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About the ProjectThe need for monitoring and analysis of emerging food scenarios is important for India both because ofsignificant dependence of output on the monsoon rains and the fact that globally India is one of the majorconsumers of food crops influencing markets. Management of agriculture from a public policy perspectiverequires organisation of this information and analysis as inputs to policy making.

Against this backdrop the National Food Security Mission (NFSM), Ministry of Agriculture, commissioned a3–Year study to National Council of Applied Economic Research (NCAER) in 2011–12 to bridge thisimportant gap in analytical inputs for understanding the emerging agricultural scenarios both in the short-termof one or two quarters and also in the medium to longer term.

Accordingly, the agricultural outlook and situation analysis undertaken in this study refers to the main cropbased food items: cereals (specifically rice, wheat, jowar, bajra, maize and overall coarse grains), pulses (gram,tur), selected fruits and vegetables (banana, potato, onion), sugarcane and edible oils (groundnut, rapeseed/mustard, soybean). In addition the analysis also covers milk, one livestock product.

The three main outputs of this work are:

(1) A Quarterly Agricultural Outlook Report that integrates the assessment of key indicators relating toagriculture with a focus on food sectors. The reports include assessment of the current situation on inputs,output and market conditions and also forecasts of key indicators for the full year based on modelsdeveloped for the purpose.

(2) A Semi-annual Agricultural Outlook Report which provides a longer term perspective for the food sector.These reports present an analysis of alternative scenarios of output and consumption for the food cropstaking into account the available information and based on the suitable economic models that permitlonger term projections.

(3) Monthly briefings on the prevailing agricultural conditions.

ImplementationNCAER has set up a study team to carry out the study.

An advisory committee has been formed to provide broad guidance to the implementation of the study. TheCommittee comprises of Dr Shekhar Shah, DG, NCAER as Chair, Dr Ashok Gulati, Chairman, Commissionon Agricultural Costs and Prices, Prof. Ramesh Chand, Director, National Centre for Agricultural Policy(NCAP), New Delhi and Prof. Mahendra Dev, Director, Indira Gandhi Institute for Development Research(IGIDR), Mumbai. Representative from FAO and DFID are Special Invitees to the Committee meetings.

A Technical Support Group comprising of key officers from different departments of the government andexperts has also been formed to interact with the study team to improve the work under the study.

Agricultural Outlook and Situation Analysis Reports

Third Semi-annual Medium-term Agricultural Outlook Report

June, 2014

AGRICULTURAL OUTLOOK AND SITUATION ANALYSIS REPORTS

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Agricultural Outlook and Situation Analysis Reports

Third Semi-annual Medium-term Agricultural Outlook Report

Under the Project Sponsored by the National Food Security MissionMinistry of Agriculture

June, 2014

Prepared by

National Council of Applied Economic Research11, I.P. Estate, New Delhi 110 002


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Against the backdrop of expectations of recovery in the pace of growth India’s economycombined with moderation in inflationary pressures the outlook for fresh investments inthe agricultural sector and its downstream and upstream industries has also improved.Aided by the improved global economic conditions India’s economic growth rate is nowexpected to be 6.5–7 per cent over the medium-term of 2014–15 to 2020–21. Improvedinvestment climate over the medium-term may raise the growth rate further.

In June 2013, the medium-term outlook projections for 2013–2022 presented by OECD-FAO World Agricultural Outlook 2013 indicate slower growth of agricultural productionin general and for production of major food commodities in particular in the projectionperiod as compared to the experience of the recent decade. The crop prices are projectedto moderate in the initial five years of the projection period and then firm up in the nextfive years. The livestock prices, on the other hand are expected to remain firm through theprojection period strengthening crop prices. In general, the analysis points to maintainingof the supply-demand balances at the global level, with relatively moderate price increase.These conditions in turn point to the need for achieving growth in the production of foodcommodities in the developing economies supported by productivity growth that is not ledmainly by price incentives. A review of the global agricultural prospects over the medium-term points to the following scenario:

Global wheat production is forecast to increase by 12.5 per cent to 784.5 million tonnesduring 2013 to 2022. Russia to emerge as the leading wheat exporter with exports of21 million tonnes by 2022. India is forecast to remain a net exporter of wheat ofaround 4 million tonnes, whereas China will remain a net importer.

World’s rice production is projected to increase by around 55 million tonnes between2013 and 2022. Rice production in Thailand and Vietnam is forecast to increase by 3million tonnes each. Significant increase in production is forecast in Indonesia (6million tonnes), Bangladesh (6 million tonnes) and African countries (10 milliontonnes). Indian rice exports are forecast to decline somewhat to 5.3 million tonnes,comprising mostly basmati rice, indicating the growth of domestic consumption.

India’s coarse grain production is forecast to increase modestly to around 53 milliontonnes from the current 42 million tonnes. India’s production of coarse grains remains,however, much lower among major producing countries such as the United States (371million tonnes), China (257 million tonnes), and Brazil (80 million tonnes). Indianexports are forecast at around 4 million tonnes.

Global vegetable oil production increases from 163 million tonnes to 196 milliontonnes by 2022. Most of the increase in world vegetable oil production is forecast tobe palm oil in Indonesia and Malaysia and soybean oil in Argentina and Malaysia.

India’s share in global sugar production in 2022 is forecast at 15 per cent at around 32million tonnes. Brazil with a production of 48 million tonnes in 2022 will continue tobe the largest sugar producing country. Almost 50 per cent of sugarcane production inBrazil goes in the production of ethanol.

Highlights

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Domestic markets will be the drivers of consumption and demand for India’s food sectorover the medium-term.

In this report, we have presented an assessment of the medium-term prospects of supplyand demand conditions for the major food commodities along with factors influencingthese conditions. Update of our September 2013 medium-term projections shows that thecurrent estimates of output growth rates are lower than the previous assessment inSeptember 2013 in the case of wheat, rice and oilseeds. The range of updated growth rateshas narrowed in the case of coarse grains but with a decline in the average of the projectedrange. The projected growth rates based on trend analysis are also lower in the case ofsugarcane, potato and onion.

The projected demand scenario is broadly similar to the one presented in September 2013,with some variations. The projected growth of domestic demand is lower in the updatedoutlook in the case of wheat and coarse grains but remains unchanged in the case of rice,partly reflecting the negative expenditure elasticity for these commodities. In the case ofpulses, the updated demand growth rate is higher, which also reflects the positiveexpenditure elasticity. In the case of other commodities, we have retained the growth ratesof demand as in the September 2013 Medium-term Agricultural Outlook Report(MTAOR).

The projections essentially reflect the differences in consumer demand preferences asincome levels rise. The changes in output composition in favour of non-cerealcommodities in domestic demand are projected to continue. The export demand isprojected at a slightly higher pace for cereals than estimated in the previous report.

Comparison of projected production and demand conditions point to the need formeasures to support growth in production and supplies in the case of wheat, coarse grains,onion and banana (or fruits more generally). Greater attention to development of marketswould be needed in the case of rice, potato and milk. In the case of sugar, the current paceof production matches the growth rate of demand and efforts to improve productivitywould result in scope for exports over the medium-term.

An analysis of production growth and variability in production points to the significantdifferences in growth and variability across states and the trends in growth and variability.Therefore, efforts could be focused on improvement of cultivation practices, to catch upwith higher yields in other states. The states with lower yields but showing higher rates ofgrowth would require measures to sustain growth which also reduce volatility inproduction. The states where yield levels are high, would require measures that push thetechnology frontiers in terms of new varieties and adoption of best practices. Supportivemeasures that reduce the adverse impact of market risks would be needed in states wherevariability of production is large for any commodity.


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The study team wishes to acknowledge the support of a number of organisations andindividuals in the preparation of this report. The encouragement and support of theofficials in the ministry of agriculture has been critical to this work. Mr Ashish Bahugunahas provided sustained support and encouragement to the study team. We wish toacknowledge the guidance and support received from Dr J.S. Sandhu, AgriculturalCommissioner and Mr Sanjay Lohiya, Joint Secretary, Crops and NFSM, in this project.Cooperation from the officials in the Directorate of Economics and Statistics has beenimmensely valuable to the work on agricultural outlook.

We have drawn on the reports of OECD/FAO, FAPRI and USDA on global agriculturaloutlook extensively for the assessment of global conditions. These references have beenacknowledged in the report. We have also drawn on wide range of official statistics fromthe ministry of agriculture and other government organisations for the preparation of thepresent report.

The members of the advisory committee for the study have provided encouragement andsupport throughout the project period. The study team is grateful to their encouragementand support.

Acknowledgements

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Study Team

Shashanka Bhide (Project Leader), A. Govindan, Laxmi Joshi, V.P. Ahuja, CharuJain, Himani Gupta and Praveen Sachdeva are the staff associated with thepreparation of the present report.

Prof. Parmod Kumar, ISEC, has contributed to the medium-term projections basedon the results of the econometric model developed for the purpose under thecollaboration between NCAER and ISEC.


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Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .v

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .vii

Highlights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .ix

Acknowledgements and Study Team . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xi

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xv

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xvii

I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

II. Parameters of Production of Selected Food Commodities at the State Level . . . . . . . . . . . . . . . . . . . . . . . . . . .3

III. Global Outlook and Implications for India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43

IV. An Assessment of the Medium-term Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59

V. Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67

Appendix I: Calculation of Growth, Variability and Decomposition of Growth of Production . . . . . . . . . . . . . . . . . .71

Contents

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II.1.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Rice . . . . . . . . . . . . . . . . . . . . . .8

II.2.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Wheat . . . . . . . . . . . . . . . . . . .12

II.3.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Maize . . . . . . . . . . . . . . . . . . . .15

II.4.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Bajra . . . . . . . . . . . . . . . . . . . . .19

II.5.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Jowar . . . . . . . . . . . . . . . . . . . .22

II.6.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Gram . . . . . . . . . . . . . . . . . . . .25

II.7.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Tur . . . . . . . . . . . . . . . . . . . . . .29

II.8.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Rapeseed & Mustard . . . . . . . .32

II.9.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Groundnut . . . . . . . . . . . . . . . .35

II.10.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Soybean . . . . . . . . . . . . . . . . . .38

II.11.1 Pattern of Growth and Variability in yields during 2000–01 to 20011–12: Sugarcane . . . . . . . . . . . . . . . . .41

III.1 Projection Comparison – Wheat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .48

III.2 Projection Comparisons – Rice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49

III.3 Projection Comparison – Maize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50

III.4 Projection Comparison – Soybeans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52

III.5 Projection Comparison – Soybean oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53

III.6 Projection Comparison – Sugar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54

IV.1 Indicators of Growth of Food Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60

IV.2 Wholesale Price Index of Selected Food Commodities: % change year on year . . . . . . . . . . . . . . . . . . . . . .61

IV.3 Average Growth Rate per cent of Production of Selected Food Commodities:Actual Production Trends in 2008–13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64

IV.4 Projected Growth in Domestic Demand for Food Commodities over the Medium-term (2014–2020) . . .65

V.1 Yield Level, Growth and Variability Characteristics: Cereals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .68

V.2 Yield Level, Growth and Variability Characteristics: Pulses, Oilseeds and Sugarcane . . . . . . . . . . . . . . . .68

List of Tables

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II.1.1 Trends in Area, Yield and Production of Rice across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

II.1.2 Pattern of Variability in Rice Area, Yield and Production across States: Coefficient of Variation (%), 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

II.1.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Rice:%, 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

II.1.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Rice across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

II.1.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Rice at All India Level:Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

II.2.1 Trends in Area, Yield and Production of Wheat across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

II.2.2 Pattern of Variability in Wheat Area, Yield and Production across States: Coefficient of Variation (%),2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

II.2.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Wheat: %,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

II.2.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Wheat across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

II.2.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Wheat at All India Level: Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

II.3.1 Trends in Area, Yield and Production of Maize across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

II.3.2 Pattern of Variability in Maize Area, Yield and Production across States: Coefficient of Variation (%), 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

II.3.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Rice:%, 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

II.3.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Maize across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

II.3.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Maize at All India Level: Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

II.4.1 Trends in Area, Yield and Production of Bajra across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16

II.4.2 Pattern of Variability in Bajra Area, Yield and Production across States: Coefficient of

List of Figures

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Variation (%), 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17

II.4.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Bajra: %,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17

II.4.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Bajra across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

II.4.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Bajra at All India Level: Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

II.5.1 Trends in Area, Yield and Production of Jowar across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

II.5.2 Pattern of Variability in Jowar Area, Yield and Production across States: Coefficient of Variation (%), 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

II.5.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Jowar:%, 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

II.5.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Jowar across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

II.5.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Jowar at All India Level: Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

II.6.1 Trends in Area, Yield and Production of Gram across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

II.6.2 Pattern of Variability in Gram Area, Yield and Production across States: Coefficient of Variation (%), 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

II.6.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Gram: %,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24

II.6.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Gram across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24

II.6.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Gram at All India Level:Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25

II.7.1 Trends in Area, Yield and Production of Tur across States: Trend Growth Rates, 2000–01 to 2011–12 . . .26

II.7.2 Pattern of Variability in Tur Area, Yield and Production across States: Coefficient of Variation (%),2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

II.7.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Tur: %,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

II.7.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Tur across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28

List of Figures

xviii

II.7.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Tur at All India Level:Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28

II.8.1 Trends in Area, Yield and Production of Rapeseed and Mustard across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .29

II.8.2 Pattern of Variability in Rapeseed and Mustard Area, Yield and Production across States:Coefficient of Variation (%), 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30

II.8.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Rapeseed & Mustard: %, 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30

II.8.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Rapeseed & Mustard across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31

II.8.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Rapeseed & Mustard at All India Level: Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32

II.9.1 Trends in Area, Yield and Production of Groundnut across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33

II.9.2 Pattern of Variability in Groundnut Area, Yield and Production across States: Coefficient of Variation (%), 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33

II.9.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Groundnut: %,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34

II.9.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Groundnut across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34

II.9.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Groundnut at All India Level: Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35

II.10.1 Trends in Area, Yield and Production of Soybean across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36

II.10.2 Pattern of Variability in Soybean Area, Yield and Production across States: Coefficient of Variation (%), 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36

II.10.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Soybean: %,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37

II.10.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviation from highest yield) for Soybean across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37

II.10.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Soybean at All India Level: Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38

List of Figures

xix

II.11.1 Trends in Area, Yield and Production of Sugarcane across States: Trend Growth Rates,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .39

II.11.2 Pattern of Variability in Sugarcane Area, Yield and Production across States: Coefficient of Variation (%), 2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .39

II.11.3 Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Sugarcane: %,2000–01 to 2011–12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .40

II.11.4 Pattern of Average Production (Thousand tonnes), Yield (kg/ha) and Yield Gap (deviation from highest yield) for Sugarcane across States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .40

II.11.5 Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Sugarcane at All India Level: Rolling Estimates for Previous 10-years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41

III.1 Volatility in Agricultural Prices (Coefficient of Variation %) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43

III.2 Volatility in Commodity Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44

III.3 Commodity Price Trend in Real Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44

IV.1 Average Annual Rate of Growth of GDP from Agricultural and Allied Sectors on Rolling 5-Year Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60

IV.2 Pattern of change in MSP: the MSP in 2013–14 with its value in 2000–01=100 . . . . . . . . . . . . . . . . . . . .61

IV.3 Pattern of changes in wholesale prices: Average WPI with TE 2000–01=100 . . . . . . . . . . . . . . . . . . . . . . .62

IV.4 Trends in the Index of Per capita Private Final Consumption Expenditure (2004–05 prices) with 1950–51=100. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62

IV.5 Index of value of output in constant 2004–05 prices with 2004–05 output=100: Selected commodities . .63

IV.6 Comparison of growth of production and domestic demand for the major food commodities in the medium-term: 2014–2021 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66

List of Figures

xx

The global supply-demand balances for food commodities remain subject to fluctuationsin weather conditions as production shortfall in one region leads to demand pressures onthe overall supplies. After the drought conditions in the United States in 2012 when wheatand soybean production there was adversely affected and prices of these commodities inthe international markets rose, the situation in 2013 reversed as the weather conditionsturned more favourable. In 2012 world production of rice, wheat, maize and soybeandeclined over the previous year. Because of the large stocks of commodities, the priceimpact was less significant. The FAO’s Food price Index, comprising of crop and livestockfood commodities, actually declined in 2012 by 7.3 per cent over the previous year. Theworld cereal production is now expected to increase in 2013/14 by 9 per cent over theprevious year according to FAO’s Crop Prospects and Food Situation (March 2014).

The short-term fluctuations in output and the resulting adjustments in available suppliesto meet the demand for basic requirement of food can be managed only if there areadequate stocks of the commodities. Building up of adequate stocks and their managementto meet the unexpected production fluctuations is possible if there are appropriatestrategies for sustaining food production that are aligned with the emerging demandconditions including the supply-demand balances at the global level. The productionstrategies need to take into account not only the growth of output but also likelyfluctuations or variability in production.

India’s foodgrain output in 2013–14 has now been estimated at 264.38 million tonnes,7.25 million tonnes higher than in the previous year. The oilseeds production is estimatedto have increased from 30.9 million tonnes in 2012–13 to 32.4 milion tonnes in 2013–14.Sugarcane production is estimated at 348.4 million tonnes, up by 7.2 million tonnes fromthe previous year.

India’s imports of pulses and vegetable oils now account for a significant proportion oftotal consumption. In the case of pulses, net imports in 2013–14 are estimated to be 2.7million tonnes as compared to production of 19.6 million tonnes. In the vegetable oils,imports in 2012–13 oil year (Nov–Oct) were 10 million tonnes as compared to productionof 7.5 million tonnes. India has also emerged as a major exporter of rice, with exports ofabout 10 million tonnes in 2013–14. Growing agricultural trade helps in balancing supply-demand imbalances in specific commodities while enabling shifts in cropping patternwhere trade is beneficial to both consumers and producers.

