26 2030-31 2035-36 2040-41 2047-48
Population 1250 1366 1445 1504 1554 1593 1629
Data source: United Nations (2022) 86
Appendix 5.7 Actual and forecasted values of area, yield and production of food commodities in India
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
area (000 ha)
Rice_area
Actual
Forecast_Holt
0
500
1000
1500
2000
2500
3000
3500
4000
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Yield (kg/ha)
Rice_Yield
Actual
Forecast_ANN
0
20
40
60
80
100
120
140
160
180
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Production (mt)
Rice_Production
Actual
Forecast
0
5000
10000
15000
20000
25000
30000
35000
40000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
area (000 ha)
Wheat_area
Actual
Forecast_ANN 87
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Yield (kg/ha)
Wheat_Yield
Actual
Forecast_ARIMA
0
20
40
60
80
100
120
140
160
180
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Produciton (mt)
Wheat_Production
Actual
Forecast
0
1000
2000
3000
4000
5000
6000
7000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Yield (kg/ha)
Maize_Yield
Actual
Forecast_ExpGR
0
2000
4000
6000
8000
10000
12000
14000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
area (000 ha)
Maize_area
Actual
Forecast_ExpGR 88
0
10
20
30
40
50
60
70
80
90
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Production (mt)
Maize_Production
Actual
Forecast
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
area (000 ha)
Nutri -cereals_area
Actual
Forecast_ExpGR
0
5
10
15
20
25
30
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Production (mt)
Nutri -cereals_Production
Actual
Forecast
0
500
1000
1500
2000
2500
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Yield (kg/ha)
Nutri -cereals_Yield
Actual
Forecast_Holt 89
85000
90000
95000
100000
105000
110000
115000
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
area (000 ha)
Cereals_area
Actual
Forecast
0
500
1000
1500
2000
2500
3000
3500
4000
4500
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Yield (kg/ha)
Cereals_Yield
Actual
Forecast
0
50
100
150
200
250
300
350
400
450
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Production (mt)
Cereals_Production
Actual
Forecast
0
5000
10000
15000
20000
25000
30000
35000
40000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Area (000 ha)
Pulses_area
Actual
Forecast_Holt 90
0
200
400
600
800
1000
1200
1400
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Yield (kg/ha)
Pulses_Yield
Actual
Forecast_ExpGR
0
5
10
15
20
25
30
35
40
45
50
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Production (mt)
Pulses_Production
Actual
Forecast
0
5000
10000
15000
20000
25000
30000
35000
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Area (000 ha)
Oilseeds_area
Actual
Forecast_Holt
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Yield (kg/ha)
Oilseeds_Yield
Actual
Forecast_Holt 91
0
10
20
30
40
50
60
70
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Production (mt)
Oilseeds_Production
Actual
Forecast
0
1000
2000
3000
4000
5000
6000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Area (000 ha)
Sugarcane_area
Actual
Forecast_ANN
0
100
200
300
400
500
600
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Production (mt)
Sugarcane_Production
Actual
Forecast
0
20000
40000
60000
80000
100000
120000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Yield (kg/ha)
Sugarcane_Yield
Actual
Forecast_Holt 92
0
2000
4000
6000
8000
10000
12000
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Area (000 ha)
Fruits_area
Actual
Forecast_ARIMA
0
5000
10000
15000
20000
25000
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Yield (kg/ha)
Fruits_Yield
Actual
Forecast_Holt
0
50
100
150
200
250
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Production (mt)
Fruits_Production
Actual
Forecast
0
2000
4000
6000
8000
10000
12000
14000
16000
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Area (000 ha)
Vegetables_area
Actual
Forecast_ARIMA 93
0
5000
10000
15000
20000
25000
30000
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Yield (kg/ha)
Vegetables_Yield
Actual
Forecast_Holt
0
50
100
150
200
250
300
350
400
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Production (mt)
Vegetables_Production
Actual
Forecast
0
100
200
300
400
500
600
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Production (mt)
Milk_Production
Actual
Forecast_ARIMA
0
5
10
15
20
25
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Production (mt)
Eggs_Production
Actual
Forecast_Holt 94
0
2
4
6
8
10
12
14
16
18
20
1966-67
1968-69
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
2010-11
2012-13
2014-15
2016-17
2018-19
2020-21
2022-23
2024-25
2026-27
2028-29
2030-31
2032-33
2034-35
2036-37
2038-39
2040-41
2042-43
2044-45
2046-47
Production (mt)
Meat_production
Actual
Forecast_ARIMA
0
1
2
3
4
5
6
1966-67
1969-70
1972-73
1975-76
1978-79
1981-82
1984-85
1987-88
1990-91
1993-94
1996-97
1999-00
2002-03
2005-06
2008-09
2011-12
2014-15
2017-18
2020-21
2023-24
2026-27
2029-30
2032-33
2035-36
2038-39
2041-42
2044-45
2047-48
Production (mt)
Fish production_Marine
Actual
Forecast_Holt 95
Appendix 6.1 Export surplus assessment (food demand (6.34%) & production:
yield potential realization)
Million Tonnes
2011-12
(base
year)
2019-
20
2025-
26
2030-
31
2035-
36
2040-41
2047-
48
Hypothesis
Foodgrains 17 21 39 65 89 127 189 Exportable
Cereals &
Millets
18 24 42 68 90 125 182 Exportable
Rice9 16 30 43 59 78 109 Exportable
Wheat5 8 14 26 38 49 68 Exportable
Nutri-cereals 0 0 -1 -3 -4 -7 -10 Importable
Maize4 1 1 2 -1 7 18 Transitioning
Pulses-3 -3 -3 -2 -1 1 7 Transitioning
Vegetables 2 -11 0 17 45 84 166 Transitioning
Fruits0 -6 -6 -2 7 23 54 Transitioning
Sugar &
products
3 -2 7 5 6 -11 13 Transitioning
Edible oil (incl.