The medium-term prospects for food commodities depend on sustained improvements ininput use, input use efficiency, development of new varieties of crops and livestock toensure supplies to meet emerging demand conditions.

In the present medium-term agricultural outlook report, we have reviewed the emergingsupply-demand balances for the major food commodities for India. We have provided ananalysis of the recent trends and patterns of production parameters at the state level inchapter II, with a view to identify the potential improvement in productivity with greaterstability of production.

CHAPTER I

Introduction

1

The productionstrategies need totake into accountnot only thegrowth of outputbut also likelyfluctuations orvariability inproduction.

The medium-term prospectsfor foodcommoditiesdepend onsustainedimprovements ininput use, inputuse efficiency,development ofnew varieties ofcrops andlivestock toensure suppliesto meet emergingdemandconditions.

The chapter III of the report provides a review of the global production conditions for themajor food commodities and the implications of the global scenario for India’s supply anddemand for food commodities. In chapter IV, we present an update of the medium-termoutlook for the country to the analysis that was presented in September 2013. Chapter Vprovides a summary of the main findings of the report.


2

Comparison of production performance across states provides an assessment of thedifferences across states that also reflect the potential for catching up with the bestperformers. Factors influencing agricultural growth at an aggregate level include agro-climatic conditions, irrigation availability, input use levels and agronomic practices thatinfluence production and productivity of crops across the states. Production performanceis also influenced by markets, implementation of various government productionprogrammes and policies besides the infrastructure for agriculture.

Production growth is contributed by growth in crop area and yield per hectare of crop area.The relative contribution of area and yield to crop production also may vary dependingupon the adoption of technology by states and potential for area growth. Besides growth,variability in production is also an important criterion to be considered from a policyperspective. Achieving higher and stable yield levels would be a policy goal to increase foodproduction when expansion of land area is not feasible.

In this chapter we provide an assessment of the relative performance of various states withregard to growth and variability in area, yield and production of major crops and also tomeasure the contribution of area and yield in production growth over the past decade1.

An attempt has also been made to assess the changing pattern of growth and variability ofcrop area, production and yield over time. This analysis provides insights on whetherfactors influencing crop production such as policy changes, input use changes and climatechange etc. have caused a shift in the growth and variability of crops over time. A ten-yearmoving compound growth rates and coefficient of variations have been estimated for thepast several decades for major crops in important producing states and at the nationallevel2.

II.1 RiceThe trends in area, yield, and production for rice in the recent decade of 2000–01 to2011–12 (Figure II.1.1.) show that the highest growth in rice production was registered byGujarat, a relatively small rice growing state, followed by Chhattisgarh, Madhya Pradesh,Haryana, Andhra Pradesh, Jharkhand and Orissa, with the annual growth rate rangingfrom nine to around three per cent. However, some major rice producing states such asWest Bengal, Uttar Pradesh, Maharashtra and Tamil Nadu have registered only a modestgrowth in production, below the all India growth rate of 1.8 per cent (Figure II.1.1).

CHAPTER II

Parameters of Production of SelectedFood Commodities at the State Level

3

Achieving higherand stable yieldlevels would be apolicy goal toincrease foodproduction whenexpansion of landarea is notfeasible.

An attempt hasalso been made toassess thechanging patternof growth andvariability of croparea, productionand yield overtime. Thisanalysis providesinsights onwhether factorsinfluencing cropproduction suchas policy changes,input use changesand climatechange etc. havecaused a shift inthe growth andvariability ofcrops over time.

1. The computation methodologies are discussed in Appendix I.

2. While coefficient of variation has been used for assessing variability, it should be pointed out that this measure includes the variation from mean arising from growth itself, besides the year to year fluctuations. An alternative measure such as the ratio of mean square error from trend value to the mean overcomes this weakness of CV. A comparison of the results using the CV with the alternative measure showed only a few variations in the results and therefore we have retained the analysis with CV as a measure of variability.

While Bihar registered a negative production growth rate during the period of 20001–02to 2011–12, we should also note that rice production in Bihar registered remarkablegrowth in 2011–12 which has been maintained in the subsequent year of 2012–13 as well.Rice production in Bihar increased from 3.1 million tonnes in 2010–11 to 7.2 milliontonnes in 2011–12 and it is estimated at 7.3 million tonnes in 2012–13. Much of theincrease has come from yield improvement. Rice production also increased by about 2million tonnes in Uttar Pradesh and West Bengal in 2011–12 over the previous year andthe output was sustained at the new high in the subsequent year.

The highest yield growth was registered by Chhattisgarh, Jharkhand, Orissa, and MadhyaPradesh, besides Gujarat, reflecting the impact of the government programmes such as“Bringing Green Revolution to Eastern India States” (BGREI) and the National FoodSecurity Mission (NFSM). At the all India level annual yield growth was 1.82 per cent.

Most states registered a marginal or negative growth rate in rice area, with the exceptionof Gujarat, Haryana, and Andhra Pradesh. At the all India level, the area growth rate wasnegligible.

Measured in terms of coefficient of variation, the higher production variability wasregistered mostly in BGREI states of Jharkhand, Chhattisgarh and Bihar implying thesestates, despite registering a higher growth, have also experienced greater variability. Asexpected, production variability was lower in the mostly irrigated states such as Punjab,Uttar Pradesh, and Haryana. West Bengal and Assam were exceptions, where despitelower irrigation coverage and lager dependence on monsoon rains, the productionvariability is lower. This is perhaps due to the fact that these states produce two or morerice crops in a year, thus offsetting the decline in one season by higher production in thenext season. Most of the production variability is attributed to fluctuations in yield, butarea fluctuation is also significant in a number of states with Jharkhand, Gujarat, andAndhra Pradesh experiencing greater variability in area under rice than in the other states.In Gujarat and Andhra Pradesh, area under rice increased at an average rate significantly


Most statesregistered amarginal ornegative growthrate in rice area,with the exceptionof Gujarat,Haryana, andAndhra Pradesh.At the all Indialevel, the areagrowth rate wasnegligible.

4

Figure II.1.1: Trends in Area, Yield and Production of Rice across States: Trend Growth Rates, 2000–01to 2011–12

Note: UP + UK = Uttar Pradesh and Uttarkhand combined.

higher than in the other states, whereas in Jharkhand the area under rice declined sharply.At the national level coefficient of variation of production, area, and yield was 9.4 per cent,3.0 per cent and 7.9 per cent respectively.

Analysis of contribution of area and yield to production change reveals that in most states,with the exception of Andhra Pradesh and West Bengal, yield was the major factorcontributing to the production growth. The yield contribution is higher in Chhattisgarh,followed by Maharashtra, Orissa, Bihar and Haryana whereas in Andhra Pradesh andWest Bengal area contributed to more than three-fourth of the production growth. At allIndia level, yield contribution was about 2/3rd and area about 1/3rd (Figure II.1.3).

PARAMETERS OF PRODUCTION OF SELECTED FOOD COMMODITIES AT THE STATE LEVEL

5

Analysis ofcontribution ofarea and yield toproductionchange revealsthat in moststates, with theexception ofAndhra Pradeshand West Bengal,yield was themajor factorcontributing to theproductiongrowth.

Fig II.1.2: Pattern of Variability in Rice Area, Yield and Production across States: Coefficient of Variation(%), 2000–01 to 2011–12

Figure II.1.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Rice: %,2000–01 to 2011–12

Differentials in yields across states suggest the likely gains that can be had by raising theyield levels in the lower yield states to the highest that is achieved among the states. Whileagro-climatic and technological conditions may constrain the low yield states fromreaching the highest yield levels achieved elsewhere, the yield gaps – difference betweenthe highest yield and actual yields in individual states point to such likely differences at themicro level also. Figure II.1.4 illustrates the average production, yield, and yield gapbetween a state’s average yield and the highest yield among all states.

The largest yield gap is seen in states of Madhya Pradesh, Chhattisgarh, Orissa, Bihar andUttar Pradesh. The potential to increase rice production by bridging the yield gap isconfined mainly to the eastern states (Figure II.1.4).

In the case of rice, there has been a significant upward shift in production growth duringthe decade ending 2012–13, after remaining subdued during previous decades. The higherproduction growth was supported by high yield growth, whereas area growth was low.Higher production growth, however, coincided with higher production variability, mostlyin yields (Figure II.1.5).


6

In the case of rice,there has been asignificantupward shift inproductiongrowth during thedecade ending2012–13, afterremainingsubdued duringprevious decades.

Figure II.1.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Rice across States

At the state level, production growth saw a significant increase in recent years mainly inthe eastern states of Chhattisgarh, Orissa, and to a lesser extent in Bihar and UttarPradesh, mainly driven by high yield growth. Andhra Pradesh and Haryana also registeredhigh production growth rates in the most recent decade. No significant trend inproduction variability was observed in any state except in Assam and to a lesser extent inBihar. There has been a modest declining trend in production variations in Tamil Naduand Orissa.

The overall trends and patterns in area and yield, the two parameters of productionreviewed above indicate that where average yield levels are low and growth rates are alsolow, there is a need for steps to support adoption of practices by the farmers that help inthe improvement in land productivity. In states where yields are high and growth is low,the steps needed are research efforts to raise the production frontier and disseminate thenew technologies that help raise the productivity. Efforts may also be needed to provideincentives for output processing and developing new markets. The programmes such asRKVY, NFSM and BGREI provide such a framework for policy actions. We havesummarised the overall patterns that emerge from a review of trends and patterns of yieldof rice at the state level in Table II.1.1.


7

At the state level,productiongrowth saw asignificantincrease in recentyears mainly inthe eastern statesof Chhattisgarh,Orissa, and to alesser extent inBihar and UttarPradesh, mainlydriven by highyield growth.

The overall trendsand patterns inarea and yield, thetwo parametersof productionreviewed aboveindicate thatwhere averageyield levels arelow and growthrates are also low,there is a need forsteps to supportadoption ofpractices by thefarmers that helpin theimprovement inland productivity.

Figure II.1.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Rice at All IndiaLevel: Rolling Estimates for Previous 10–years

There are seven states where the average yield levels are relatively high (above 2 tonnes perha) and five states where the growth rate of yields is also high (above 1.5 per cent per year).Among the states where yields are high but variability is also high are the southern statesof Andhra Pradesh, Tamil Nadu and Karnataka. In Punjab and Haryana the yield andyield growth are high and variability in yields is low.

The states with low yields are Assam and Bihar, with the latter also experiencing morevariability. In six states of Chhattisgarh, Gujarat, Jharkhand, MP, Maharashtra andOdisha, the yields are low but growth rate of yields is high. In these states, greater attentionis required to provide protective measures such as improved irrigation or alternativevarieties that can withstand fluctuations in rainfall and weather conditions.

II.2 WheatAcross the major states, the highest growth rate in production over the last decade wasrecorded by Gujarat followed by Maharashtra, Madhya Pradesh and Rajasthan whereasthe lowest production growth was mostly in major wheat growing states such as Punjab,Uttar Pradesh and Bihar. West Bengal, although not a major wheat growing state,registered a negative growth rate. Production growth in Haryana was a modest 2.53 percent, marginally lower than the national level growth rate of 2.65 per cent. The areagrowth was the highest in Maharashtra while yield growth was higher in Gujarat,Maharashtra and Madhya Pradesh than in the other states, almost twice the nationalgrowth rate of 1.29 per cent (Figure II.2.1). The national level growth rate of area wasgreater than growth rate of yield (Figure II.2.2).


8

Across the majorstates, the highestgrowth rate inproduction overthe last decadewas recorded byGujarat followedby Maharashtra,Madhya Pradeshand Rajasthanwhereas thelowest productiongrowth wasmostly in majorwheat growingstates such asPunjab, UttarPradesh andBihar.

Table II.1.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Rice

Yield growth Yield

Low (<= 2 tonnes/ ha) High (>2 tonnes/ ha)

CV: low (<=10%) CV: high (>10%) CV: low (<=10%) CV: high (>10%)

Low (<=1.5% per year) Assam Bihar UP

West Bengal

High (>1.5% per year) Chhattisgarh Haryana Andhra Pradesh

Gujarat Punjab Karnataka

Jharkhand Tamil Nadu

MP

Maharashtra

Orissa

Along with high growth, Gujarat also experienced high production variability of wheat.Production variability was also high in Madhya Pradesh, Maharashtra, and Rajasthan,whereas major wheat growing states of Punjab, Uttar Pradesh, and Bihar experiencedsmaller variability in production. Production variability was largely spurred by variabilityin area rather than in yield in states such as Maharashtra, Rajasthan and Gujarat. At thenational level average year-to-year variability was around 11 per cent, 5.2 per cent in areaand 6.2 per cent in yield.


9

Productionvariability waslargely spurredby variability inarea rather thanin yield.

Figure II.2.1: Trends in Area, Yield and Production of Wheat across States: Trend Growth Rates,2000–01 to 2011–12

Fig II.2.2: Pattern of Variability in Wheat Area, Yield and Production across States: Coefficient ofVariation (%), 2000–01 to 2011–12

Decomposition of production growth indicates that yield was the major contributingfactor for the production increase in most states, except in Gujarat, Maharashtra, andRajasthan, where area increase was more important. At the national level yieldcontribution accounted for almost 60 per cent of the increase in wheat production and areaincrease around 40 per cent (Figure II.2.3).

The highest average yield was in Punjab at 4,400 kg/ha and the deviation from this highestyield in various states ranged from 3 tonnes/ha in Maharashtra to 200 kg/ha in Haryana.In the major wheat growing state of Uttar Pradesh, the yield gap is around 1,600 kg/haand in Madhya Pradesh 2,700 kg/ha (Figure II.2.4).


10

In the majorwheat growingstate of UttarPradesh, the yieldgap is around1,600 kg/ha and inMadhya Pradesh2,700 kg/ha.

Figure II.2.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Wheat: %,2000–01 to 2011–12

Figure II.2.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Wheat across States

The potential for increasing wheat production by bridging the yield gap is to be significant.

The trends in CV and growth rates of area, production, and yield of wheat at the nationallevel over time. show that that since 2010–11 there has been an increasing trend in theCGR of area, production, and yield of wheat, after remaining low during 2004–05through 2009–10. However, with increasing growth rates and partly because of thisincrease in growth rates itself, production fluctuation has also widened (Figure II.2.5). Thefluctuations are also indicative of the continued influence of rainfall on crop production.

At the state level, production growth rate has recorded significant increases in recentdecade in Madhya Pradesh and Rajasthan as also the variability in production. The highproduction growth in Madhya Pradesh was driven both by high growth rate in area as wellas in yield while in Rajasthan the high growth rate was propelled mainly by high areagrowth In other major wheat growing states such as Uttar Pradesh, Punjab, and Haryana,the increase in production growth rates was modest mostly driven by yield, and productionfluctuation has been less significant indicative of a plateauing of production. In Bihar,however, there was a significant increase in growth rate in the most recent decade mainlydue to high yield growth rate.

We have summarised the overall patterns that emerge from a review of trends and patternsof yield of wheat at the state level in Table II.2.1.


11

The trends in CVand growth ratesof area,production, andyield of wheat atthe national levelover time. showthat that since2010–11 there hasbeen anincreasing trendin the CGR of area,production, andyield of wheat,after remaininglow during2004–05 through2009–10.

Figure II.2.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Wheat at All IndiaLevel: Rolling Estimates for Previous 10-years

The low yield and low growth states are UP, Bihar and West Bengal, among which UPaccounts for almost a third of India’s wheat area. Efforts to improve yields in these statesare likely to have significant production gains. The states currently with low yields butexperiencing significant growth in yield are Gujarat, Madhya Pradesh and Maharashtra.Along with growth, these states also experienced high variability in yields. Therefore,measures to reduce the impact of yield fluctuations would lead to stable growth.

The states having high yield and lower variability are Punjab, Haryana and Rajasthan.Punjab has now reached a plateau in yields in the sense that growth rate of wheat yield inPunjab is relatively low. In the case of yield, therefore, efforts to improve yield potentialthrough new varieties and new techniques of crop production are likely to be the mainsource of yield growth in these states.

II.3 MaizeThe three highest growth rates in maize production during the past decade were registeredby Tamil Nadu (28.5 per cent) followed by West Bengal (18.8 per cent) and Maharashtra(18.7 per cent). Karnataka and Andhra Pradesh were the only two other states whereproduction increased by about 10 per cent or more per year in the last decade. Most of theincrease was attributed to growth in area, except in Tamil Nadu, where yield growth wasthe highest. In Uttar Pradesh and Madhya Pradesh, production growth rate was negative.At the national level, production growth was 5.8 per cent equally contributed by area (2.8per cent per year) and yield (2.9 per cent per year) (Figure II.3.1).


12

The states havinghigh yield andlower variabilityare Punjab,Haryana andRajasthan. Punjabhas now reached aplateau in yieldsin the sense thatgrowth rate ofwheat yield inPunjab isrelatively low. Inthe case of yield,therefore, effortsto improve yieldpotential throughnew varieties andnew techniques ofcrop productionare likely to be themain source ofyield growth inthese states.

Table II.2.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Wheat

Yield growth Yield

Low (<= 2.8 tonnes/ ha) High (>2.8 tonnes/ ha)


Low (<=1.5% per year) UP Bihar Punjab

West Bengal

High (>1.5% per year) Gujarat Haryana

Madhya Pradesh Rajasthan

Maharashtra

However, the high production growth rate was also associated with high productionvariability, which ranged from 80 per cent in Tamil Nadu to 36 per cent in Andhra Pradesh(Figure II.3.2).

Although area growth exceeded pace of increase in yield was the major factor contributingto production in most states with the exception of West Bengal. The contribution of areagrowth to production growth was 30 per cent or more in the case of Andhra Pradesh,Karnataka, UP and West Bengal.


13

Although areagrowth exceededpace of increasein yield was themajor factorcontributing toproduction inmost states.

Figure II.3.1: Trends in Area, Yield and Production of Maize across States: Trend Growth Rates, 2000–01to 2011–12

Figure II.3.2: Pattern of Variability in Maize Area, Yield and Production across States: Coefficient ofVariation (%), 2000–01 to 2011–12

The yield gap is highest in Rajasthan, Uttar Pradesh, MP and Gujarat with the deficitrelative to maximum yield being more than 2 tonnes per hectare. In Karnataka, Bihar andMaharashtra, the yield gap is between 1 and 2 tonnes per hectare. Hence significant futureincrease in maize production can come from yield improvement in these states (FigureII.3.4).

Maize production growth at the national level has registered a generally upward trend overthe past decade except for occasional marginal dips. Yield was the major contributoryfactor for higher production growth. Production variability has tended to stabilize inrecent decades, whereas yield variability has declined (Figure II.3.5).


14

The yield gap ishighest inRajasthan, UttarPradesh, MP andGujarat with thedeficit relative tomaximum yieldbeing more than 2tonnes perhectare.

Figure II.3.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Rice: %,2000–01 to 2011–12

Figure II.3.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Maize across States

States which recorded an upward trend in production growth include Andhra Pradesh,Bihar, Karnataka, Rajasthan and Uttar Pradesh, whereas the growth trend wasinsignificant or negative in most other states. Yield variability has increased in AndhraPradesh, Bihar, and Rajasthan.

Among the major states having low yields, growth of yield is at a relatively higher in thecase of Maharashtra and Rajasthan (Table II.3.1). Measures to sustain growth in the formof marketing support, infrastructure would sustain yield growth as the states catch up withthe higher yield states.

In the higher yield states of Tamil Nadu, Andhra Pradesh, Punjab and West Bengal, thevariability in yield is also relatively high. Therefore, measures to reduce variability in yieldswhile maintaining growth would produce more stable growth.


15

In the higher yieldstates of TamilNadu, AndhraPradesh, Punjaband West Bengal,the variability inyield is alsorelatively high.Therefore,measures toreduce variabilityin yields whilemaintaininggrowth wouldproduce morestable growth.

Figure II.3.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Maize at All IndiaLevel: Rolling Estimates for Previous 10–years

Table II.3.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Maize

Yield growth Yield



Low (<=3% per year) Bihar Gujarat

Jammu & Kashmir Himachal Pradesh

Karnataka

UP

High (>3% per year) Maharashtra Tamil Nadu

Andhra Pradesh

Punjab

West Bengal

II.4 BajraBajra production growth was high in Haryana, Rajasthan and Madhya Pradesh exceeding4.5 per cent per year, whereas in Gujarat and Maharashtra the growth rate was negligibleor negative. During the last decade, bajra production increased by 3.5 per cent per year inKarnataka and UP. Area growth was minimal at the national level and the productiongrowth was driven by yield increases in most states. At the national level annualproduction growth was 2.9 per cent, fuelled by 3.3 per cent growth in yield despite amarginal negative growth in area (Figure II.4.1).

Being a mostly rainfed crop, variability in production is high in bajra, both due tovariability in yield and to a lesser extent by volatility in area. At the national level the CVof production is at around 24 per cent, 20 per cent in yield and 7.6 per cent in area (FigureII.4.2).


16

Being a mostlyrainfed crop,variability inproduction is highin bajra, both dueto variability inyield and to alesser extent byvolatility in area.

Figure II.4.1: Trends in Area, Yield and Production of Bajra across States: Trend Growth Rates, 2000–01to 2011–12

More than 70 per cent of the contribution to the production growth is from yield at theall India level and in most states except in Maharashtra, where it was only 46 per cent(Figure II.4.3).

Among major bajra producing states, the yield gap is largest in Rajasthan, Karnataka andMaharashtra. Hence future growth in bajra production should be focused on these threestates by narrowing the yield gap (Figure II.4.4).


17

More than 70 percent of thecontribution to theproductiongrowth is fromyield at the allIndia level and inmost statesexcept inMaharashtra,where it was only46 per cent.

Figure II.4.2: Pattern of Variability in Bajra Area, Yield and Production across States: Coefficient ofVariation (%), 2000–01 to 2011–12

Figure II.4.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Bajra: %,2000–01 to 2011–12

At all India level, production growth rate has shown a generally upward trend, almostentirely driven by yield growth whereas area growth rate has registered a negative trend.Area variability, although high, has generally remained flat except for the most recentdecade (Figure II.4.5).

Although Karnataka, Maharashtra and Rajasthan have relatively lower yields, yields haveincreased there at a faster pace during the last decade. In Haryana and Madhya Pradesh,yields are relatively high, yield growth is also high but yield variability measured by CV ismore than 20 per cent (Table II.4.1). Therefore, yield growth stabilising measures inHaryana, MP, Karnataka, Maharashtra and Rajasthan and yield enhancing measures in


18

At all India level,productiongrowth rate hasshown a generallyupward trend,almost entirelydriven by yieldgrowth whereasarea growth ratehas registered anegative trend.

Figure II.4.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Bajra across States

Figure II.4.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Bajra at All IndiaLevel: Rolling Estimates for Previous 10-years

Karnataka, Maharashtra and Rajasthan will have significant impact on sustainingproduction growth. In Gujarat and UP, technology improvements in terms of higheryielding varieties of bajra would be required to increase the yields further.

II.5 JowarWith the exception of Rajasthan, all major states registered a decline in jowar productionduring the period 2000–01 to 2011–12, largely due a declining trend in area. At thenational level, production declined at the rate of 1 per cent per year during the period of2000–01 to 2011–12. Area also declined by 3.6 per cent per year but yield rose by 2.7 percent per year to reduce the production decline. In Rajasthan area increased by a modestrate of 0.2 per cent per year and production by 7.66 per cent (Figure II.5.1).

Competition from other crops such as soybean, maize and cotton has led to decline injowar acreage. Most states have registered a positive growth rate in yield, which rangedfrom as high as 7.4 per cent in Rajasthan to 0.5 per cent in Uttar Pradesh.


19

With theexception ofRajasthan, allmajor statesregistered adecline in jowarproduction duringthe period2000–01 to2011–12, largelydue a decliningtrend in area.

Figure II.5.1: Trends in Area, Yield and Production of Jowar across States: Trend Growth Rates, 2000–01to 2011–12

Table II.4.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Bajra

Yield growth Yield



Low (<=3.5% per year) Gujarat

UP

High (>3.5% per year) Karnataka Haryana

Maharashtra Madhya Pradesh

Rajasthan

Production variability was the highest in Rajasthan with CV at 52 per cent even as itregistered high rate of growth of production. The CV of production was the lowest inMaharashtra at 11.7 per cent (Figure II.5.2). At the national level, production variabilitymeasured by CV was a modest 7.2 per cent, with area variability at 13 per cent and yieldvariability at 11.5 per cent.

Yield contributed relatively more to production change, which at the national level wasalmost 92 per cent and ranged from almost 100 per cent in Karnataka to 56 per cent inUttar Pradesh (Figure II.5.3).


20

At the nationallevel, productionvariabilitymeasured by CVwas a modest 7.2per cent, witharea variability at13 per cent andyield variability at11.5 per cent.

Figure II.5.2: Pattern of Variability in Jowar Area, Yield and Production across States: Coefficient ofVariation (%), 2000–01 to 2011–12

Figure II.5.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Jowar: %,2000–01 to 2011–12

With the exception of Rajasthan, the yield gap in jowar is not significant in most states(Figure II.5.4) implying that potential for increasing production from bridging the yieldgap at the present level of technology is limited. However, some scope exists inMaharashtra and Karnataka with about 5 million hectares of area under jowar where theyields are lower than the best yields.

Jowar has shown a slowdown in production growth rate in recent decades almost entirelydriven by declining area growth rate. Production variability has also widened during themost recent decade compared with previous performance due to area variability (FigureII.5.5).

With the exception of Rajasthan, there has been a slowdown in jowar production growthin most states with the largest growing state Maharashtra registering the steepest decline.Almost all the major growing states continuously registered a worsening area growth.Trend in yield growth turned negative during the most recent decade in Maharashtra butshowed some improvement in Karnataka, Madhya Pradesh and Uttar Pradesh.


21

Jowar has showna slowdown inproductiongrowth rate inrecent decadesalmost entirelydriven bydeclining areagrowth rate.

Figure II.5.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Jowar across States

Maharashtra is in the low yield zone with lower variability in yield. Karnataka, Rajasthanand Tamil Nadu have lower growth rate of yield and also higher variability. In these states,efforts to raise yields would be appropriate. In UP, Andhra Pradesh and Madhya Pradesh,measures to maintain stable growth and focus on technology improvements to push theyield frontier would be necessary (Table II.5.1).

II.6 GramThere has been significant growth in the production of gram in the period 2000–01 to2011–12. With the exception of Uttar Pradesh and Haryana, all the major states growinggram have registered a significant growth in gram production (Figure II.6.1). The highestgrowth of 27 per cent was registered in Gujarat, followed by Maharashtra (11.5 per cent)and Andhra Pradesh. Karnataka and Chhattisgarh also registered high growth rates of 9.5to 10.0 per cent per year during the period. Only Uttar Pradesh registered a negativeproduction growth due to declining trend in area. At the all India level, production growthrate is about 6 per cent, mostly due to high growth rate in area (4.4 per cent) and to alimited extent from yield (1.7 per cent).


22

In UP, AndhraPradesh andMadhya Pradesh,measures tomaintain stablegrowth and focuson technologyimprovements topush the yieldfrontier would benecessary.

There has beensignificant growthin the productionof gram in theperiod 2000–01 to2011–12. With theexception of UttarPradesh andHaryana, all themajor statesgrowing gramhave registered asignificant growthin gramproduction.

Figure II.5.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Jowar at All IndiaLevel: Rolling Estimates for Previous 10-years

Table II.5.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Jowar

Yield growth Yield



Low (<=3% per year) Maharashtra UP

High (>3% per year) Karnataka Andhra Pradesh

Rajasthan Madhya Pradesh

Tamil Nadu

Being a largely rainfed crop, production fluctuations are high in gram with the estimatedCV ranging from about 60 per cent in Gujarat to 22 per cent in Uttar Pradesh, mainly dueto fluctuations in area (Figure II.6.2). At the national level, the CV in production is 22per cent, 15 per cent in area and 8 per cent in yield.

Decomposition of Production change into area and yield contributions shows thatproduction growth was explained mainly by yield changes in some states (Chhattisgarh,Madhya Pradesh, Uttar Pradesh, Karnataka and Andhra Pradesh) and by area inMaharashtra, Haryana and Gujarat leading to equal contributions of area and yield toproduction growth at the national level (Figure II.6.3).


23

Being a largelyrainfed crop,productionfluctuations arehigh in gram withthe estimated CVranging fromabout 60 per centin Gujarat to 22per cent in UttarPradesh, mainlydue tofluctuations inarea.

Figure II.6.1: Trends in Area, Yield and Production of Gram across States: Trend Growth Rates, 2000–01to 2011–12

Fig II.6.2: Pattern of Variability in Gram Area, Yield and Production across States: Coefficient ofVariation (%), 2000–01 to 2011–12

Andhra Pradesh has the highest average yield of 1207 kg/ha among the major statesgrowing gram. The yield gap is the highest in Karnataka, Rajasthan and Maharashtra withthe differential from the highest yield at more than 0.5 tonnes per hectare. The other stateshave a yield gap of 0.3 to 0.5 tonnes per hectare (Figure II.6.4).

Decadal gram production growth has generally trended upward since 2009–10 except fora drop in 2010–11, driven both by area growth and yield growth. Production variabilityhas tended to stabilize (Figure II.6.5). Gram is emerging as a high growth low variabilitypulse crop reflective of the government policy of providing high support prices and thepositive impact of the NFSM.


24

The yield gap isthe highest inKarnataka,Rajasthan andMaharashtra withthe differentialfrom the highestyield at more than0.5 tonnes perhectare.

Figure II.6.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Gram: %,2000–01 to 2011–12

Figure II.6.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Gram across States

Karnataka, Madhya Pradesh, Maharashtra and Rajasthan are states which registeredsignificant production growth in recent decade. Madhya Pradesh recorded the highestgrowth rate in yield during the most recent decade. In Andhra Pradesh, although theproduction growth continues to remain strong, it has slowed down from the double digitgrowth rate experienced since 2005–06. Uttar Pradesh was the only state which registereda negative production growth rate during all the decades.

In terms of variations in the parameters of productivity and variability, the variations in theperformance across states suggests that focus on promoting yield enhancing agronomicpractices along with growth stabilising measures would be appropriate in Haryana,Rajasthan and Karnataka. In Madhya Pradesh, UP and Andhra Pradesh, where yields arerelatively high, the need for further improvement through new varieties and practices bywhich yield fluctuations are reduced (Table II.6.1).


25

In terms ofvariations in theparameters ofproductivity andvariability, thevariations in theperformanceacross statessuggests thatfocus onpromoting yieldenhancingagronomicpractices alongwith growthstabilisingmeasures wouldbe appropriate inHaryana,Rajasthan andKarnataka.

Figure II.6.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Gram at All IndiaLevel: Rolling Estimates for Previous 10-years

Table II.6.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Gram

Yield growth Yield



Low (<=2% per year) Haryana Madhya Pradesh Andhra Pradesh

Karnataka UP

Rajasthan

High (>2% per year) Chhattisgarh

Gujarat

Maharashtra

II.7 TurKarnataka, Gujarat and Orissa registered production growth of 4–7 per cent per yearduring the period 2000–01 to 2012–12. Maharashtra and MP registered moderateproduction growth of 1–2 per cent per year and AP and UP experienced growth rate ofless than one per cent. In Uttar Pradesh growth rate of production was negative with botharea and yield showing declining trend. At the national level production growth was 1.85per cent due to a 1.31 per cent growth in area and 0.54 per cent increase in yield (FigureII.7.1).

Production variability, CV, was generally high exceeding 10 per cent at the national level.Karnataka, Andhra Pradesh, Gujarat and Uttar Pradesh experienced variability in excess of20 per cent of the average annual production during the period 2000–01 to 2011–12. Itwas close to 20 per cent even in the remaining three states of Odisha, Maharashtra andMP indicating the vulnerability of production to weather fluctuations (Figure II.7.2).


26

At the nationallevel productiongrowth was 1.85per cent due to a1.31 per centgrowth in areaand 0.54 per centincrease in yield. Figure II.7.1: Trends in Area, Yield and Production of Tur across States: Trend Growth Rates, 2000–01 to

2011–12

Increase in yield contributed relatively more than expansion in area to production growthin all the major states growing tur. In MP, area had declined. At the national level yieldincrease contributed to 66 per cent of the growth in production (Figure II.7.3).

The highest average yield was in Uttar Pradesh and the yield gap is the highest, about 0.5tonnes per hectare, in the southern states of Karnataka and Andhra Pradesh (FigureII.7.4). Focusing efforts on yield improvements in these two states can lead to significantgains in production as these states together account for about 0.5 million tonnes ofproduction.


27

Increase in yieldcontributedrelatively morethan expansion inarea to productiongrowth in all themajor statesgrowing tur.

The highestaverage yield wasin Uttar Pradeshand the yield gapis the highest,about 0.5 tonnesper hectare, in thesouthern states ofKarnataka andAndhra Pradesh.

Figure II.7.2: Pattern of Variability in Tur Area, Yield and Production across States: Coefficient ofVariation (%), 2000–01 to 2011–12

Figure II.7.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Tur: %,2000–01 to 2011–12

Tur production growth rate has shown significant increase during the most recent decademainly due to higher yield growth. Decadal production variability has remained more orless static (Figure II.7.5).

The highest production growth rate in the most recent decade was registered by MadhyaPradesh, propelled by area growth, followed by Andhra Pradesh. Although productiongrowth in Karnataka is high, there has been a slowdown in the most recent decade vis-a-vis earlier decades. Yield growth remained highest in Gujarat. In Uttar Pradesh, althoughthe production growth is showing some improvement, it continued to remain in thenegative territory


28

Tur productiongrowth rate hasshown significantincrease duringthe most recentdecade mainlydue to higher yieldgrowth. Decadalproductionvariability hasremained moreor less static.

Figure II.7.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Tur across States

Figure II.7.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Tur at All IndiaLevel: Rolling Estimates for Previous 10-years

Although Karnataka and Andhra Pradesh have lower yields, they have registered growthrate of yield of tur in excess of 2 per cent per year. Therefore, sustaining the higher growthrate of yield is important in a number of states where the average yields during the decadewere less than 0.7 tonnes per hectare. After registering higher yield levels, growth rate ofyield had remained low in a number of northern and eastern states. In these states, effortsto identify new varieties and practices to push the yield frontier would be needed (TableII.7.1).

II.8 Rapeseed/MustardMadhya Pradesh, Rajasthan and Gujarat registered the three highest production growthrates in rapeseed/mustard and growth was supported by significant area growth as well(Figure II.8.1). The growth was negative in Uttar Pradesh (-1.17 per cent) or less than 1per cent per year in UP (-1.17 per cent) and West Bengal (0.36 per cent) due to negativegrowth of area. At the national level production growth was an impressive 4.6 per centdue to both increases in area (2.6 per cent) and yield (2.0 per cent).