vanaspati)
-9 -11 -11 -10 -9 -5 0 Importable
Appendix 6.2 Export surplus assessment (food demand (7%) & production:
business as usual)
Million Tonnes
2011-12
(base year)
2019-
20
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
Hypothesis
Foodgrains 17 21 26 37 35 36 38 Exportable
Cereals & Millets 18 24 30 43 41 42 43 Exportable
Rice9 16 26 35 40 40 40 Exportable
Wheat5 8 10 20 26 29 41 Exportable
Nutri-cereals 0 0 -3 -5 -8 -12 -17 Importable
Maize4 1 -2 -6 -15 -13 -17 Importable
Pulses-3 -3 -5 -5 -6 -6 -5 Importable
Animal Food 2 5 5 5 3 -1 -8 Transitioning
Eggs0 1 2 2 2 2 2 Transitioning
Meat 1 2 1 0 -1 -3 -6 Transitioning
Fish1 2 3 3 2 0 -3 Transitioning
Milk 0 12 9 0 -13 -28 -49Transitioning
Vegetables 2 -11 -18 -24 -27 -27 -18 Importable
Fruits0 -6 -16 -25 -32 -38 -38 Importable
Sugar &
products
3 0 6 5 6 10 12 Exportable
Edible oil (incl.
vanaspati)
-9 -11 -12 -12 -12 -11 -8 Importable 96
Appendix 6.3 Export surplus assessment (food demand (7%) & production:
yield potential realization)
Million Tonnes
2011-12
(base
year)
2019-
20
2025-
26
2030-31
2035-
36
2040-
41
2047-
48
Hypothesis
Foodgrains 17 21 37 62 83 118 176 Exportable
Cereals &
Millets
18 24 41 65 85 119 172 Exportable
Rice9 16 30 44 60 78 109 Exportable
Wheat 5 8 13 26 37 48 68 Exportable
Nutri-cereals 0 0 -1 -3 -5 -8 -12Importable
Maize 4 1 0 0 -6 2 10Transitioning
Pulses -3 -3 -4 -3 -2 -1 4 Importable
Vegetables 2 -11 -4 10 34 70 146Transitioning
Fruits 0 -6 -9 -8 -2 10 36Transitioning
Sugar &
products
3 -2 6 5 6 -11 12Transitioning
Appendix 6.4 Export surplus assessment (food demand (8%) & production:
business as usual)
Million Tonnes
2011-12
(base
year)
2019-
20
2022-
23
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
Hypothesis
Foodgrains 17 21 25 23 32 24 22 16 Exportable
Cereals &
Millets
18 24 29 29 39 33 32 26 Exportable
Rice 9 16 20 27 36 40 41 41 Exportable
Wheat 5 8 14 10 19 25 28 40 Exportable
Nutri-
cereals
0 0 -2 -3 -6 -9 -13 -20Importable
Maize 4 1 -1 -4 -9 -22 -22 -32Importable
Pulses -3 -3 -4 -5 -7 -8 -9 -10Importable
Animal Food 2 5 4 4 1 -3 -10 -23Transitioning
Eggs 0 1 1 1 1 1 0 -2Transitioning
Meat 1 2 1 1 -1 -3 -6 -11Transitioning
Fish1 2 2 2 1 -1 -5 -11Transitioning
Milk 0 12 7 0 -21 -48 -81 -128Importable
Vegetables 2 -11 -16 -23 -35 -44 -51 -50Importable
Fruits 0 -6 -13 -21 -35 -48 -60 -69Importable
Sugar &
products
3 0 6 6 5 5 9 11Exportable
Edible
oil (incl.
vanaspati)
-9 -11 -11 -12 -13 -13 -12 -9 Importable 97
Appendix 6.5 Export surplus assessment (food demand (8%) & production: yield
potential realization)
Million Tonnes
2011-12
(base
year)
2019-
20
2022-
23
2025-
26
2030-
31
2035-
36
2040-
41
2047-
48
Hypothesis
Foodgrains 17 21 33 35 57 72 105 153 Exportable
Cereals &
Millets
18 24 37 39 62 77 109 155 Exportable
Rice 9 16 23 30 44 61 79 110 Exportable
Wheat 5 8 16 13 25 37 47 67 Exportable
Nutri-cereals 0 0 -1 -1 -3 -6 -9 -14 Importable
Maize 4 1 0 -2 -4 -13 -7 -5 Importable
Pulses -3 -3 -4 -4 -5 -5 -4 -1 Importable
Vegetables 2 -11 -11 -9 -1 17 46 114 Transitioning
Fruits 0 -6 -10 -13 -17 -18 -12 5 Importable
Sugar &
products
3 -2 6 6 5 5 -12 12 Transitioning
Edible oil (incl.
vanaspati)
-9 -11 -11 -12 -11 -10 -7 -2 Importable 98
Appendix 7.1 Methodological approach for projection of fertilizer and pesticide
Fertilizer consumption
L_FER_CON_TOT = -0.23 + 0.69*L_FER_CON_TOT(-1) + 0.95*L_GIA - 0.77*L_WPI_FER
+ 0.25*L_WPI_FA…(1)
Pesticide consumption
L_PES_CON = 4.06 + 0.53*L_PES_CON(-1) + 0.42*L_AREA_COT + 0.18*COTDUM2010 -
0.18*COTDUM2012… (2)
Notations: L denotes natural logarithms
FER_CON_TOT = Total fertilizer consumption (N+P+K) in lakh tons
WPI_FER = Wholesale price index (2011-12=100) of fertilizers
WPI_FA = Wholesale price index (2011-12=100) of food articles
PES_CON = Total pesticide consumption in tons
AREA_COT = Area under cotton (million ha)
COTDUM2010, COTDUM2012 = Cotton dummy in 2010 and 2012
Diagnostics
S.No Equation Adjusted R2 D-W statistic ADF test of the residuals
1 Fertilizer 0.971.75-4.57***
2 Pesticide 0.742.14-4.89***

Appendix 7.2 Government initiatives for reducing the usage of pesticides and fertilizers
In order to encourage the use and production of biofertilizers/biopesticides/traditional
indigenous practices over chemical fertilizers/pesticides and ensure transition from
agrochemicals to sustainable farming practices, the Government of India had launched
various schemes over the years.