29

AlthoughKarnataka andAndhra Pradeshhave lower yields,they haveregistered growthrate of yield of turin excess of 2 percent per year.Therefore,sustaining thehigher growthrate of yield isimportant in anumber of stateswhere theaverage yieldsduring the decadewere less than 0.7tonnes perhectare.

Madhya Pradesh,Rajasthan andGujaratregistered thethree highestproductiongrowth rates inrapeseed/mustard and growth wassupported bysignificant areagrowth as well.

Figure II.8.1: Trends in Area, Yield and Production of Rapeseed and Mustard across States: TrendGrowth Rates, 2000–01 to 2011–12

Table II.7.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Tur

Yield growth Yield



Low (<=2% per year) Tamil Nadu Bihar Haryana

Madhya Pradesh Jharkhand

UP

West Bengal

High (>2% per year) Chhattisgarh Andhra Pradesh

Orissa Gujarat

Karnataka

Maharashtra

Rajasthan

However, higher production is also associated with higher variability with CV beinghighest in Rajasthan, Madhya Pradesh, and Gujarat (Figure II.8.2). At the all India levelproduction variability was 22.4 per cent, 16.6 per cent variability in area and 9.8 per centin yield.

Area change contributed to 58 per cent to production change and yield change 42 per cent,at the national level with yield change contribution the largest in West Bengal andHaryana (Figure II.8.3).


30

Area changecontributed to 58per cent toproductionchange and yieldchange 42 percent, at thenational level withyield changecontribution thelargest in WestBengal andHaryana.

Figure II.8.2: Pattern of Variability in Rapeseed and Mustard Area, Yield and Production across States:Coefficient of Variation (%), 2000–01 to 2011–12

Figure II.8.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Rapeseed& Mustard: %, 2000–01 to 2011–12

With Haryana recording the highest yield of 1,422 kg/ha, the yield gap among states islargest in West Bengal followed by Madhya Pradesh, Uttar Pradesh and Rajasthan. Theyield gap is the lowest in Gujarat (Figure II.8.4). By bridging the yield gap, particularly inmajor producing states like Rajasthan and Uttar Pradesh, there is a large potential toincrease rapeseed/mustard production in the country.

Production growth slowed significantly during the most recent decade from the highgrowth of the preceding decade. However, the production variability has tended tostabilize (Figure II.8.5).

All major producing states have registered a deceleration in production growth during themost recent decade, the sharpest decline in Rajasthan, followed by Haryana and MadhyaPradesh due to a deceleration in yield growth. There was no significant change inproduction, area, and yield variability in most states, which continued to remain high.


31

By bridging theyield gap,particularly inmajor producingstates likeRajasthan andUttar Pradesh,there is a largepotential toincreaserapeseed/mustard production inthe country.

Figure II.8.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Rapeseed & Mustard across States

The efforts to improve yield are required in West Bengal and Madhya Pradesh. AlthoughMP has registered high annual growth rate of 2 per cent during the period of 2000–01 to2011–12, the average yields remain lower than one tonne per hectare (Table II.8.1).

In the high yield states, growth rate has slackened in UP and Haryana while it remainsabove 2 per cent in Gujarat and Rajasthan. Gujarat and Rajasthan are high yield, highgrowth and lower variability states for rapeseed and mustard. Sustaining these conditionswill require that markets remain favourable.

II.9 GroundnutRajasthan and Gujarat registered the two highest rates of growth in production ofgroundnut during the period 2000–01 to 2011–12. Among the two, Rajasthan had less than0.3 million hectares under groundnut whereas Gujarat had an average of 1.8 millionhectares. The production growth rate was negative in Karnataka where groundnut wasgrown in about 870,000 hectares during 2000–01 to 2011–12 (Figure II.9.1). There was adecline in area under groundnut in all the major states growing the crop except Rajasthan.Even in Gujarat where production growth was the highest among the states, area under thecrop had declined. At the national level, production growth rate was a modest 1.44 percent, the higher growth rate in yield more than offsetting the negative growth in area.


32

In the high yieldstates, growthrate hasslackened in UPand Haryanawhile it remainsabove 2 per centin Gujarat andRajasthan.Gujarat andRajasthan arehigh yield, highgrowth and lowervariability statesfor rapeseed andmustard.Sustaining theseconditions willrequire thatmarkets remainfavourable.

Rajasthan andGujaratregistered the twohighest rates ofgrowth inproduction ofgroundnut duringthe period2000–01 to2011–12.

Figure II.8.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Rapeseed &Mustard at All India Level: Rolling Estimates for Previous 10–years

Table II.8.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Rapeseed & Mustard

Yield growth Yield



Low (<=2% per year) West Bengal UP Haryana

High (>2% per year) Madhya Pradesh Gujarat

Rajasthan

Production variability was the highest in Gujarat, which also experienced the highestgrowth rate of production, followed by Rajasthan, Andhra Pradesh and Karnataka (FigureII.9.2). Being a mostly rainfed crop, yield fluctuations are the main factor responsible forthe production variability. At the national level, production CV was around 22 per cent,with yield variability at 21 per cent.

As indicated by the decline in crop area across the states it was the improvement in yieldthat helped growth of groundnut production during the period 2000–01 to 2011–12.Decomposition of production growth into growth of area and yield shows that at thenational level, yield growth accounted for 86 per cent of growth in Production. In


33

At the nationallevel, productionCV was around 22per cent, withyield variability at21 per cent.

As indicated bythe decline in croparea across thestates it was theimprovement inyield that helpedgrowth ofgroundnutproduction duringthe period2000–01 to2011–12.

Figure II.9.1: Trends in Area, Yield and Production of Groundnut across States: Trend Growth Rates,2000–01 to 2011–12

Figure II.9.2: Pattern of Variability in Groundnut Area, Yield and Production across States: Coefficient ofVariation (%), 2000–01 to 2011–12

Maharashtra and Tamil Nadu, area growth accounted for 44–52 per cent of productionincrease. In the other states, contribution of yield to production growth was above 60 percent (Figure II.9.3).

The highest average yield during the period 2000–01 to 2011–12 was in Tamil Nadu atclose to 2000 kg/ha and the yield gap is the largest in neighbouring Karnataka at 1,250kg/ha, followed by another neighbouring state of Andhra Pradesh (Figure II.9.4). It willbe worth investigating the reason for this large yield gap among the southern states withmore or less similar growing conditions.


34

The highestaverage yieldduring the period2000–01 to2011–12 was inTamil Nadu atclose to 2000kg/ha and theyield gap is thelargest inneighbouringKarnataka at1,250 kg/ha,followed byanotherneighbouringstate of AndhraPradesh.

Figure II.9.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Groundnut:%, 2000–01 to 2011–12

Figure II.9.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Groundnut across States

Production growth rate has shown a significant improvement in the most recent decade,contributed almost equally by area growth and yield growth. Production fluctuation hasalso slowed down, mainly due to yield stabilisation (Figure II.9.5).

In Gujarat, the production growth has slowed down during the most recent decade fromthe double digit growth experienced during the preceding decade. Production growth ratehas improved in Madhya Pradesh, but slowed in Rajasthan despite being highest amongstates. Production variability continued to remain high in all major growing states

Seven out of nine states have an average yield of more than 1 tonne per hectare. OnlyAndhra Pradesh and Karnataka have registered lower average yield, below 1 tonne per ha(Table II.9.1). Measures to support adoption of inputs and practices to raise yields wouldbe appropriate in these two states.

In the other states average yield is above 1 tonne per ha. Only in Maharashtra, yield growthrate is below 3 per cent per year. Therefore, measures supporting stable yield growth wouldbe needed to maintain growth of production of groundnut. Production variability is also aconcern in most of the states indicating the need for policies that help reduce vulnerabilityof yields to fluctuations in weather.


35

In Gujarat, theproductiongrowth hasslowed downduring the mostrecent decadefrom the doubledigit growthexperiencedduring thepreceding decade.

Figure II.9.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Groundnut at AllIndia Level: Rolling Estimates for Previous 10-years

Table II.9.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Groundnut

Yield growth Yield



Low (<=3% per year) Andhra Pradesh Maharashtra

Karnataka

High (>3% per year) Tamil Nadu Gujarat

Madhya Pradesh

Rajasthan

II.10 SoybeanThe highest production growth rate was in Andhra Pradesh (25.5 per cent), a relativelynew producing state, followed by Madhya Pradesh (10.5 per cent), Rajasthan (9.9 percent), and Maharashtra (7.4 per cent). At the national level, production growth was animpressive 8.8 per cent fuelled by 5.2 per cent increase in area and 3.4 per cent in yield(Figure II.10.1).

Production variability is highest in Andhra Pradesh, followed by Madhya Pradesh andRajasthan and the lowest in Maharashtra (Figure II.10.2). At the national level,production variability is about 31 per cent, with area variability and yield variabilitycontributing almost equally.


36

At the nationallevel, productionvariability is about31 per cent, witharea variabilityand yieldvariabilitycontributingalmost equally.

Figure II.10.1: Trends in Area, Yield and Production of Soybean across States: Trend Growth Rates,2000–01 to 2011–12

Figure II.10.2: Pattern of Variability in Soybean Area, Yield and Production across States: Coefficient ofVariation (%), 2000–01 to 2011–12

Yield change contributed the most to the production change in all major producing statesand at the national level (Figure II.10.3).

The highest average yield of 1,426 kg/ha during the period 2000–01 to 2011–12 wasrealized in Andhra Pradesh, and the lowest in Madhya Pradesh, the largest soybeangrowing state (Figure 10.4). Although AP has the highest yield and MP the lowest, thelatter accounts for more than three times the output of AP. In other words, systematicefforts would be needed to examine the potential to raise productivity within the state also.Bridging the yield gap across states could raise total soybean production in the country.


37

Systematic effortswould be neededto examine thepotential to raiseproductivitywithin the statealso.

Figure II.10.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production of Soybean:%, 2000–01 to 2011–12

Figure II.10.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha)and Yield Gap (deviationfrom highest yield) for Soybean across States

Production growth slowed during the most recent decade from the high growth of thepreceding decade. However, the production variability has tended to stabilise (FigureII.10.5).

Taking 1 tonne per hectare as the threshold level of yield for soybean, only Maharashtrafalls below this yield. Although yield growth in the state is high, further improvements tocatch up with the best yields would increase overall production as Maharashtra has thesecond largest are under the crop after MP (Table II.10.1).

Reducing vulnerability to yield fluctuations would also help in more stable growth ofoutput.

II.11 SugarcaneMaharashtra registered the highest rate of increase in production during the period of2000–01 to 2011–12 among all the major cane growing states. Expansion of area and yieldcontributed to the growth in production. The production growth was the lowest in Punjabamong the various states, mainly due to a negative growth rate in area. In the largestsugarcane growing state of Uttar Pradesh, annual production growth was a modest 0.8 percent, 0.53 per cent growth in area and 0.23 per cent growth in yield. At the national levelannual production growth was 2.1 per cent, 1.34 per cent in area and 0.75 per cent in yield(Figure II.11.1).


38

Taking 1 tonne perhectare as thethreshold level ofyield for soybean,only Maharashtrafalls below thisyield.

Figure II.10.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Soybean at AllIndia Level: Rolling Estimates for Previous 10-years

Table II.10.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Soybean

Yield growth Yield



Low (<=3% per year) Andhra Pradesh

Madhya Pradesh

High (>3% per year) Maharashtra Rajasthan

Along with growth, production was also characterised by variability in terms of CV inMaharashtra. Bihar and Maharashtra registered the highest CV for sugarcane productionand area. In Uttar Pradesh production variability was the lowest at 6.7 per cent,accompanying low growth of production, with no significant year-to-year variations inarea. At all India level CV was 14.2 per cent, 10.5 per cent in area and 5.2 per cent in yield(Figure II.11.2). Being a highly irrigated crop, the variability in production of sugarcane isamong the lowest across food crops.


39

Bihar andMaharashtraregistered thehighest CV forsugarcaneproduction andarea. In UttarPradeshproductionvariability was thelowest at 6.7 percent,accompanyinglow growth ofproduction, withno significantyear-to-yearvariations in area.

Figure II.11.1: Trends in Area, Yield and Production of Sugarcane across States: Trend Growth Rates,2000–01 to 2011–12

Figure II.11.2: Pattern of Variability in Sugarcane Area, Yield and Production across States: Coefficient ofVariation (%), 2000–01 to 2011–12

The relative influence of yield changes on production growth was the largest in UttarPradesh at 60.7 per cent even though the overall rate of increase in production was amongthe lowest in the state. At the national level the relative influence of yield and area changeson production change was 23.6 per cent and 76.4 per cent respectively (Figure II.11.3).Sugarcane is one crop where area changes have dominated production growth among thevarious crops considered in this analysis.

The highest yield was in Tamil Nadu at 103 tonnes/ha. While the yield gap is narrow inKarnataka, Andhra Pradesh, and Maharashtra it is higher in most north Indian stateswith Bihar topping the list. In the largest sugarcane growing state of Uttar Pradesh, theyield gap is about 46 tonnes/ha (Figure II.11.4).


40

The highest yieldwas in Tamil Naduat 103 tonnes/ha.While the yieldgap is narrow inKarnataka,Andhra Pradesh,and Maharashtrait is higher in mostnorth Indianstates with Bihartopping the list.

Figure II.11.3: Contribution of Growth Rates of Area and Yield to Growth Rate of Production ofSugarcane: %, 2000–01 to 2011–12

Figure II.11.4: Pattern of Average Production (Thousand tonnes), Yield (kg/ha) and Yield Gap (deviationfrom highest yield) for Sugarcane across States

There has been no significant change in the decadal production, area, and yield growthover past three years. Production variability also remained more or less stable (FigureII.11.5).

Tamil Nadu was the only state which showed an improvement in decadal productiongrowth recently, while most other states showed a static or slower growth rate comparedto the preceding decade. There has been no significant change in production variabilitywith Maharashtra topping the list followed by Karnataka, Tamil Nadu and AndhraPradesh. Uttar Pradesh experienced the least production variability.

UP is one large state where the cane yields are lower than the other major cane growingstates and it also has the largest area under the crop. Improvement in crop yields in thestate, therefore, can have a significant impact on crop output. The overall variability inyield is relatively less than in the case of other crops. Only Karnataka and Maharashtrahave CV of more than 10 per cent in yield as compared to the other states. Karnataka hasalso registered lower growth rate of production although it has yield level after Tamil Nadu(Table II.11.1).

Efforts to raise the yield frontier appear to be important initiative needed in the case ofsugarcane to sustain the current annual rate of increase in production of 2.1 per cent peryear.


41

There has been nosignificant changein the decadalproduction, area,and yield growthover past threeyears. Productionvariability alsoremained more orless stable.

UP is one largestate where thecane yields arelower than theother major canegrowing statesand it also has thelargest areaunder the crop.Improvement incrop yields in thestate, therefore,can have asignificant impacton crop output.

Figure II.11.5: Trends in Growth (%) and Variability (CV%) Area, Production and Yield of Sugarcane at AllIndia Level: Rolling Estimates for Previous 10-years

Table II.11.1: Pattern of Growth and Variability in Yields during 2000–01 to 20011–12: Sugarcane

Yield growth Yield



Low (<=1% per year) Punjab Andhra Pradesh Karnataka

UP Gujarat

Tamil Nadu

High (>1% per year) Bihar Haryana Maharashtra


42

CHAPTER III

Global Outlook and Implications forIndia

43

The first decade of the 21st century saw much greater volatility in world prices than theprevious 10 years. In the case of rice and wheat, the variability in prices was even greaterthan in the 1980s. In the case of production also, the same pattern of greater variability inthe recent decade was seen across a number of food commodities (Figures III.1 and III.2).A number of factors have influenced this pattern. Macroeconomic shocks or the co-movement of agricultural prices with energy and other commodity markets, and weatherfluctuations have combined to produce sharp changes in prices and production. TheOECD-FAO World Agricultural Outlook 2013 also points out that market reforms in thedeveloped economies also led to price increase in the food sector. Some of the increase involatility has also been a result of higher trend increase in prices and production.

Macroeconomicshocks or the co-movement ofagriculturalprices withenergy and othercommoditymarkets, andweatherfluctuations havecombined toproduce sharpchanges in pricesand production.

Figure III.1: Volatility in Agricultural Prices (Coefficient of Variation %)

Global soft commodity prices eased in 2013 as the U.S. drought induced highs of 2012subsided. Farmers in most countries responded to the relatively high global agriculturalcommodity prices which combined with favourable growing conditions generated a strongglobal supply response, and reduced prices in the short term. Although global prices havedropped significantly, they remain well above the levels that characterized the late 1990sthrough the mid- 2000s (Figure III.3). Weather will continue to be a significant uncertaintyfacing producers and the capacity for global markets to respond to large short termproduction short-falls will be a challenge, with direct impacts on price levels and volatility.

With India emerging as a key player in the global grain, oilseed/vegetable oil, and sugarmarkets, understanding outlook for key trends in global agriculture markets is crucial inorder to support a profitable and competitive domestic agriculture and agri-food sector.


44

Global softcommodity priceseased in 2013 asthe U.S. droughtinduced highs of2012 subsided.

Figure III.2: Volatility in Commodity Production

Figure III.3: Commodity Price Trend in Real Terms

Medium-term Outlook Projection ComparisonsMedium agricultural outlooks present a consistent view on the evolution of agriculturalmarkets over the next 8 to 10 years. The projections generally are based on normal oraverage weather and macroeconomic conditions and assume that current agricultural andtrade policy will remain in force during the projection period.

We have reviewed here medium-term global Agricultural Outlook provided byOECD/FAO, USDA, and FAPRI, the three institutions providing such assessments everyyear.

a. OECD-FAO Outlook for World Agricultural Commodity MarketsThe OECD-FAO annual Agricultural Outlook is prepared jointly by the Organisation forEconomic Co-operation and Development (OECD) and the Food and AgricultureOrganisation (FAO) of the United Nations. The Agricultural Outlook presents aconsistent view on the evolution of global agricultural markets over the next decade andprovides a baseline for further analysis of alternative economic or policy assumptions.Markets for cereals, oilseeds, sugar, meats, dairy products and biofuels are covered. TheOutlook brings together the commodity, policy and country expertise of OECD and FAO,providing an assessment of agricultural market prospects for production, consumption,trade, stocks and prices of the included commodities. This collaborative work aims atbuilding consensus on how global agriculture may evolve in the coming decade and the keydrivers of this evolution.

b. USDA Agricultural OutlookThe Economic Research Service (ERS) of the United States Department of Agriculture(USDA) prepares a set of 10-year projections for U.S. and world agricultural commoditymarkets. The commodity coverage is focused on such products for which US governmentsupport programmes exist. The 10-year USDA baseline is developed using a composite ofmodels and analysis of other available information. The baseline is based on specificassumptions regarding macroeconomic conditions, policy, weather and internationaldevelopments. Projections cover production, demand and trade for agriculturalcommodities, as well as aggregate indicators on the sector, such as farm income.

c. FAPRI Projections for Agricultural MarketsThe Food and Agricultural Policy Research Institute (FAPRI) housed jointly at Iowa StateUniversity and the University of Missouri, Columbia prepares every year multi-yearbaseline projections for US and world agricultural markets. The FAPRI baseline isprepared using comprehensive data, a computer modelling system and an expert reviewprocess. The model FAPRI uses to develop the baseline contains over 3,000 equationsrepresenting supply and demand relationships in the United States and major countriesaround the world, covering the US crops model, as well as the international cotton, dairy,livestock, oilseeds, rice, and sugar models.

GLOBAL OUTLOOK AND IMPLICATIONS FOR INDIA

45

Mediumagriculturaloutlooks presenta consistent viewon the evolution ofagriculturalmarkets over thenext 8 to 10 years.The projectionsgenerally arebased on normalor averageweather andmacroeconomicconditions andassume thatcurrentagricultural andtrade policy willremain in forceduring theprojection period.

Comparison of the Medium-term Projections for IndiaIn this report we have used the most recent of these medium-term projections3 as areference scenario.

The projections using these three models may differ to some extent due to the assumptionsmade regarding various macroeconomic, agriculture and policy variables, weather, andinternational developments, and also partly due to the differences in the modellingframework used to arrive at projections. The projections of production, consumption,trade, stocks and prices of major commodities such as wheat, rice, maize, soybeans, soybeanoil, and price are summarised in Tables III.1 to III.6. The main features of the projectedscenarios pertaining to India and the world are discussed below:

WheatWhile FAO/OECD forecasts Indian wheat production to increase steadily to reach111.8 million tonnes, 14.2 per cent of global production, by 2022, the USDA andFAPRI forecasts are significantly lower at 98 to 99 million tonnes (Table III.1).

Similarly FAO/OECD Indian wheat consumption forecast for 2022 is higher at 108.7million tonnes compared to USDA and FAPRI forecast s of 97 to 99 million tonnes.

FAO forecasts India to be a net exporter of around 3.8 million tonnes of wheat in 2022whereas USDA and FAPRI forecasts India as an insignificant net exporter of wheat.

India’s per capita wheat consumption is forecast to grow steadily during the forecastperiod reaching around 70 kg by 2022, close to the world average.

While FAO/OECD forecasts global real wheat prices to decline marginally until 2017and then increase steadily to reach $274 by 2022, FAPRI forecasts global wheat pricesto remain more or less unchanged at around $290 per metric tonnes, with minor yearto year variations.

RiceFAO/OECD forecast of Indian rice production by 2022 is 113 million tonnes close toUSDA forecast of 110 million tonnes (Table III.2). FAPRI has not included rice in itsforecast model.

Rice consumption is forecast to grow at a lower rate than production by both theagencies at 108.5 million tonnes by FAO/OECD and 103.6 million tonnes by USDA.

India is forecast to remain a net exporter of rice: 5.1 million tonnes by FAO and 6.8million tonnes by USDA.

Per capita rice consumption is forecast to increase marginally at 73.6 kg by 2022 from72.7 kg in 2013.

World rice price is expected to decline until 2017 and then to increase to reach ataround the current level by 2022.


46

India’s per capitawheatconsumption isforecast to growsteadily duringthe forecastperiod reachingaround 70 kg by2022, close to theworld average.

Per capita riceconsumption isforecast toincreasemarginally at 73.6kg by 2022 from72.7 kg in 2013.

3. www.oecd.org/site/oecd-faoagriculturaloutlook/www.fapri.iastate.edu/outlook/2012/www.ers.usda.gov/data-products/international-baseline-data.aspx#37269

Maize and Coarse grainsIndian maize production is forecast to grow modestly to 25 to 26 million tonnes by2022 by both USDA and FAPRI from the 2013 level of 21.5 million tonnes (TableIII.3).

FAO/OECD forecast for total coarse grains is around 53 million tonnes from the 2013level of 41.7 million tonnes.

India is forecast to remain a net exporter of maize with exports forecast at 4.3 milliontonnes by FAO/OECD, 2.4 million tonnes by USDA, and 1.2 million tonnes byFAPRI.

Indian maize consumption is forecast to increase by around 4.5 million tonnes during2013 to 2022.

No significant increase in global maize price from the current level is forecast in themedium-term.


47

Indian maizeconsumption isforecast toincrease byaround 4.5 milliontonnes during2013 to 2022.


48

Table III.1: Projection Comparison – Wheat2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

World Production (TMT)

FAO/OECD 697,361.8 711,766.2 716,474.7 724,075.8 732,378.1 740,406.4 753,604.3 764,617.2 775,384.2 784,493.0

USDA 686,574.0 695,003.0 699,996.0 705,947.0 712,272.0 718,808.0 726,211.0 733,741.0 740,757.0 746,992.0

FAPRI 695,511.1 698,944.3 705,297.0 713,432.6 722,180.8 729,887.8 735,166.5 744,096.5 751,325.9 758,101.4

India Production

FAO/OECD 88,438.3 92,257.7 94,450.6 96,242.1 98,304.2 100,650.1 103,990.9 106,715.5 109,369.7 111,828.7

USDA 92,677.0 93,646.0 94,505.0 95,335.0 96,100.0 96,685.0 97,263.0 97,908.0 98,608.0 99,358.0

FAPRI 86,905.2 90,291.4 90,482.8 91,481.2 92,035.8 93,589.4 94,533.4 95,767.2 96,951.9 98,250.2

World Trade (TMT)

FAO/OECD 135,001.3 137,596.3 140,729.5 141,445.0 143,209.3 143,691.5 145,789.2 147,290.5 149,054.2 150,442.3

USDA 141,543.0 143,596.0 146,135.0 148,583.0 151,013.0 153,370.0 155,930.0 158,588.0 161,171.0 163,731.0

FAPRI 109,277.0 111,344.4 112,195.0 113,677.1 114,344.7 115,600.0 116,794.7 118,158.2 119,656.4 121,153.5

India net exports

FAO/OECD 5,095.1 5,615.5 5,803.6 5,640.9 5,420.6 4,995.5 5,145.7 4,963.2 4,506.6 3,791.1

USDA 5,004.0 3,158.0 2,149.0 1,733.0 1,404.0 1,114.0 912.0 677.0 425.0 217.0

FAPRI 727.8 1,195.9 712.1 516.4 -118.9 288.0 563.6 460.9 461.4 835.0

World Consumption (TMT)

FAO/OECD 692,224.5 700,774.8 712,004.8 723,751.6 733,070.6 742,948.6 753,590.5 763,367.4 773,155.9 782,429.5

USDA 689,866.0 694,800.0 700,575.0 706,541.0 713,225.0 720,164.0 727,311.0 734,545.0 741,546.0 748,126.0

FAPRI 681,726.0 691,541.5 697,056.4 705,493.0 713,542.3 721,931.9 727,644.6 736,121.3 743,772.6 750,913.8

India Consumption

FAO/OECD 86,067.6 87,615.1 89,802.9 91,653.7 93,804.9 96,560.0 99,465.4 102,414.8 105,483.1 108,691.2

USDA 90,298.0 91,454.0 92,564.0 93,652.0 94,691.0 95,578.0 96,448.0 97,364.0 98,319.0 99,310.0

FAPRI 87,599.6 89,104.5 89,663.2 90,876.9 92,012.1 93,186.0 93,872.1 95,192.0 96,396.2 97,330.5

World end Stocks (TMT)

FAO/OECD 188,127.0 199,118.4 203,588.3 203,912.6 203,220.0 200,677.8 200,691.6 201,941.4 204,169.7 206,233.1

USDA 170,890.0 171,093.0 170,514.0 169,920.0 168,967.0 167,611.0 166,511.0 165,707.0 164,918.0 163,784.0

FAPRI 209,706.7 210,857.0 212,845.3 214,533.0 216,919.6 218,623.0 219,891.8 221,614.7 222,915.8 223,851.3

India end Stocks

FAO/OECD 16,475.6 15,502.7 14,346.8 13,294.2 12,372.9 11,467.5 10,847.3 10,184.9 9,564.9 8,911.4

USDA 19,825.0 18,859.0 18,650.0 18,600.0 18,605.0 18,598.0 18,502.0 18,368.0 18,232.0 18,063.0

FAPRI 14,167.9 14,158.9 14,266.4 14,354.4 14,496.9 14,612.4 14,710.2 14,824.4 14,918.7 15,003.4

World Per capita Consumption (Kg)

FAO/OECD 66.1 66.0 66.4 66.5 66.6 66.8 67.2 67.4 67.7 68.0

USDA NA NA NA NA NA NA NA NA NA NA

FAPRI NA NA NA NA NA NA NA NA NA NA

India Per Capita Consumption

FAO/OECD 60.5 60.8 61.7 62.3 63.1 64.3 65.6 66.9 68.2 69.6


FAPRI 72.6 72.9 72.4 72.5 72.5 72.6 72.3 72.4 72.6 72.5

World Price (US$/Tonne)

FAO/OECD 301.3 262.3 256.5 259.4 259.3 266.6 270.0 272.3 273.4 274.2


FAPRI 276.1 288.7 291.0 294.6 290.0 289.3 290.2 287.1 286.5 286.5


49

Table III.2: Projection Comparison – Rice2013 2014 2015 2016 2017 2018 2019 2020 2021 2022


FAO/OECD 493,685.5 500,498.5 506,689.0 512,391.5 518,176.7 523,971.7 530,306.9 536,428.6 542,929.5 549,330.5

USDA 473,257.0 480,497.0 485,139.0 490,378.0 494,525.0 498,714.0 504,289.0 509,618.0 513,537.0 516,863.0


India Production (TMT)

FAO/OECD 102,808.4 104,603.9 105,882.1 106,963.6 107,909.7 108,882.5 109,900.2 110,911.4 111,922.2 112,915.9

USDA 99,899.0 101,929.0 102,681.0 104,721.0 105,733.0 106,719.0 107,617.0 108,434.0 109,227.0 109,976.0


World Trade (TMT)

FAO/OECD 36,503.2 39,387.7 40,653.1 41,238.9 42,069.6 42,668.9 43,283.9 43,845.2 44,446.8 45,041.0

USDA 37,496.0 38,411.0 39,494.0 40,575.0 41,607.0 42,697.0 43,796.0 44,921.0 45,965.0 46,932.0


India net exports

FAO/OECD 6,158.2 6,820.3 7,098.2 6,764.1 6,484.5 6,277.5 6,156.9 5,904.3 5,533.6 5,146.9

USDA 6,831.0 5,754.0 5,500.0 5,750.0 5,910.0 6,049.0 6,254.0 6,409.0 6,573.0 6,750.0



FAO/OECD 486,688.2 496,060.7 505,740.8 510,359.9 517,233.9 524,446.2 531,843.8 538,739.7 545,188.1 551,294.7

USDA 473,806.0 477,242.0 483,757.0 490,104.0 494,895.0 499,113.0 504,361.0 509,840.0 514,309.0 518,192.0


India Consumption

FAO/OECD 97,232.8 98,131.4 99,516.4 101,089.6 102,376.9 103,516.5 104,633.2 105,830.8 107,166.0 108,516.0

USDA 96,986.0 94,943.0 96,508.0 98,265.0 99,427.0 100,489.0 101,335.0 102,152.0 102,898.0 103,570.0



FAO/OECD 179,641.3 184,079.1 185,027.3 187,058.9 188,001.7 187,527.2 185,990.3 183,679.2 181,420.5 179,456.3

USDA 101,704.0 104,959.0 106,341.0 106,615.0 106,245.0 105,846.0 105,774.0 105,552.0 104,780.0 103,451.0


India end Stocks

FAO/OECD 22,417.3 22,069.5 21,337.0 20,446.8 19,495.1 18,583.5 17,693.6 16,869.8 16,092.4 15,345.3

USDA 17,682.0 18,913.0 19,587.0 20,293.0 20,689.0 20,870.0 20,898.0 20,771.0 20,527.0 20,183.0



FAO/OECD 57.5 57.8 58.2 58.2 58.4 58.6 58.9 59.1 59.3 59.4




FAO/OECD 72.7 72.5 72.6 72.9 73.1 73.1 73.1 73.2 73.4 73.6




FAO/OECD 480.9 440.3 423.2 419.3 417.9 426.1 438.0 451.1 462.5 470.3




50

Table III.3: Projection Comparison – Maize2013 2014 2015 2016 2017 2018 2019 2020 2021 2022


FAO/OECD 1/ 1,249,069.8 1,232,561.7 1,234,277.3 1,259,660.8 1,287,602.0 1,312,455.7 1,337,517.7 1,359,430.5 1,381,977.8 1,407,104.5

USDA 959,127.0 950,516.0 948,304.0 971,799.0 990,814.0 1,010,666.0 1,028,387.0 1,046,241.0 1,064,683.0 1,083,441.0

FAPRI 898,823.2 887,659.9 928,636.9 938,292.6 959,530.2 968,167.9 985,439.8 999,183.6 1,014,217.5 1,024,403.2


FAO/OECD 1/ 41,659.3 42,747.2 43,211.6 43,201.9 44,452.5 46,087.4 48,265.8 49,985.3 51,455.4 53,293.0

USDA 21,500.0 21,925.0 22,444.0 22,780.0 23,056.0 23,412.0 23,722.0 24,039.0 24,452.0 24,918.0

FAPRI 21,570.7 21,608.6 23,710.1 24,129.5 25,667.0 25,588.6 26,116.1 26,211.9 26,544.7 26,162.4

World Trade (TMT)

FAO/OECD 1/ 132,101.5 136,110.7 138,439.0 142,023.2 144,694.4 148,865.0 152,284.8 155,792.7 158,472.7 162,149.8

USDA 106,259.0 111,411.0 113,905.0 116,516.0 120,133.0 123,918.0 127,524.0 130,901.0 134,687.0 138,730.0

FAPRI 84,417.0 86,353.9 87,046.4 88,333.9 91,095.1 93,828.6 98,068.4 100,498.4 103,050.4 106,502.7

India net exports

FAO/OECD 2,525.5 3,417.2 3,295.4 2,843.3 3,132.9 3,107.8 3,670.6 3,925.1 4,059.5 4,264.7

USDA 2,991.0 2,991.0 2,940.0 2,799.0 2,698.0 2,599.0 2,540.0 2,488.0 2,426.0

FAPRI 1,506.8 1,564.0 2,794.1 2,750.2 3,567.3 2,972.1 2,907.7 2,397.0 2,101.7 1,223.2


FAO/OECD 1/ 1,203,903.7 1,231,697.7 1,247,310.7 1,267,641.2 1,289,564.2 1,314,146.1 1,338,035.7 1,361,121.9 1,383,999.0 1,408,174.5

USDA 916,099.0 938,668.0 954,127.0 972,850.0 991,294.0 1,010,981.0 1,030,670.0 1,050,068.0 1,069,186.0 1,088,044.0

FAPRI 890,530.7 891,913.9 919,349.5 934,394.9 952,365.4 964,580.2 980,057.0 994,370.9 994,370.9 1,021,977.0

India Consumption

FAO/OECD 1/ 39,020.7 39,766.3 40,583.2 41,099.0 41,993.5 43,361.0 44,913.6 46,353.6 47,633.5 49,241.7

USDA 18,501.0 18,936.0 19,499.0 19,904.0 20,256.0 20,712.0 21,122.0 21,497.0 21,962.0 22,491.0

FAPRI 19,953.8 20,027.4 20,873.9 21,358.8 22,063.4 22,592.4 23,181.6 23,788.9 24,418.2 24,920.9


FAO/OECD 1/ 237,666.2 240,596.7 229,629.7 223,715.7 223,820.0 224,196.0 225,744.4 226,119.4 226,164.7 227,161.0

USDA 161,014.0 172,862.0 167,039.0 165,988.0 165,508.0 165,193.0 162,910.0 159,083.0 154,580.0 149,977.0

FAPRI 126,807.1 119,850.9 126,435.9 127,626.7 132,084.7 132,968.6 135,648.8 137,758.2 139,780.5 139,502.6

India end Stocks

FAO/OECD 1/ 5,618.7 5,836.9 6,039.6 6,282.0 6,538.9 6,779.3 7,022.3 7,276.9 7,536.6 7,809.4

USDA 274.0 272.0 278.0 280.0 281.0 283.0 284.0 286.0 288.0 289.0

FAPRI 673.1 690.4 732.5 753.0 789.3 813.3 840.1 866.1 890.9 909.1


FAO/OECD 1/ 31.7 31.9 32.2 32.5 32.9 33.3 33.8 34.3 34.7 35.2




FAO/OECD 1/ 22.2 22.3 22.5 22.5 22.8 23.3 24.0 24.5 25.0 25.7


FAPRI 8.6 8.4 8.5 8.5 8.6 8.6 8.7 8.7 8.8 8.8


FAO/OECD 243.4 216.4 221.1 227.2 228.2 234.1 236.4 237.7 240.3 240.6


FAPRI 234.1 262.8 253.5 259.4 250.7 252.6 249.6 246.5 243.0 244.2

1/ FAO-OECD Data is for total coarse grains.