7, 8
Sustainable farming practices include non-chemical
system of farming such as organic and natural farming systems. While organic systems use
off-farm purchased organic and biological inputs, natural farming systems are based on
biomass mulching, indigenous cow-based inputs but excludes all purchased organic and
biological inputs.
9
The Government is promoting the adoption of both organic farming and
natural farming through the following schemes.
Paramparagat Krishi Vikas Yojana (PKVY)
10
: PKVY was launched in 2015.It is an extended
component of Soil Health Management (SHM) under the Centrally Sponsored Scheme (CSS),
National Mission for Sustainable Agriculture (NMSA). It encourages cluster-based organic
farming with Participatory Guarantee System (PGS) certification which is a decentralized
organic farming certification system. The program supports mobilization of farmers for cluster
formation, training, certification and marketing and post-harvest management. The scheme
aimed to form 10000 clusters of 20 ha each and convert nearly two lakh hectares of agricultural
land to organic farming by 2017-18.
7
https://pib.gov.in/newsite/PrintRelease.aspx?relid=194633. (accessed on 19th September, 2023)
8
https://pib.gov.in/Pressreleaseshare.aspx?PRID=1656146 (accessed on 19th September, 2023)
9
http://agriculture.up.gov.in/nmnf/natural_farming/guid/NMNFGuidelines.pdf (accessed on 21st September, 2023)
10
https://darpg.gov.in/sites/default/files/Paramparagat%20Krishi%20Vikas%20Yojana.pdf (accessed on 19th September, 2023) 99
A total financial assistance of Rs 14.95 lakhs spread over three years is provided per
cluster of 20 ha. Around Rs 50000 per hectare/3 years is given, of which Rs 31000 (62%)
goes directly to the farmers through direct benefit transfer (DBT) for on-farm/off-farm
organic inputs, production/procurement, post-harvest management etc. The pattern of
funding is in the ratio of 60:40 by the Central and State governments respectively. It
is in the ratio of 90:10 (Centre: State) for North Eastern and Himalayan States while
assistance is 100% for Union Territories.
Mission Organic Value Chain Development for North Eastern Region (MOVCDNER):
MOVCDNER is a centrally sponsored scheme initiated in 2015, a sub-mission under
the National Mission for Sustainable Agriculture. Its objective is to develop end to end
organic value chains in North Eastern States starting from inputs, seeds, certification,
and creation of facilities for collection, aggregation, processing, marketing and brand
building initiative.
11
The scheme supports third party certified organic farming of traditional crops in the
north eastern region through cluster development and formation of Farmer Interest
Groups (FIGs)/Farmers Producer Organizations/Companies (FPOs/FPCs). Through the
FPCs, farmers are provided infrastructural, technical and financial support to achieve
economies of scale, engage bulk buyers, and have direct market linkages to national and
international markets with least dependence on traders/middlemen.
12

The scheme was initiated with an average annual allocation of Rs 134 crore and as of
February 2021, it had covered 74880 ha area.
13
The allocation was increased to Rs 200
crore per year with an aim to bring additional one lakh ha area under 200 new FPOs over
a period of three years. As of July 2023, around 1.73 lakh ha area has been brought under
organic farming benefitting 1.89 lakh farmers. It led to the formation of 379 FPOs/FPCs
and establishment of 205 collection, aggregation and grading units; 190 custom hiring
centres; 123 processing unit and pack houses; and development of 7 brands.
14
Financial
assistance of Rs 46575/ha for three years is provided for creation of FPO, support to
farmers for organic inputs, quality seeds/planting material and training and certification.
15

Out of this, around Rs. 32500/ ha for 3 years is provided to farmers for off-farm /on-farm
organic inputs wherein Rs. 15,000 is provided as DBT to the farmers and Rs. 17,500 for the
planting material is given to the farmers by State Lead Agency in kind.
National Mission on Oilseeds and Oil Palm (NMOOP)
16
: Under NMOOP, financial
assistance of up to Rs 300 per ha is provided for use of biofertilizers including supply
of Rhizobium culture/Phosphate Solubilising Bacteria (PSB)/Sinc Solubilising Bacteria
(ZSB)/ Azatobacter/Mycorrhiza and vermi compost.
National Food Security Mission (NFSM)
17
: Under NFSM, financial assistance @ Rs 300 per ha
or 50% of the cost whichever is less, is granted for the use of various biofertilizers including
Rhizobium/Azotobactor/ Azospirilieum, Phosphate solubilising bacteria (PSB) etc in pulses.
11
https://asfac.assam.gov.in/sites/default/files/swf_utility_folder/departments/asfac_medhassu_in_oid_6/portlet/
level_2/9.3.pdf (accessed on 20
th
September, 2023)
12
https://pib.gov.in/PressReleseDetailm.aspx?PRID=1697160 (accessed on 20
th
September, 2023)
13
https://pib.gov.in/PressReleseDetailm.aspx?PRID=1697160 (accessed on 20
th
September, 2023)
14
https://pib.gov.in/PressReleasePage.aspx?PRID=1939604 (accessed on 20
th
September, 2023)
15
https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1946809 (accessed on 20
th
September)
16
https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1592263 (accessed on 20
th
September)
17
https://www.nfsm.gov.in/Guidelines/NFSM12102018.pdf (accessed on 21
st
September, 2023) 100
Integrated Nutrient Management (INM) & Integrated Pest Management (IPM)
18
:
To promote soil health and maintain higher agricultural productivity, fertilizers are
necessary while pesticides play a significant role in sustaining agricultural production by
protecting crops from pests. For promoting a balanced and cautious use of fertilizers,
the Government of India has been advocating soil test based Integrated Nutrient
Management. Under INM, Soil Heath Card Scheme has been implemented since 2015-
16 to help farmers identify their soil health condition.
19
Soil health card provides crop-
specific recommendations on appropriate dosage of fertilizers to be applied based on
soil samples analyzed by the soil testing labs (STL).
The Government of India has also implemented the “Sub-Mission on Plant-protection
and Plant Quarantine” Scheme, which promotes Integrated Pest Management to educate
farmers on the judicious use of chemical pesticides. Additionally, biocontrol methods
and biopesticides are advocated under IPM.
One acre Integrated Organic Farming System (IOFS) models
20
: The Indian Council of
Agricultural Research (ICAR)-Indian Institute of Farming Systems Research developed
IOFS models under the scheme All India Network Programme on Organic Farming (AL-
NPOF). IOFS is a model that consists of providing crop, cropping systems and one acre of
land.
21
Need based trainings are provided to farmers to develop IOFS models.
22
In Kerala,
Sikkim, Meghalaya, and Tamil Nadu, IoFS models have been built which are suitable for
marginal farmers. They offer the opportunity to produce more than 80% of the inputs
needed for organic farming within the farm, thereby lowering the cost of production.
PM-PRANAM (PM Programme for Restoration, Awareness, Generation, Nourishment
and Amelioration of Mother Earth)
23
: PM-PRANAM which was approved in June 2023
aims to support the wide-spread movement initiated by States/Uts to preserve Mother
Earth’s health through promotion of sustainable and balanced use of fertilizers, adoption
of alternate fertilizers, and promotion of organic farming and implementation of resource
conservation technologies. Under PM-PRANAM, a State/UT would get a grant equal to
50% of the fertilizer subsidies that were saved by that State/UT in a given fiscal year by
reducing its consumption of chemical fertilizers (Urea, DAP, NPK, and MOP) compared
to the average consumption over the previous three years.
Capital Investment Subsidy Scheme (CISS): CISS for commercial production units
for organic/biological inputs was introduced in 2004-05 under National Project on
Organic Farming. It aims to promote organic farming by increasing the availability and
quality of biopesticides, biofertilizers and composts.
24
Individuals, groups of farmers,
proprietary/partnership firms, cooperatives, fertilizer industry, companies, corporations,
and NGOs are among the beneficiaries eligible for the subsidy for the establishment
of a biofertilizer and biopesticides production unit, while APMCs, Municipalities, NGOs,
18
https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1602828 (accessed on 21st September, 2023)
19
https://cdn.s3waas.gov.in/s388ae6372cfdc5df69a976e893f4d554b/uploads/2018/07/2018072691.pdf (accessed on21st
September, 2023)
20
https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1592263 (accessed on 20th September, 2023)
21
https://www.indiafilings.com/learn/integrated-organic-farming-system/ (accessed on 21st September, 2023)
22
https://pib.gov.in/newsite/PrintRelease.aspx?relid=194883 (accessed on 20th September, 2023)
23
https://pib.gov.in/PressReleasePage.aspx?PRID=1945750#:~:text=The%20Cabinet%20Committee%20on%20
Economic,(PM%2DPRANAM)%E2%80%9D . (accessed on 21st September, 2023)
24
https://www.nabard.org/content1.aspx?id=592&catid=23&mid=23 (accessed on 20th September) 101
and private entrepreneurs are eligible for the subsidy for the establishment of fruit and
vegetable waste compost unit. While most of the aforementioned schemes were aimed
at promoting the use of organic inputs, Capital Investment Subsidy Scheme (CISS) was
solely aimed at encouraging the production of these inputs.
The scheme provides credit linked and back-ended capital investment subsidy at 25% of
total financial outlay subject to the maximum of Rs 40 lakh per unit for the establishment
of biofertilizers/biopesticides unit.
25
For fruit & vegetable market waste compost unit,
the scheme provides 33% of total financial outlay subject to a maximum of Rs 63 lakh
per unit.
In 2009-10, it was estimated that the production of biofertilizers and biopesticides was
about 28000 and 40000 tonnes per annum (TPA) respectively against the installed
production capacity of around 80000 TPA (for biofertilizers and biopesticides).
26
This
was much lower than the potential requirement of 7.6 lakh TPA of biofertilizers and 15
lakh tonnes of biopesticides in the country.
Bharatiya Prakritik Krishi Padhati (BPKP)
27
: BPKP was included in Paramparagat Krishi
Vikas Yojana (PKVY) as a sub-scheme in 2020-21. BPKP is based on the principles of
natural farming. The scheme encourages traditional indigenous practices to enable
farmers to avoid the use of externally purchased inputs. It promotes on-farm biomass
recycling and focuses on biomass mulching, use of cow dung-urine formulations
and exclusion of synthetic chemical inputs. BPKY emphasizes on improving farmers’
profitability, availability of quality food and restoration of soil fertility and farmland
ecosystem along with generation of employment and contribution to rural development.