Soybeans/ soybean oilUSDA forecasts Indian soybean production at 14.6 million tonnes by 2022 from 11.9million tonnes in 2013. However, FAPRI forecasts no significant increase in soybeanproduction from the current level in the medium-term (Figure III.4).

FAO/OECD forecast of total oilseed production for India is 27.2 million tonnes in2022 compared to 23.9 million tonnes in 2013.

Both FAO/OECD and FAPRI project a decline in global soybean price by 2022.

Indian soybean oil production in 2022 is forecast at 2.3 million tonnes by USDA andlower 1.7 million tonnes by FAPRI consistent with its projection of no significantimprovement in soybean production.

FAO/OECD forecasts total vegetable oil production at 8.7 million tonnes by 2022compared to 7.2 million tonnes in 2013.

India’s soybean oil imports are forecast at 1.4 million tonnes both by USDA andFAPRI.

Total vegetable oil imports are forecast at 14.6 million tonnes by FAO/OECD fromthe 2013 imports of 11 million tonnes.

Global soybean oil price is forecast to remain more or less unchanged at $1160 byFAO/OECD but to increase to $1,250 per tonnes by FAPRI.

SugarThe FAO/OECD forecast of Indian sugar production by 2002 is 31.8 million tonnesand 37.6 million tonnes by FAPRI (Figure III.5).

While FAO/OECD project India to be a net importer of sugar by 2022, FAPRIforecasts India to be a net exporter of around 3 million tonnes.

World sugar price by 2022 is forecast to strengthen to $536 per tonne by FAO/OECDbut to remain more or less unchanged at $582 per tonne by FAPRI.


51

Total vegetable oilimports areforecast at 14.6million tonnes byFAO/OECD fromthe 2013 importsof 11 milliontonnes.

While FAO/OECDproject India to bea net importer ofsugar by 2022,FAPRI forecastsIndia to be a netexporter ofaround 3 milliontonnes.


52

Table III.4: Projection Comparison – Soybean2013 2014 2015 2016 2017 2018 2019 2020 2021 2022


FAO/OECD 1/ 408,196.7 413,970.4 426,990.3 435,659.7 443,725.7 452,515.5 460,665.1 470,910.6 480,754.9 490,460.4

USDA 245,062.0 247,024.0 252,482.0 259,212.0 265,845.0 272,104.0 278,591.0 284,974.0 291,356.0 297,605.0

FAPRI 266,603.1 271,606.3 274,146.9 279,829.6 284,025.6 289,066.9 293,259.8 298,326.1 302,779.9 307,136.4


FAO/OECD 1/ 23,889.9 23,106.2 23,616.2 24,202.5 24,633.4 25,247.3 25,474.6 26,049.1 26,552.4 27,165.3

USDA 11,894.0 12,311.0 12,797.0 13,194.0 13,427.0 13,633.0 13,864.0 14,106.0 14,361.0 14,624.0

FAPRI 10,387.9 10,283.5 10,262.1 10,379.4 10,485.5 10,566.3 10,568.8 10,623.8 10,680.8 10,761.0

World Trade (TMT)

FAO/OECD 1/ 119,620.6 121,133.2 124,798.0 126,778.0 128,588.8 130,563.1 132,360.9 135,366.5 138,336.8 141,194.1

USDA 83,065.0 85,500.0 87,834.0 90,170.0 92,500.0 94,802.0 97,084.0 99,358.0 101,625.0 103,871.0

FAPRI 96,676.0 99,118.5 100,758.5 102,915.1 104,693.3 106,713.9 108,622.1 110,656.3 112,552.4 114,242.0

India net exports

FAO/OECD 1/ 235.4 206.6 143.5 128.2 136.3 182.7 196.0 201.6 201.5 200.3

USDA 22.0 23.0 23.0 23.0 23.0 23.0 24.0 24.0 25.0 25.0

FAPRI 10.0 10.0 10.0 10.0 10.0 10.0 10.0 10.0 10.0 10.0


FAO/OECD 1/ 406,220.6 416,193.7 426,600.9 436,261.5 444,508.6 453,316.6 461,591.0 470,717.2 480,491.9 489,640.0

USDA 241,002.0 245,547.0 247,835.0 253,392.0 259,146.0 264,856.0 271,373.0 277,702.0 284,126.0 290,295.0

FAPRI 268,327.7 273,805.4 276,801.0 281,917.7 286,327.0 291,183.0 295,612.4 300,482.5 305,050.8 309,242.6

India Consumption

FAO/OECD 1/ 23,077.2 23,338.8 23,737.5 24,090.6 24,377.6 24,703.1 25,082.9 25,552.1 26,165.0 26,865.7

USDA 11,853.0 12,276.0 12,762.0 13,162.0 13,399.0 13,604.0 13,834.0 14,077.0 14,331.0 14,594.0

FAPRI 10,314.1 10,260.4 10,243.2 10,346.8 10,456.4 10,536.0 10,542.2 10,595.1 10,655.6 10,735.0


FAO/OECD 1/ 38,455.4 37,228.9 38,615.2 39,010.3 39,224.2 39,420.0 39,491.0 40,681.2 41,941.0 43,758.2

USDA 61,399.0 61,678.0 61,684.0 61,969.0 62,467.0 63,038.0 63,601.0 64,176.0 64,756.0 65,314.0

FAPRI 47,608.2 47,960.6 47,858.6 48,323.0 48,574.4 49,010.6 49,210.4 49,606.3 49,888.0 50,333.6

India end Stocks

FAO/OECD 1/ NA NA NA NA NA NA NA NA NA NA

USDA 275.0 287.0 298.0 307.0 312.0 318.0 324.0 329.0 334.0 339.0

FAPRI 328.8 341.8 350.7 373.2 392.3 412.7 429.3 448.0 463.2 479.2


FAO/OECD 1/ 1,527.3 1,088.1 823.2 806.9 926.3 1,287.8 1,483.6 1,779.0 1,965.0 2,064.2




FAO/OECD 1/ NA NA NA NA NA NA NA NA NA NA




FAO/OECD 564.1 514.0 511.2 507.0 521.7 523.0 530.0 530.5 538.9 540.0


FAPRI 474.6 486.7 500.0 494.5 492.2 485.6 482.9 474.5 470.1 465.0

1/ FAO/OECD data pertain to total oilseeds.


53

Table III.5: Projection Comparison – Soybean Oil2013 2014 2015 2016 2017 2018 2019 2020 2021 2022


FAO/OECD 1/ 163,276.4 166,877.3 170,867.3 174,311.8 177,543.3 181,167.5 184,647.8 188,317.4 192,054.7 195,658.3

USDA 44,824.0 46,490.0 48,100.0 49,491.0 50,818.0 52,252.0 53,791.0 55,239.0 56,728.0 58,182.0

FAPRI 44,061.1 45,129.3 45,744.1 46,712.9 47,570.0 48,510.8 49,390.8 50,346.0 51,269.4 52,122.1


FAO/OECD 1/ 7,409.5 7,532.9 7,647.5 7,767.2 7,883.1 8,033.8 8,179.8 8,319.1 8,496.4 8,694.1

USDA 1,852.0 1,921.0 2,002.0 2,067.0 2,105.0 2,136.0 2,171.0 2,209.0 2,249.0 2,291.0

FAPRI 1,606.0 1,600.6 1,601.6 1,622.1 1,643.4 1,658.6 1,660.7 1,670.8 1,682.5 1,697.5

World Trade (TMT)

FAO/OECD 1/ 66,538.8 66,878.9 68,394.8 69,409.0 71,009.6 72,450.1 74,008.6 75,636.5 76,930.6 78,226.0

USDA 8,887.0 9,435.0 9,588.0 9,685.0 9,876.0 10,060.0 10,252.0 10,430.0 10,600.0 10,761.0

FAPRI 7,754.1 8,085.9 8,348.3 8,608.1 8,875.9 9,145.8 9,410.2 9,683.7 9,969.8 10,259.9

India net exports

FAO/OECD 1/ -11,039.6 -11,312.7 -11,484.3 -11,895.4 -12,316.8 -12,823.8 -13,229.4 -13,651.3 -14,077.2 -14,565.6

USDA -1,058.0 -1,371.0 -1,337.0 -1,295.0 -1,306.0 -1,325.0 -1,344.0 -1,354.0 -1,354.0 -1,351.0

FAPRI -1,044.8 -1,091.7 -1,127.8 -1,166.9 -1,201.9 -1,246.1 -1,300.8 -1,350.7 -1,397.9 -1,435.3


FAO/OECD 1/ 163,674.8 167,851.1 170,636.7 174,892.0 178,328.8 181,803.0 185,296.2 188,987.5 192,620.9 196,243.4

USDA 44,798.0 46,503.0 48,070.0 49,454.0 50,796.0 52,254.0 53,772.0 55,229.0 56,694.0 58,154.0

FAPRI 44,227.6 45,009.9 45,647.7 46,581.6 47,460.8 48,398.3 49,294.5 50,244.4 51,186.4 52,028.3

India Consumption

FAO/OECD 1/ 18,432.3 18,828.2 19,117.2 19,647.8 20,185.0 20,841.3 21,392.3 21,953.4 22,557.2 23,243.7

USDA 2,909.0 3,290.0 3,337.0 3,361.0 3,409.0 3,460.0 3,513.0 3,562.0 3,602.0 3,641.0

FAPRI 2,642.1 2,688.8 2,727.5 2,785.1 2,841.9 2,900.9 2,958.3 3,018.2 3,077.7 3,130.4


FAO/OECD 1/ 22,066.8 21,997.6 23,132.8 23,457.1 23,576.1 23,845.1 24,101.1 24,335.5 24,673.8 24,993.1

USDA 2,930.0 2,917.0 2,947.0 2,984.0 3,006.0 3,004.0 3,023.0 3,033.0 3,067.0 3,095.0

FAPRI 2,843.5 2,887.7 2,909.6 2,966.0 3,000.5 3,038.1 3,059.5 3,086.3 3,094.5 3,113.8

India end Stocks

FAO/OECD 1/ 1,554.8 1,572.1 1,586.6 1,601.5 1,616.4 1,632.7 1,649.6 1,666.7 1,683.1 1,699.1

USDA 153.0 155.0 157.0 158.0 160.0 161.0 163.0 164.0 165.0 166.0

FAPRI 108.7 112.1 114.0 117.8 121.2 125.0 128.2 131.5 134.2 136.7


FAO/OECD 1/ 18.7 19.0 19.0 19.2 19.3 19.4 19.5 19.6 19.8 20.0


FAPRI 6.2 6.3 6.3 6.4 6.4 6.5 6.5 6.6 6.6 6.7


FAO/OECD 1/ 14.2 14.3 14.3 14.5 14.7 15.0 15.2 15.5 15.7 16.0


FAPRI 2.2 2.2 2.2 2.2 2.2 2.2 2.3 2.3 2.3 2.3

World Price (US$/Tonne) 1/

FAO/OECD 1,141.4 1,038.3 1,077.6 1,065.2 1,097.7 1,104.9 1,117.6 1,136.1 1,154.6 1,160.3


FAPRI 1,198.2 1,214.7 1,247.7 1,246.8 1,251.5 1,244.7 1,246.1 1,240.5 1,242.7 1,248.8

1/ FAO/OECD data is for total vegetable oils.


54

Table III.6: Projection Comparison – Sugar2013 2014 2015 2016 2017 2018 2019 2020 2021 2022


FAO/OECD 180,530 182,905 182,381 190,267 195,337 194,724 200,198 203,688 207,946 212,197


FAPRI 175,961 180,430 183,602 187,839 191,729 195,703 200,018 204,212 208,780 212,678


FAO/OECD 26,171 27,001 23,933 28,483 30,708 26,651 29,211 29,450 31,093 31,848


FAPRI 28,815 29,068 30,069 31,560 32,943 34,226 35,309 36,222 36,972 37,633

World Trade (TMT)

FAO/OECD 49,493 50,605 51,686 51,811 53,056 53,508 54,214 54,821 55,396 56,710


FAPRI 47,403 49,726 50,683 51,319 51,779 52,212 52,789 53,365 54,380 55,492

India net exports

FAO/OECD 997 -60 -2,876 115 1,413 -2,050 -785 -766 -1,001 -1,224


FAPRI 2,568 1,816 2,109 2,688 3,179 3,534 3,606 3,526 3,234 2,972


FAO/OECD 173,150 176,418 178,953 182,648 186,366 188,880 192,732 196,773 200,528 204,189


FAPRI 173,989 178,978 182,786 187,011 191,047 195,073 199,347 203,578 208,088 212,153

India Consumption

FAO/OECD 25,999 26,189 26,967 27,604 28,327 29,287 30,150 30,935 31,923 32,772


FAPRI 26,118 27,068 27,828 28,729 29,628 30,561 31,562 32,562 33,598 34,546


FAO/OECD 70,696 70,752 67,722 68,854 71,310 70,609 71,498 71,804 72,578 73,906


FAPRI 32 34 35 36 36 37 37 38 39 39

India end Stocks

FAO/OECD 13,075 13,948 13,789 14,554 15,521 14,935 14,781 14,062 14,234 14,535


FAPRI 6,987 7,170 7,303 7,445 7,580 7,712 7,853 7,987 8,127 8,242


FAO/OECD 24 25 25 25 25 25 25 26 26 26




FAO/OECD 20 20 21 21 21 22 22 22 23 23


FAPRI 21 22 22 23 23 24 24 25 25 26


FAO/OECD 499 504 531 513 507 539 545 541 541 536


FAPRI 582 574 585 585 589 592 588 586 577 582

III.2 OECD/FAO Medium-term Projections – India vs.Other Major PlayersThe OECD/FAO Medium-term assessment is used as reference to assess India’s statusvis-a-vis other major players with regard to the supply/demand balance for majoragricultural commodities. This is summarized below:

WheatGlobal wheat area is forecast to increase by around 9 million hectares during theforecast period to 231.8 million hectares by 2022 with most of the increase occurringin India, Russia and Ukraine. Almost one-third of the area increase is forecast to be inIndia reaching around 31 million hectares. Area expansion in most other majorproducing/exporting countries such as the United States, China, Canada, Australia andEU is expected to be marginal or negative.

Global wheat production is forecast to increase by around 87 million tonnes (12.5 percent) to 784.5 million tonnes during 2013 to 2022, with India’s contribution at 23.4million tonnes, followed by Russia (12 million tonnes), China (6.5 million tonnes),Ukraine (4 million tonnes),and Australia (2 million tonnes). While, production isforecast to remain more or less unchanged in Canada, a 3 million ton decline in U.S.wheat production is forecast.

Although India’s wheat yield is forecast to increase from the current 3.1 tonnes perhectare to 3.5 tonnes per hectare, matching the global wheat yield, and yields in mostmajor exporting countries, it will continue to remain significantly below the Chinesewheat yield forecast to reach 5.3 tonnes per hectare from the current 5 tonnes perhectare.

Global wheat trade is forecast to increase to 150 million tonnes, an increase of around15 million tonnes from the current level.

Russia is likely to emerge as the leading wheat exporter with exports forecast at 21million tonnes, closely followed by the United States and Canada with somewhat lowerexports. Other major exporters will be Australia, European Union, and Ukraine. Indiais forecast to remain a net exporter of wheat of around 4 million tonnes, whereas Chinawill remain a net importer.

India’s annual per capita wheat consumption is expected to grow to 69.6 kilogramsclose to the world average but significantly below per capita consumption in majorwheat exporting countries such as the United States, Canada, Europe, Australia, andRussia, where wheat is the major staple unlike in most Asian countries where rice is themajor staple.

RiceGlobal rice area is forecast to increase marginally to around 165 million hectares fromthe current 162 million hectares, with the growth mostly confined to smaller producingcounties. Rice area in all major producing states such as India, China, Thailand, andVietnam is forecast to decline marginally.

Global rice production is forecast to increase by around 55 million tonnes to 549million tonnes with India forecast to contribute 10 million tonnes to the increasereaching 113 million tonnes. Rice production in Thailand and Vietnam is forecast to


55

Although India’swheat yield isforecast toincrease from thecurrent 3.1 tonnesper hectare to 3.5tonnes perhectare, matchingthe global wheatyield, and yields inmost majorexportingcountries, it willcontinue toremainsignificantlybelow the Chinesewheat yieldforecast to reach5.3 tonnes perhectare from thecurrent 5 tonnesper hectare.