The program is implemented on a demand-driven basis in accordance with Centrally
Sponsored Scheme (CSS) guidelines and has a total outlay of Rs. 4645.69 crore for the
six-year period (2019-20 to 2024-25). With a goal of covering 12 lakh ha in 600 major
blocks of 2000 hectare in various states, BPKP provides financial assistance of Rs 12200/
ha for three years for cluster creation, capacity building and handholding by trained
personnel, certification, and residue analysis. The scheme complies with Participatory
Guarantee System (PGS) certification. Only eight states have chosen to participate in
the program: Andhra Pradesh, Chattisgarh, Kerala, Himachal Pradesh, Madhya Pradesh,
Odisha, Tamil Nadu, and Jharkhand.
National Mission on Natural Farming (NMNF)
28
: By up scaling the Bhartiya Prakritik
Krishi Paddati (BPKP), in 2023-24, the Government has formulated National Mission on
Natural Farming (NMNF) as a separate and independent scheme for implementation all
across the country. NMNF aims to motivate farmers to adopt chemical free farming and
enhance the reach of natural farming.
25
https://ncof.dacnet.nic.in/uploads/SchemaGuidelines/Capital_Investment_Subsidy_Scheme_CISS_Guidelines.pdf (accessed
on 20th September, 2023)
26
https://www.nabard.org/auth/writereaddata/File/NPOF_English.pdf (accessed on 20th September, 2023)
27
https://naturalfarming.niti.gov.in/bharatiya-prakritik-krishi-paddhati-bpkp/ (accessed on 20th September, 2023)
28
https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1911558#:~:text=To%20motivate%20farmers%20to%20
adopt,Prakritik%20Krishi%20Paddati%20(BPKP). (accessed on 20th September, 2023) 102
The success of NMNF will necessitate behavioral change in farmers to switch from
chemical inputs to cow based locally produced inputs. This would further involve
continuous creation of awareness, training, handholding and capacity building of farmers
in the initial years.
With a total outlay of Rs 1584 crore, NMNF aims to cover 7.5 lakh hectares of land,
developed into 15,000 natural farming clusters in the next 4 years and each cluster
would comprise 50 or more farmers with 50 ha of land.
29
Alongside 15000 model natural
farming clusters, Bharitya Prakritik Kheti Bio-inputs Resources Centres (BRCs) would be
set up to prepare and supply bio-inputs like Jeevaamrit, Ghana Jeevamrit, neemastra
etc. wherein cow dung and urine, neem and bio culture play an important role.
Under this scheme, farmers would be provided a financial assistance of Rs 15000 per
ha @ Rs 5000 per ha/year for three years as DBT for the creation of on-farm input
production infrastructure. The incentives would be provided to the farmers on the
condition that they commit to undertake natural farming on long term basis. Through
NMNF, the government proposes to cover 1 crore farmers along the Ganga belt and in
other rainfed regions of the country.
However, despite two decades of efforts by the government to promote non-chemical
farming practices, only 2.7 % (3.8 million ha) of the India’s net-sown area is under organic
and natural farming.
30
Further, it is stated that the overall funds spent on the schemes
and programmes for promoting the use and production of biofertilizers and organic
fertilizers is significantly less than the annual subsidy given for chemical fertilizers
31

(which was Rs 175099 crore in 2023-24
32
).
29
https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1906884 (accessed on 21st September, 2023)
30
https://www.downtoearth.org.in/news/agriculture/natural-option-organic-natural-farming-not-only-profitable-sustainable-
but-also-productive-81684 (accessed on 21st September, 2023)
31
https://www.cseindia.org/content/downloadreports/11235 (accessed on 20th September, 2023)
32
https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1911558#:~:text=To%20motivate%20farmers%20to%20
adopt,Prakritik%20Krishi%20Paddati%20(BPKP). (accessed on 20th September, 2023) 103
crops
Area
projected
(2025-
26) (m.
ha)
New
SMR
Revised
Seed
Rate
(kg/ha)*
SRR
Projected
(2025-
26)
Seed requirement at
100% SRR
Seed requirement at
projected SRR
Certified
seed
(000’ q)
Foundation
seed
(000’ q)
Breeder
seed
(q)
Certified
seed
(000’ q)
Foundation
seed
(000’ q)
Breeder
seed
(q)
WHEAT 31.3732 100 47.9731370 980 3063515049 470 14696
PADDY 46.3280 30 35.8413895 174 2171 4981 62 778
MAIZE 10.36150 20 67.09 2071 14 92 1390 9 62
JOWAR 3.66180 10 29.59 366 2 11 108 1 3
BAJRA 7.40300 5 46.72 370 1 4 173 1 2
RAGI 1.09200 10 92.14 109 1 3 100 1 3
BARLEY 0.5530 87.5 38.81 485 16 539 188 6 209
URD 5.2153 15 37.34 782 15 278 292 6 104
MOONG 6.5753 15 26.64 986 19 351 263 5 94
ARHAR 5.2112012.562.57 651 5 45 407 3 28
PEAS 0.6714 88 43.01 587 42 2995 252 18 1288
GRAM 10.8226 58 28.20 6275 241 9282 1770 68 2618
LENTIL 1.4440 30 64.35 432 11 270 278 7 174
GROU-
NDNUT
6.1418 120 25.09 7363 409 22724 1847 103 5701
RAPE/
MUST
6.93240 5 65.18 347 1 6 226 1 4
TIL 1.62250 5 68.66 81 0 1 56 0 1
SUNFLOWER 0.1250 6 30.60 7.08 0 3 2 0 1
SOYABEAN 13.7520.0068.5 34.96 9418 471 23546 3292 165 8231
CASTOR 0.72120 7.5 65.08 54 0 4 35 0 2
SAFFLOWER 0.0367 12 37.33 3.2 0 1 1 0 0
TOTAL 158.59    75652 2403 92961 30710 925 33998
Appendix 7.3a Crop-wise seed demand in 2025-26 104
Appendix 7.3b Crop-wise seed demand in 2030-31
crops
Projected
area
(2030-
31) (m.
ha)
New
SMR
Revised
seed
rate
(kg/
ha)*
Projected
SRR
(2030-
31)
Seed requirement at 100%
SRR
Seed requirement at projected
SRR
Certified
seed
(000’ q)
Foundation
seed
(000’ q)
Breeder
seed
(q)
Certified
seed
(000’ q)
Foundation
seed
(000’ q)
Breeder
seed
(q)
WHEAT 31.6832 100 55.1031679 990 3093717455 545 17046
PADDY 47.0180 30 33.4614103 176 2204 4719 59 737
MAIZE 10.97150 20 73.062193 15 97 1602 11 71
JOWAR 2.92180 10 29.81292 2 9 87 0 3
BAJRA 7.10300 5 42.32 355 1 4 150 1 2
RAGI 1.01200 10 100.00 101 1 3 101 1 3
BARLEY 0.5130 87.5 42.61446 15 495 190 6 211
URD 6.94 53 15 36.381041 20 371 379 7 135
MOONG 8.96 53 15 24.701345 25 479 332 6 118
ARHAR 5.89120 12.587.30 736 6 51 642 5 45
PEAS 0.82 14 88 46.83 719 51 3669 337 24 1718
GRAM 11.9426 58 30.466926 266 102462109 81 3120
LENTIL 1.4140 30 89.52 422 11 263 377 9 236
GROUN-
DNUT
6.29 18 120 25.177548 419 232951900 106 5864
RAPE/
MUST
7.24240 5 68.07 362 2 6 246 1 4
TIL 1.50250 5 100.00 75 0 1 75 0 1
SUN-
FLOWER
0.05 50 6 22.30 3.15 0 1 1 0 0
SOYABEAN 14.8620.0068.5 32.7410182 509 254543333 167 8333
CASTOR 0.56120 7.5 73.05 42 0 3 31 0 2
SAF-
FLOWER
0.01 67 12 44.17 1.2 0 0 1 0 0
TOTAL 163.02    78571 2509 9758934068 1030 37649 105
Appendix 7.3c Crop-wise seed demand in 2035-36
crops
Area
projected
(2035-
36) (m.
ha)
New
SMR
Revised
Seed
Rate (kg/
ha)*
SRR
Projected
(2035-
36)
Seed requirement at 100% SRR
Seed requirement at
projected SRR
Certified
seed
(000’ q)
Foundation
seed
(000’ q)
Breeder
seed
(q)
Certified
seed
(000’ q)
Foundation
seed
(000’ q)
Breeder
seed
(q)
WHEAT 31.9932 100 63.2831991 1000 3124120245 633 19771
PADDY 47.7280 30 31.2414315 179 2237 4472 56 699
MAIZE 11.61150 20 79.552323 15 103 1848 12 82
JOWAR 2.34180 10 30.03 234 1 7 70 0 2
BAJRA 6.82300 5 38.34 341 1 4 131 0 1
RAGI 0.93200 10 100.00 93 0 2 93 0 2
BARLEY 0.47 30 87.5 46.77 410 14 455 192 6 213
URD 9.24 53 15 35.451386 26 494 491 9 175
MOONG 12.2253 15 22.901834 35 653 420 8 149
ARHAR 6.65120 12.5100.00 831 7 58 831 7 58
PEAS 1.00 14 88 50.98 881 63 4495 449 32 2292
GRAM 13.1826 58 32.897646 294 113102515 97 3720
LENTIL 1.3740 30 100.00 411 10 257 411 10 257
GROUN-
DNUT
6.45 18 120 25.257737 430 238811954 109 6031
RAPE/
MUST
7.55240 5 71.08 378 2 7 268 1 5
TIL 1.39250 5 100.00 69 0 1 69 0 1
SUN-
FLOWER
0.02 50 6 16.24 1.4 0 1 0.2 0 0
SOYABEAN 16.0720 68.5 30.6611007 550 275183375 169 8437
CASTOR 0.43120 7.5 82.00 32 0 2 26 0 2
SAF-
FLOWER
0.00 67 12 52.26 0.5 0 0 0.2 0 0
TOTAL 167.59    81922 2628 10272637863 1151 41897 106
Appendix 7.3d Crop-wise seed demand in 2040-41
crops
Area
projected
(2040-
41) (m.
ha)
New
SMR
Revised
Seed
Rate
(kg/
ha)*
SRR
Projected
(2040-
41)
Seed requirement at 100%
SRR
Seed requirement at
projected SRR
Certified
seed
(000’ q)
Foundation
seed
(000’ q)
Breeder
seed
(q)
Certified
seed
(000’ q)
Foundation
seed
(000’ q)
Breeder
seed
(q)
WHEAT 32.3132 100 72.6932306 1010 3154923482 734 22932
PADDY 48.4380 30 29.1714530 182 2270 4238 53 662
MAIZE 12.30150 20 86.632460 16 109 2131 14 95
JOWAR 1.87180 10 30.26 187 1 6 57 0 2
BAJRA 6.54300 5 34.73 327 1 4 114 0 1
RAGI 0.86200 10 100.00 86 0 2 86 0 2
BARLEY 0.43 30 87.5 51.35 377 13 418 193 6 215
URD 12.3153 15 34.54 1846 35 657 638 12 227
MOONG 16.6753 15 21.232500 47 890 531 10 189
ARHAR 7.5212012.5100.00 940 8 65 940 8 65
PEAS 1.23 14 88 55.511079 77 5507 599 43 3057
GRAM 14.5526 58 35.528440 325 124852998 115 4434
LENTIL 1.3440 30 100.00 402 10 251 402 10 251
GROUND-
NUT
6.61 18120 25.34 7932 441 244812010 112 6203
RAPE/
MUST
7.88240 5 74.23 394 2 7 293 1 5
TIL 1.29250 5 100.00 64 0 1 64 0 1
SUN-
FLOWER
0.01 50 6 11.83 0.6 0 0 0.1 0 0
SOYABEAN 17.372068.5 28.7111899 595 297483417 171 8542
CASTOR 0.331207.5 92.05 25 0 2 23 0 2
SAF-
FLOWER
0.00 67 12 61.83 0.2 0 0 0.1 0 0
TOTAL 172.28    85795 2762 10845442213 1291 46885 107
Appendix 7.3e. Crop-wise seed demand in 2047-48
crops
Area
projected
(2047-
48) (m.