Global riceproduction isforecast toincrease byaround 55 milliontonnes to 549million tonneswith Indiaforecast tocontribute 10million tonnes tothe increase.

increase by 3 million tonnes to 28 million tonnes and 32 million tonnes respectively,whereas China’s production is forecast to decline by 3 million tonnes to 137 milliontonnes. Significant increase in production is forecast in Indonesia (6 million tonnes),Bangladesh (6 million tonnes), Philippines (3 million tonnes), and African countries(10 million tonnes).

India’s rice yield is forecast to increase only marginally to 2.7 tonnes per hectare fromthe current 2.4 tonnes per hectare, although close to Thai yield, is significantly belowthe world average yield of 3.3 tonnes/ha and Chinese and Vietnamese yield of 4.8 and4.4 tonnes/ha, respectively.

Global rice trade is forecast to increase by around 8 million tonnes to 45 million tonneswith most of the increase confined to Thailand and Vietnam. Indian rice exports areforecast to decline somewhat to 5.3 million tonnes, mostly basmati rice.

India’s per capita ice consumption is forecast to grow only marginally to 73.6 kgcompared with the global average of 59.4 kg, but significantly below that of thepredominantly rice consuming countries such as Vietnam (171 kg) and Thailand(133.5 kg)

Coarse grainsWorld coarse grain area is forecast to reach 352 million hectares by 2022 from the 2013level of 334 million hectares. India’s coarse grain area is forecast to increase by 3 millionhectares to 31.5 million hectares by 2022, the third largest after China (38.7 millionhectares) and the United States (36.4 million hectares).

India’s coarse grain production is forecast to increase modestly to around 53 milliontonnes from the current 42 million tonnes, one of the lowest among major producingcountries such as the United States (371 million tonnes), China (257 million tonnes),and Brazil (80 million tonnes). Most of the increase in production is expected to be inmaize.

Per hectare yield of coarse gains in India is forecast to remain one of the lowest amongall major coarse grain producing countries at 1.7 tonnes/hectare compared with theUnited States (10.2 tonnes), China (6.6 tonnes), Argentina (5.9) and Brazil (4.6tonnes) and world (4 tonnes).

Global coarse grain trade is forecast to increase to 160 million tonnes by 2022 from thecurrent 130 million tonnes. Most of the increase is in the United States reaching 61million tonnes, followed by Argentina (26 million tonnes) and Brazil (10 milliontonnes). Despite lower production, Indian exports are forecast at around 4 milliontonnes. China, despite high production, will remain a net importer of coarse grainsforecast at 13 million tonnes.

OilseedsGlobal oilseed area is forecast to increase by around 15 million hectares to 204 millionhectares with most of the increase in Brazil, Argentina and India. India’s total oilseedarea is forecast to increase by around 2 million hectares to 26 million hectares. Oilseed(mostly soybeans) area in Brazil is forecast to increase by 4 million hectares and inArgentina by 2 million hectares, whereas no appreciable expansion in oilseed area isforecast in United States, China, and Canada.

Although India ranks third in the world in oilseed planted area after United States and


56

India’s rice yield isforecast toincrease onlymarginally to 2.7tonnes perhectare from thecurrent 2.4tonnes perhectare, althoughclose to Thai yield,is significantlybelow the worldaverage yield of3.3 tonnes/ha andChinese andVietnamese yieldof 4.8 and 4.4tonnes/ha,respectively.

Per hectare yieldof coarse gains inIndia is forecast toremain one of thelowest among allmajor coarsegrain producingcountries at 1.7tonnes/hectarecompared withthe United States(10.2 tonnes),China (6.6tonnes),Argentina (5.9)and Brazil (4.6tonnes) and world(4 tonnes).

Brazil, in oilseed production the country ranks fifth after the U.S., Brazil, Argentinaand China at 24 million tonnes because of low yields. While most major oilseedproducing countries have yields ranging from 2 to 3 tonnes per hectare, Indian oilseedyield is 1 tonne per hectare, with no increase forecast in the medium-term.

Nevertheless, India is forecast to remain a modest exporter of oilseeds, mostly HPSpeanut. The U.S., Brazil, Argentina, and Canada will continue as major exporter ofoilseeds, with China remaining as the largest importer, importing annually around 64million tonnes gradually increasing to 82 million tonnes by 2022, more than threetimes India’s annaul oilseed production, despite producing almost twice India’sproduction.

Vegetable Oils and Oilseed MealIndia’s vegetable oil production at around 7.5 million tonnes now is forecast to increasemodestly to 8.5 million tonnes by 2022 as global vegetable oil production increasesfrom 163 million tonnes to 196 million tonnes. Most of the increase in world vegetableoil production is forecast to be palm oil in Indonesia and Malaysia and soybean oil inArgentina and Malaysia. India ranks the lowest among major vegetable oil producingcountries.

Because of lower production, India’s vegetable oil imports are forecast to reach over 14million tonnes by 2022 from the current 11 million tonnes, thus emerging as thetopmost importer of vegetable oils replacing China. Palm oil from Indonesia andMalaysia, soybean oil from Argentina, Brazil, and rapeseed oil from Canada remain tobe the major source of vegetable oils.

Even with such large imports, India’s per capita vegetable oil consumption is likely toremain low at around 16 kilograms, compared with 20 kgs world average, 26 kilogramsin China and 33 kilograms in the United States. If the vegetable oils demand increasesmore than at the forecast rate due to higher income growth, import requirements willbe even higher.

Indian oil meal production is forecast at 23 million tonnes by 2022 from the present 20million tonnes but significantly below those of other major producing counties such asChina (80 million tonnes), United States (46 million tonnes), Argentina (43 milliontonnes) and Brazil (39 million tonnes).

Despite lower production, India will continue to remain an exporter of oil mealsreaching 6 million tonnes by 2022, whereas China with record oil meal production willcontinue to remain a net importer of 6 million tonnes of oil meal.

India’s oil meal consumption is among the lowest compared with most other majorcountries such as China, Unites States and Brazil.

Sugarcane and sugarIndian sugar cane area, fluctuating cyclically, is forecast to reach 4.4 million hectares by2022, 16 per cent of global sugarcane area. Largest increase in sugarcane area is forecastin Brazil, reaching 11.8 million hectares from the current 9.4 million hectares.

Global sugar cane production is forecast at 2 billion tonnes in 2022, an increase ofaround 15 per cent over the 2013 production, with India’s production forecast at 295million tonnes (15 per cent of global production) ranking the second largest producer.Brazil will continue to remain the largest producer of sugarcane with production


57

India is forecast toremain a modestexporter ofoilseeds, mostlyHPS peanut. TheU.S., Brazil,Argentina, andCanada willcontinue as majorexporter ofoilseeds, withChina remainingas the largestimporter,importingannually around64 million tonnesgraduallyincreasing to 82million tonnes by2022, more thanthree timesIndia’s annauloilseedproduction,despite producingalmost twiceIndia’sproduction.

Despite lowerproduction, Indiawill continue toremain anexporter of oilmeals reaching 6million tonnes by2022, whereasChina with recordoil mealproduction willcontinue toremain a netimporter of 6million tonnes ofoil meal.

forecast at 900 million tonnes, three times India’s production, with China ranking thirdwith 145 million tonnes.

While sugarcane production in India fluctuates cyclically, production in most othercountries shows a steady upward trend.

Like most other commodities, sugarcane yield in India at 68 tonnes per hectare isbelow the world average yield of 73 tonnes per hectare and yields in other majorproducing counties such as Brazil (76 tonnes), China (73 tonnes), Thailand (82tonnes), and Australia (89 tonnes).

India’s share in global sugar production in 2022 is forecast at 15 per cent at around 32million tonnes. Brazil with a production of 48 million tonnes in 2022 will continue tobe the largest sugar producing country.

Unlike in Brazil where almost 50 per cent of sugarcane production goes in theproduction of ethanol, no sugarcane is used in India for ethanol production, which ismostly based on molasses.

India will remain the largest consumer of sugar in the world forecast at around 33million tonnes. Nonetheless, per capita sugar consumption at 23 kilograms will remainbelow the world average of 26 kilograms and significantly below the per capitaconsumption in Brazil (76 kilograms) and Thailand (50 kilograms) but above theChinese per capita consumption of around 14 kilograms.

Global sugar trade is forecast at 63 million tonnes by 2022 with India remaining animporter of around 1 million tonnes of sugar. Brazil with net exports of 32 milliontonnes and Thailand with net exports of 10 million tonnes will remain the largest sugarexporting countries.


58

India’s share inglobal sugarproduction in2022 is forecastat 15 per cent ataround 32 milliontonnes. Brazilwith a productionof 48 milliontonnes in 2022will continue to bethe largest sugarproducingcountry.

The Macroeconomic EnvironmentThe medium-term assessment presented in September 2013, pointed to the slower growthprospects for the food sector relative to the experience of the recent years. One of factorsinfluencing such a pattern is the slower growth in consumption demand for staple fooditems such as cereals and also the need for increasing production mainly based on yieldimprovements per unit of land as scope for further expansion of land area under crops islimited. Nevertheless, given the current lower levels of consumption of food items in thecountry relative to the more developed countries and the shifts in consumption patternfrom basic foods to high value foods growth of 3-4 per cent per year over the medium-term may be necessary for the food sector.

In the September 2013 report, we also pointed to the factors influencing the medium-termoutlook for the food sector. At the level of overall economy, annual growth rate of GDPwas projected at 6.5 per cent over the period 2014–20. While the growth performance mayimprove, these projections are also consistent with the global projections released by theInternational Monetary Fund in its April 2014 World Economic Outlook. The overallmacroeconomic conditions, therefore, remain moderately robust both in terms ofproviding adequate domestic demand for the sector and also allowing scope for publicinvestment in areas relevant for food and agriculture. The relatively low level of incomethat the sector provides to the small holdings also emphasises the need for improvingproductivity of land. Achieving higher productivity levels is also critical for the sector toretain its competitiveness in international markets.

While the core set of parameters affecting supply and demand balances of foodcommodities have not changed significantly since the September 2013 report, theexperience of persistent and high rate of food inflation in the recent five year period hasemphasised the need for sustaining adequate supply response of the sector. It is in thiscontext that we have reviewed the factors influencing the supply- demand balances for themajor commodities again in the present report highlighting the need for sustaining growthof productivity even as the short term fluctuations affect the output.

Trends in Agricultural Output and Factors Influencing The average annual growth rate of GDP from agriculture and allied sectors over five-yearperiod has varied between 3 and 4 per cent from 2008–09 onwards. Taking only agriculturesector, which comprises of crops and livestock output the five-year growth rate hasgenerally followed the pattern of agricultural and allied sector. Only during the five-yearperiod of 2008–09 to 2012–13, the average growth rate fell below 3 per cent in the case ofagriculture sector. The decline to below 3 per cent medium-term growth rate occurred asannual growth rate fell below 1 per cent in 2008–09 and 2009–10 and to 1.42 per cent in2012–13. In all these three years monsoon rainfall was below the long period average(LPA). The five-year period ending in 2007–08 registered an average rate of growth of 5

CHAPTER IV

An Assessment of the Medium-termProspects

59

The relatively lowlevel of incomethat the sectorprovides to thesmall holdingsalso emphasisesthe need forimprovingproductivity ofland. Achievinghigherproductivitylevels is alsocritical for thesector to retain itscompetitivenessin internationalmarkets.

The averageannual growthrate of GDP fromagriculture andallied sectorsover five-yearperiod has variedbetween 3 and 4per cent from2008–09onwards.


60

Deficiency inrainfall can havesignificant impacton the medium-term outlook butthere may beother factors thathave sustainedthe generalmomentum of thegrowth of thesector.

Increase in thecoverage of croparea underirrigation, moreintensive use ofinputs andadoption ofpractices and cropvarieties that canreduce the impactof adverse naturalconditions havebeen the factorssustaininggrowth.

per cent in the agriculture sector. However, even during this five-year period, the monsoonrainfall was below LPA in three years. Thus, deficiency in rainfall can have significantimpact on the medium-term outlook but there may be other factors that have sustainedthe general momentum of the growth of the sector.

Increase in the coverage of crop area under irrigation, more intensive use of inputs andadoption of practices and crop varieties that can reduce the impact of adverse naturalconditions have been the factors sustaining growth.

The cropping intensity, percentage of cultivated land that is sown more than once hassteadily increased from a 5-year average of 33 per cent in 2000–01 to an average of 38 percent for the 5-year period ending in 2010–11. The irrigated area as a percentage of grosscropped area increased from an average of 40.8 per cent for the 5-year period ending2000–01 to 45.1 per cent for the 5-year period ending in 2010–11. While there are limitsto increasing the coverage of irrigation, more efficient ways of irrigation can extendbenefits of irrigation to larger areas. Fertiliser consumption per hectare also increased from105 kg per hectare of NPK in 2005–06 to about 140 kg per hectare in 2011–12. The trendsin production also point to differential rates at which output has changed over timeresponding to both production and demand environment. The fruits and vegetable outputgrowth has exceeded the growth in the production of rice and wheat, the two main cereals.

Figure IV.1: Average Annual Rate of Growth of GDP from Agricultural and Allied Sectors on Rolling 5-Year Period

Table IV.1: Indicators of growth of food output Indicator Average for 5-year period ending

2005–06 2010–11Cropping intensity 34.52 38.00Gross irrigated area as % of Gross cropped area 42.20 45.13Fertiliser use per hectare (NPK) 95.1 127.4Average Index of Production Rice 100 115Wheat 100 124Fruits & vegetables 100 150Oilseeds 100 112

Note: The Index of production derived from data on index of production available from the MOA and data on value of output in constant prices availablefrom Central Statistics Organisation.

Although both supply and demand conditions are influenced by the government policyinterventions, the output changes have also been responding to underlying demand andprice signals. The MSP is one of the key policy measures that influence allocation ofresources by the farmers among crops. The pattern of MSP over time has now placedoilseeds, pulses and sugarcane having received the highest increase over its level in 2000–01in comparison to the many other crops for which support prices are announced. Whilesome of this increase in the MSP for pulses has occurred in the recent years, the MSPshave signalled the need for increasing production of pulses and oilseeds in the recent years.

The prices of food commodities increased sharply in the case of a number of commoditiesin the period 2005–06 to 2009–10 and the increase was sustained upto 2012–13. Even in2013–14, the pace of increase in prices remained high in the case of rice, wheat and cereals,sharply increased in the case of vegetables but prices remained relatively stable or declinedmoderately in the other cases. While the sharp increase in the price of cereals may beattributed to the increase in MSP, the rise in milk, fruits and vegetables is a consequenceof rising demand as average income levels increased.

AN ASSESSMENT OF THE MEDIUM-TERM PROSPECTS

61

Although bothsupply anddemandconditions areinfluenced by thegovernmentpolicyinterventions, theoutput changeshave also beenresponding tounderlyingdemand and pricesignals.

The prices of foodcommoditiesincreased sharplyin the case of anumber ofcommodities inthe period2005–06 to2009–10 and theincrease wassustained upto2012–13.

Figure IV.2: Pattern of change in MSP: the MSP in 2013–14 with its value in 2000–01=100

Table IV.2: Wholesale Price Index of Selected Food Commodities: % change year on yearCommodity Average per year during

2000–01 to 2005–06 to 2008–09 to 2011–12 2012–13 2013–142004–05 2009–10 2012–13

Rice -0.36 9.65 9.75 3.05 12.69 16.50

Wheat 1.06 10.84 7.87 -1.84 15.51 9.21

Cereals 0.03 10.04 9.42 3.87 13.41 12.87

Pulses 1.82 14.41 11.04 2.52 19.57 -5.31

Fruits 6.10 6.42 10.74 14.22 1.30 7.47

Vegetables 3.64 10.34 9.16 -1.95 17.19 40.33

Edible oils 5.35 3.02 5.19 12.56 9.13 -0.75

Sugar 1.95 12.94 17.05 5.10 11.34 -2.43

Milk 4.51 8.08 12.81 10.31 7.24 6.03


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There have alsobeen changes inthe consumptionpattern of food inthe country due tothe rising incomelevels and alsopreferences. Thelonger termtrends indicatefaster growth inthe consumptionof fruits andvegetables andlivestock productsthan the cereals.

The faster increase in prices of food commodities is also illustrated in Figure IV.3. Thecumulative effect of supply-demand pressures and the policy measures has been the rise inthe prices of milk, fruits, pulses and vegetables more than in the case of cereals, edible oilsand sugar.

There have also been changes in the consumption pattern of food in the country due tothe rising income levels and also preferences. The longer term trends indicate faster growthin the consumption of fruits and vegetables and livestock products than the cereals. Thedivergence in the rates of change accelerated in the 1990s as compared to the previousyears.

Figure IV.3: Pattern of changes in wholesale prices: Average WPI with TE 2000–01=100

Figure IV.4: Trends in the Index of Per capita Private Final Consumption Expenditure (2004–05 prices)with 1950–51=100


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The compositionof output of theagriculturalsector alsochanged with theoutput of fruitsand vegetablesand livestockproductsincreasing at afaster pace thanthe growth ofcereals.

The changing consumption pattern was a stimulus to producers to allocate more resourcesto the production of commodities where demand was growing faster. The composition ofoutput of the agricultural sector also changed with the output of fruits and vegetables andlivestock products increasing at a faster pace than the growth of cereals. This pattern isillustrated in Figure IV.5 for the five- year period ending 2012–13. The value of output hasgone up also because of higher value of output per hectare of land because of changes inthe composition of output.