ha)

New
SMR
Revised
Seed
Rate (kg/
ha)
*
SRR
Projected
(2047-
48)

Seed requirement at 100% SRR
Seed requirement at projected
SRR
Certified
seed
(000’ q)
Foundation
seed
(000’ q)
Breeder
seed
(q)
Certified
seed
(000’ q
)
Foundation
seed
(000’ q)
Breeder
seed
(q)
WHEAT 32.7532 100 88.2432753 1024 3198528901 903 28223
PADDY 49.4580 30 26.4914836 185 23183930 49 614
MAIZE 13.33150 20 97.602665 18 1182601 17 116
JOWAR 1.36180 10 30.58 136 1 4 42 0 1
BAJRA 6.17300 5 30.24 309 1 3 93 0 1
RAGI 0.77200 10 100.00 77 0 2 77 0 2
BARLEY 0.38 30 87.5 58.51 335 11 372 196 7 218
URD 18.3953 15 33.302758 52 982 919 17 327
MOONG 25.7353 15 19.093859 73 1374 737 14 262
ARHAR 8.92120 12.5100.00 1115 9 77 1115 9 77
PEAS 1.6314 88 62.531434 102 7318 897 64 4576
GRAM 16.7126 58 39.559692 373 143383834 147 5671
LENTIL 1.2940 30 100.00 388 10 243 388 10 243
GROUND-
NUT
6.84 18 120 25.46 8212 456 253462091 116 6453
RAPE/
MUST
8.37240 5 78.87 419 2 7 330 1 6
TIL 1.16250 5 100.00 58 0 1 58 0 1
SUN-
FLOWER
0.00 50 6 7.60 0.2 0 0 0.0 0 0
SOYABEAN 19.3720 68.5 26.2013271 664 331783476 174 8691
CASTOR 0.23120 7.5100.00 17 0 1 17 0 1
SAF-
FLOWER
0.00 67 12 78.25 0.0 0 0 0.0 0 0
TOTAL 179.07    92335 2981 11766949701 1531 55483 108 109 110
File No. Q-11018/02/2016-Agri
Government of India
National Institution for Transforming India
(Agriculture Vertical)
Subject: Minutes of the 1st Meeting of Working Group on Demand and Supply projections
of Crops, Livestock, Fisheries and Agriculture Inputs –reg.
1. The first Working Group (WG) Meeting on Demand and Supply projections of
Crops, Livestock, Fisheries and Agriculture Inputs, constituted vide O.M dated 17
th

August, 2022 was held under the chairpersonship ofMember (Agri), NITI Aayog
on 6th October 2022 at 1000 hrs in Room No. 500 (Bengal Tiger), NITI Aayog.
The Meeting was held in hybrid mode (in-person and virtual mode). The list of
participants is enclosed as Annexure–I.
2. At the outset, Dr Neelam Patel, Sr. Adviser (Agri) welcomed the Hon’ble Member
(Agriculture), NITI Aayog and members of the Working Group. It was shared
that the Working Group has been constituted as per the directions of Hon’ble
Member (Agri), NITI Aayog and it’s a time-bound task. The timely release of the
desired projections will enable Indian policy-makers in taking decisions based on
empirical datasets.
3. Hon’ble Member (Agri), NITI Aayog acknowledged that the Agriculture Vertical
has undertaken this task second time after constitution of NITI Aayog and this
exercise is immensely useful. It was mentioned that the long-term sectoral growth
projections used to be published by the Planning Commission of India. Since, NITI
Aayog was constituted in 2014, development agenda for 3 and 5 years for various
sectors have been published by the think-tank. It was shared that Demand and
Supply projections for agrifood commodities are often referred in many high-
level meetings chaired and extensively used in food management policy of India.
In 2016, a Working Group on Demand and Supply projections was constituted by
NITI Aayog under the chairmanship of Dr Pramod Kumar, Professor, Institute of
Social and Economic Change, Bangalore. The projections were given till 2032-33.
These estimations are helpful in addressing many issues related to agri-business,
farmers’ welfare, inflation control, buffer stocking, state agri-ecosytem, food
management etc. and support in devising planning measures for sustainable
agricultural practices- production & value chain. The Terms of Reference (ToR)
had been identified for the Working Group that will be chaired by Prof Birthal.
The chairman can decide on co-opting a few members or constitutesub-groups
to drive the task. However, the number of experts in the WG should not be very
large.Also, it was shared that an independent short term study can be proposed
by the Group to fill any data gap needed by the WG.NITI Aayog can consider
funding of such short term study.
4. Prof P.S. Birthal, Chairman of the Working Group shared that a small group
meeting was convened to discuss the study approach, methodology to steer this
task. The methodological approaches and data requirements were presented by
Dr S.K. Shivendra. 111
5. Hon’ble Member mentioned that WG may see historical trend in agri-food sector
after 1970. It emerged that in some cases like supply, it would be a better approach
to prepare state level estimates and aggregate them to arrive at National level
estimates. The NABARD or CSO databases can be explored for estimating credit
demand.