Projection of Medium-term OutlookThe medium-term production scenario was developed in the case of cereals and oilseedson the basis of estimated crop area and yield relationships. Projections were obtained basedon two sets of assumptions relating to input and output prices and expansion of irrigatedarea. The projected growth rate of production of major food commodities is summarisedin Table IV.3. In addition, for a comparison, production growth rates based on the trendgrowth rates during the period 2008–09 to 2011–12 and 2012–13. In the case of pulses,vegetable oils, sugarcane, sugar, potato, onion, banana and milk medium-term projectionsare based on the recent trends in production.

Figure IV.5: Index of value of output in constant 2004–05 prices with 2004–05 output=100: Selectedcommodities

There are some differences in the projections provided in September 2013 and the updatedprojections of output growth. The current estimates of output growth rates are lower thanthe previous assessment in September 2013 in the case of wheat, rice and oilseeds. Therange of updated growth rates has narrowed in the case of coarse grains but with a declinein the average of the projected range. The projected growth rates based on trend analysisare also lower in the case of sugarcane, potato and onion.

The key drivers of demand for food commodities over the medium-term of next 5-6 yearsare the population growth and income growth of the population. The patterns that haveemerged in the past decade have shown that demand for non-foodgrain commodities suchas fruits and vegetables, livestock products, edible oils and sugar has increased faster thanthe demand for cereals. As cereals form the basic staple food for the population, theNational Food Security Act of 2013 aimed to provide rice, wheat and other cereals athighly subsidised rates to two thirds of the population. Over the medium-term, thisapproach may also accelerate demand for non-cereal food commodities as purchasingpower of the consumers would increase due to subsidies on cereals.

The demand for food commodities has been examined in terms of (1) domestic demandand (2) export demand. Domestic demand is related to population growth andconsumption expenditure elasticity of the commodity and overall growth rate ofpopulation. As pointed out earlier, in the Medium-term Outlook Report of September2013, we had provided projected growth of demand for the food commodities based on thegrowth of GDP of 6 per cent over the medium-term which also comprised of annualpopulation growth rate of 1.37 per cent. In the present report we have re-estimated thegrowth of domestic and export projections taking into account the more recent data for2012–13. The export demand has been estimated based on assumptions relating to worldGDP growth, exchange rate and domestic prices. The projections of domestic and exportdemand are summarised in Table IV.4.


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The currentestimates ofoutput growthrates are lowerthan the previousassessment inSeptember 2013in the case ofwheat, rice andoilseeds.

The key drivers ofdemand for foodcommodities overthe medium-termof next 5-6 yearsare the populationgrowth andincome growth ofthe population.

Table IV.3: Average Growth Rate per cent of Production of Selected Food Commodities: ActualProduction Trends in 2008–13Commodities Average % YOY OECD/FAO Projections NCAER MTOR

(June 2013)2008–12 2008–13 2014–21 Sep(2013) May (2014)

2014–2020 2014–2021

Wheat 3.34 3.62 2.69 1.31-1.69 1.14-1.38

Rice 1.77 1.96 1.07 2.47-2.62 2.17-2.29

Coarse Grains 0.76 0.70 2.68 1.27-2.96 1.56-2.12

Oilseeds 1.85 1.81 1.35 4.47-4.75 3.33-4.39

Vegetable oils 1.75 3.61 1.73 NA 4.0

Sugarcane 0.18 0.49 1.35 3.00 2.0

Sugar 3.06 2.88 2.68 NA 4.0

Pulses 5.0 5.1 2.0 2.0

Potato -- 5.9 7.0 6.0

Onion 7.6 3.2 5.0 4.0

Banana -- 1.9 5.0 5.0

Milk 4.3 4.2 3.8 3.8

Note: OECD/ FAO Projections are from World Agricultural Outlook Report; MTOR = Medium-term Outlook Report. In the case of potato, banana andmilk the trend growth rate for the period 2008–09 to 2012–13 was calculated by truncating the annual growth rate to +/- 10 per cent, to reduce theimpact of extreme year-to-year fluctuations on average growth rate.

The projected growth of domestic demand is lower in the updated outlook in the case ofwheat and coarse grains but remains unchanged in the case of rice, partly reflecting thenegative expenditure elasticity for these commodities. The current projection of domesticdemand is higher than the September 2013 projections in the case of pulses, which alsoreflects the positive expenditure elasticity.

In the case of other commodities, we have retained the growth rates of demand as in theSeptember 2013 MTAOR. While there are some changes in the projected demandprospects, the projections essentially reflect the differences in consumer demandpreferences as income levels rise. The changes in output composition in favour of non-cereal commodities in domestic demand are projected to continue.

We should also point out that the projected demand growth for banana is actually basedon the expenditure elasticity for fruits as a group. The demand growth at the commoditylevel, therefore, should be taken as indicative as it appears to be over stated. The exportdemand is projected at a slightly higher pace for cereals than estimated in the previousreport.

The emerging differences in projected domestic production and domestic demand areillustrated in Figure IV.6 below.


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The projectedgrowth ofdomestic demandis lower in theupdated outlookin the case ofwheat and coarsegrains butremainsunchanged in thecase of rice, partlyreflecting thenegativeexpenditureelasticity forthesecommodities.

Table IV.4: Projected Growth in Domestic and Export Demand for Food Commodities over the Medium-term (2014–2020)Commodities Growth in domestic demand (% per year)* Growth in export demand (% per year)**

2014–2020 2014–2021 2014–2020 2014–2021 (Sep 2013 MTAOR) (May 2014 MTAOR) (Sep 2013 MTAOR) (May 2014 MTAOR)

Rice 0.94 0.94 5.9 7.06

Wheat 1.94 1.51 NA 0.27

Coarse Grains 3.19 2.56 11.1 13.33

Total cereals 1.75 1.46 NA 10.07

Pulses 1.38 1.66 - -

Foodgrain 1.72 1.48 8.4 10.07

Edible oil 3.32 3.32 - -

Sugar 4.1 4.1 -

Potato 5.0 5.0 -

Onion 5.0 5.0 -

Banana 9.1 9.1 -

Milk 3.4 3.4 -

Note: * In the case of rice, wheat, coarse grains, pulses and foodgrains domestic demand includes demand for seed, feed and an allowance forwastage besides the consumption demand. In the case of sugar, potato, onion, banana and milk the growth rates are derived from estimatedexpenditure elasticities and assumptions of population and income growth. ** Export demand projections are made only in the case of selected commodities.

In the case of rice, vegetable oils, pulses, potato and milk, the production growth isprojected to be faster than growth rate of domestic demand. However, it should be pointedout that the initial levels of gap between domestic production and demand in the case ofpulses and vegetable oils imply that the need for imports will remain in the twocommodities. In the case of rice, the scope for exports will remain in the medium-term. Inthe case of wheat, growth of domestic demand is projected to be higher than productionand scope for exports may decline. In the case of onion and banana, the demand growth isgreater than production but in milk and potato, the pattern is reversed.

The results point to the need for measures to support growth in production and suppliesin the case of wheat, coarse grains, onion and banana (or fruits more generally). Greaterattention to development of markets would be needed in the case of rice, potato and milk.In the case of sugar, the current pace of production matches the growth rate of demandand efforts to improve productivity would result in scope for exports over the medium-term.


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In the case of rice,vegetable oils,pulses, potato andmilk, theproductiongrowth isprojected to befaster thangrowth rate ofdomesticdemand.

Figure IV.6: Comparison of growth of production and domestic demand for the major food commoditiesin the Medium-term: 2014–2021

India’s overall macroeconomic conditions appear to be on the path to recovery to registerimproved growth, moderate rate of inflation and investments in infrastructure that cancatalyse growth in the other sectors. While the GDP growth for 2012–13 and 2013–14has been below 5 per cent mark, the narrowing of external current account deficit,improved capital inflows, compression of fiscal deficit and deceleration of price inflationhave led to some buoyancy in the capital markets as well. Aided by the improved globaleconomic conditions India’s economic growth rate is now expected to be 6.5-7 per centover the medium-term of 2014–15 to 2020–21. With the new government taking charge,fresh policy initiatives to accelerate growth and development are expected to be taken up.

The medium-term outlook projections for 2013–2022 presented by OECD-FAO WorldAgricultural Outlook 2013, indicates slower growth of agricultural production growth ingeneral and for production of major food commodities in the projection period ascompared to the experience of the recent decade. The crop prices are projected to moderatein the initial five years of the projection period and then firm up in the next five years. Thelivestock prices, on the other hand are expected to remain firm through the projectionperiod strengthening crop prices. In general the analysis points to the maintaining ofsupply-demand balances at the global level with relatively moderate increase in prices.These conditions in turn point to the need for achieving growth in the production of foodcommodities in the developing economies supported by productivity growth that is not ledmainly by price incentives.

In this report, we have presented an assessment of the medium-term prospects of supplyand demand conditions for the major food commodities along with factors influencingthese conditions. An analysis of production growth and variability in production at thestate level points to the significant differences in growth and variability and the trends ingrowth and variability. There are states with low average yields and also show relatively lowgrowth of yield. In such states, efforts could be focused on improvement of cultivationpractices, to catch up with higher yields in other states. The states with lower yields butalready showing higher rates of growth, would require measures to sustain growth whichalso reduce volatility in production. Finally the states where yield levels are high, wouldrequire measures that push the technology frontiers in terms of new varieties and adoptionof best practices. Supportive measures that reduce the adverse impact of market riskswould be needed in states where variability of production is large for any commodity.

The key findings of the growth-variability analysis are summarised in Tables V.1 and V.2.The findings point to the distribution of states into low yield and high yield with severalstates in each category, which suggests that there are substantial benefits from increasingthe yield levels in the low yield states and there are also states that have achieved highgrowth even when the yield levels are high. In other words adoption of best practices andimprovement in infrastructure can yield significant benefits across states. The low yieldgrowth and high yield combination of characteristics indicates the need for steps to removethe technology constraints on yields. The results also point to relatively higher level ofvariability in yields in both low yield and high yield states and low growth and high growth

CHAPTER V

Summary and Conclusions

67

Aided by theimproved globaleconomicconditions India’seconomic growthrate is nowexpected to be6.5-7 per centover the medium-term of 2014–15to 2020–21.

An analysis ofproductiongrowth andvariability inproduction at thestate level pointsto the significantdifferences ingrowth andvariability and thetrends in growthand variability.

states. Steps to reduce yield variability would improve incentives for more investments onthe farm and also in other marketing and distribution infrastructure.


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Table V.1: Yield Level, Growth and Variability Characteristics: CerealsCharacteristic Rice Wheat Maize Bajra Jowar

Low yield- Assam* UP* Bihar* Maharashtra*

low growth Bihar** Bihar** JK*

WB** Gujarat**

HP**

Karnataka**

UP**

Low yield- Chhattisgarh** Gujarat** Maharashtra** Karnataka** Karnataka**

high growth Gujarat** MP** Rajasthan** Maharashtra** Rajasthan**

MP** Maharashtra** Rajasthan** TN**

Maharashtra**

Orissa**

High yield- UP* Punjab* Gujarat* UP*

low growth WB* UP*

High yield- Haryana* Haryana** TN** Haryana** AP**

high growth Punjab* Rajasthan** AP** MP** MP**

Karnataka** Punjab**

TN** WB**

Note: * = Coefficient of variation is relatively low and ** = CV is high (based on the levels adopted in Chapter 4)

Table V.2: Yield Level, Growth and Variability Characteristics: Pulses, Oilseeds and Sugarcane Characteristic Gram Tur Groundnut Soybean Rapeseed/ Sugarcane

mustard

Low yield- Haryana** TN** AP** WB* Punjab*

low growth Karnataka** Karnataka** UP*

Rajasthan**

Low yield- Chhattisgarh** Chhattisgarh** Maharashtra** MP* Bihar*

high growth Gujarat** Odisha**

Maharashtra** AP**

Gujarat**

Karnataka**

Maharashtra**

Rajasthan**

High yield- MP* Bihar* Maharashtra* AP** UP* AP*

low growth UP* MP* TN* MP** Haryana** Gujarat*

AP** UP* Gujarat** TN*

WB* MP** Karnataka**

Haryana** Rajasthan**

Jharkhand*

High yield- Rajasthan** Gujarat* Haryana*

high growth Rajasthan* Maharashtra**

Note: * and ** as explained in note for Figure V.1; TN= Tamil Nadu, MP = Madhya Pradesh, AP = Andhra Pradesh, UP = Uttar Pradesh, WB = WestBengal

The global outlook for food commodities available from FAO/ OECD, USDA andFAPRI points to improvement in production but declining to moderate rising trend inworld prices. An important implication of the declining or moderately rising prices is theneed to sustain productivity growth at competitive prices of output. In other words,production growth would have to be led by more efficient use of resources. While there aresome differences in the extent of changes in the medium-term projections from the threeorganisations, the direction of changes are generally the same. For this reason, wesummarise the points that emerge from the projections from FAO/OECD for the majorcommodities below,

Global wheat production is forecast to increase by 12.5 per cent to 784.5 milliontonnes during 2013 to 2022. India’s contribution to the world output growth is 23.4million tonnes or 27 per cent of the total increase. Russia is projected to contribute 12million tonnes. Wheat production is US is projected to decline by 3 million tonneseach. Much of the increase in India’s wheat production is expected to come from areaexpansion.

Russia to emerge as the leading wheat exporter with exports of 21 million tonnes by2022. India is forecast to remain a net exporter of wheat of around 4 million tonnes,whereas China will remain a net importer.

India projected to contribute about 10 million tonnes to the increase in world’s riceproduction of around 55 million tonnes between 2013 and 2022. Rice production inThailand and Vietnam is forecast to increase by 3 million tonnes. Significant increasein production is forecast in Indonesia (6 million tonnes), Bangladesh (6 million tonnes)and African countries (10 million tonnes). Indian rice exports are forecast to declinesomewhat to 5.3 million tonnes, mostly basmati rice, indicating the growth of domesticconsumption.

India’s rice yield is projected to increase only marginally to 2.7 tonnes per hectare fromthe current 2.4 tonnes per hectare.

India’s coarse grain production is forecast to increase modestly to around 53 milliontonnes from the current 42 million tonnes, with most of the increase expected to comefrom maize. India’s production of coarse grains remains, however, much lower amongmajor producing countries such as the United States (371 million tonnes), China (257million tonnes), and Brazil (80 million tonnes). Indian exports are forecast at around 4million tonnes.

Per hectare yield of coarse gains in India is forecast to remain one of the lowest amongall major coarse grain producing countries at 1.7 tonnes/hectare compared with theUnited States (10.2 tonnes), China (6.6 tonnes), Argentina (5.9) and Brazil (4.6tonnes) and world (4 tonnes).

India’s vegetable oil production now at around 7.5 million tonnes is forecast to increasemodestly to 8.5 million tonnes by 2022 as global vegetable oil production increasesfrom 163 million tonnes to 196 million tonnes. Most of the increase in world vegetableoil production is forecast to be palm oil in Indonesia and Malaysia and soybean oil inArgentina and Malaysia.

India’s vegetable oil imports are forecast to reach over 14 million tonnes by 2022 fromthe current 11 million tonnes, emerging as the topmost importer of vegetable oilsreplacing China.

India will continue to remain an exporter of oil meals reaching 6 million tonnes by

SUMMARY AND CONCLUSIONS

69

An importantimplication of thedeclining ormoderately risingprices is the needto sustainproductivitygrowth atcompetitiveprices of output.In other words,productiongrowth wouldhave to be led bymore efficient useof resources.

Russia to emergeas the leadingwheat exporterwith exports of 21million tonnes by2022. India isforecast to remaina net exporter ofwheat of around 4million tonnes,whereas Chinawill remain a netimporter.

India projected tocontribute about10 million tonnesto the increase inworld’s riceproduction ofaround 55 milliontonnes between2013 and 2022.

2022, whereas China with record oil meal production will continue to remain a netimporter of 6 million tonnes of oil meal.

India’s share in global sugar production in 2022 is forecast at 15 per cent at around 32million tonnes. Brazil with a production of 48 million tonnes in 2022 will continue tobe the largest sugar producing country. Almost 50 per cent of sugarcane production inBrazil goes in the production of ethanol.

Global sugar trade is forecast at 63 million tonnes by 2022 with India remaining animporter of around 1 million tonne of sugar.

The medium-term assessment at the global level and India points to the increase inproduction and trade in the major commodities. While India’s share in increasedproduction is significant in grains, its share in growing trade volumes is not expected torise significantly. In other words, domestic markets will be the drivers of consumption anddemand for India’s food sector over the medium-term.

A comparison of these projections with those of OECD/ FAO shows that NCAERprojections of growth rates of production of rice, oilseeds and sugarcane are higher whereasthey are lower in the case of wheat and coarse grains. Although potential for improvementin yield levels remains high, as indicated by the large yield gaps between India’s averageyield levels with the yield levels in the major producing countries and across states withinthe country, the investments in productivity improvement would be justified only byadequate demand.

The update of our September 2013 medium-term projections, shows that the currentestimates of output growth rates are lower than the previous assessment in September2013 in the case of wheat, rice and oilseeds. The range of updated growth rates hasnarrowed in the case of coarse grains but with a decline in the average of the projectedrange. The projected growth rates based on trend analysis are also lower in the case ofsugarcane, potato and onion.

There projected demand scenario is broadly similar to the one presented in September2013, with some variations. The projected growth of domestic demand growth is lower inthe updated outlook in the case of wheat and coarse grains but remains unchanged in thecase of rice, partly reflecting the negative expenditure elasticity for these commodities. Inthe case of pulses, the updated demand growth rate is higher, which also reflects thepositive expenditure elasticity. In the case of other commodities