6. The WG noted the episodes of sharp price rise in the case of dry fodder and
underlined the need to prepare estimate of demand for dry fodder in the country.
7. All the members acknowledged that there is a need of empirically drawn demand-
supply projection for policy-makers - both Central and State Government to
address issues like availability of agri-inputs esp. bio-fertilizers/organic fertilizers,
Nano-fertilizers, feed and fodder for livestock in states etc. The WG members
assured full support in timely completion of the report.
8. The meeting ended with a vote of thanks to the chair.
The Action Points from the meeting are as follows:
1. To share the list of co-opted Members/Members if considered essential or sub-
groups (Action: Chairman)
2. To share the list of datasets required for the study and source (Action: Chairman)
3. To prepare a list of interactions with Industry/associations/Institute/others.
(Action: Chairman and Member Secretary) 112
Annexure-1
List of Participants
S.No. Name & Organization
1. Prof. P. S. Birthal, Director, ICAR - NIAP, New Delhi
2. Smt Neeraja Adidam, Joint Secretary, Department of Fertilizers, Shastri Bhavan, ND
3. Sh. Shankar L., Joint Commissioner, DoF, MoFAH&D
4. Dr Vijay Laxmi Pandey, IGIDR, Mumbai, CESS
5. Dr Shivendra Kr. Srivastava, ICAR-NIAP
6. Sh. Kedar Nath Verma, Director (MIDH), Ministry of Agriculture & FW, Krishi Bhavan, ND
7. Dr O.P Chaudhary, Joint Secretary, DAHD, Krishi Bhavan, ND
8. Sh. B.M Sahare, Additional Director (Agriculture), Bhopal, MP
9. Sh. Jag Raj Dandi, Joint Director, Dept. of Agriculture, Haryana
10. Dr Subhra Sarkar, Deputy Director General, National Accounts Division (NAD), MoSPI
11. Sh. Kana Ram, Commissioner (Agriculture), Rajasthan (joined via virtual mode)
12. Dr. R.K Tewatia, Director (Agriculture Science), Fertilizer Association of India
13. Sh. Arputhaswamy (IES), DES, Ministry of Agriculture and Farmers Welfare
14. Ms Shraddha Pal, Asst. Director, Animal Husbandry Statistics Division, DADH
15. Sh. Dipankar Mishra, Asst. Director, DAH&D
16. Dr Neelam Patel, Sr. Adviser (Agriculture), NITI Aayog
17. Dr Tanu Sethi, Sr Associate (Agri), NITI Aayog 113
File No. Q-11018/02/2016-Agri Government of India
National Institution for Transforming India (Agriculture Vertical)
Minutes of the consultation of the Working Group on Demand and Supply projections of
Crops, Livestock, Fisheries and Agriculture Inputs –reg.
1. A consultation was organised under the chairmanship of Hon’ble Member (Agri),
NITI Aayog to discuss changing food consumption and production patterns
(Terms of References no. 1 of the working group constituted on Demand and
Supply projections) on 27th February 2023 (Monday), 3:00- 5:30 PM at Room
No. 122, NITI Aayog. In absentia of Hon’ble Member, NITI Aayog, the consultation
was chaired by Prof Dr. Pratap Singh Birthal, Chairman of the Working Group and
Director, ICAR- National Institute of Agricultural Economics and Policy Research.
The list of participants is enclosed as annexure.
2. At the outset, Dr. Neelam Patel, Sr. Adviser (Agri), NITI Aayog and Member
Secretary of the working group welcomed members of the Working Group, Sr.
Government Officers and representatives from various Associations.
3. Dr. Birthal welcomed the participants and briefed about the working group task
and highlighted the importance of projections on demand and supply of agri-
commodities for food security along with imports and exports. For calculation
of Demand projections, data is inevitable and it was requested that respective
Ministry/Departments may share the requested data sets on priority.
4. A Presentation on food consumption and demand was made by Dr S. K Srivastava,
Senior Scientist, ICAR-NIAP. The presentation covered changing consumption
patterns and food demand of Indian households till 2011-12, preliminary estimates
on normative food demand and models adopted in the study.
5. Detailed discussion was held on coefficient of estimates and future scenarios,
changing food preferences towards value added food products, future model
for the study etc. It was iterated that latest data sets are required for making
projections.
The agreed Action Points are as follows:
1. To send reminder to respective Ministries/Departments to share state-wise time
series data on Area, production, productivity of horticultural crops, milk, non-veg
items, crops, etc. on priority. (Action: Member Secretary and Respective Ministry/
Departments).
2. To convene following meeting of Stakeholders:
i. With MoSPI officials to discuss the use of supply use tables (SUTs) and food
balance sheet;
ii. With the food processing Industry and Hotel Association to discuss third
processing – market share, food utilization and waste etc.
iii. With Animal Feed Industry Association
(Action: Member Secretary) 114
3. To share unit-level household survey data, updated balanced diet recommendations
for children (age group wise) as recent report (2020) does not has values for children.
This data will help in studies related to projections on recent trend in consumption
pattern and estimation of population weighted - all India average balance diet
recommendations for moderate and sedentary activity (
Action: ICMR-NIN).
4. To visit ICMR-NIN for collecting data (
Action: Dr Sivaramane, N., Principal Scientist,
ICAR-NAARM and other Members).
5. To provide estimates on diversion of raw produce (individual food items) to
processing industry in quantity terms in India and extent of direct& indirect uses of
food commodities (edible oils, cereals, pulses, milk, etc.) (
Action: The Food Processing
Industry association, Indian Oilseed and Produce Export Promotion Council, India
Pulses and Grains Association, Indian Sugar Mills Association, and Indian Dairy
Association). 115
NOTES NOTES NOTES Designed by: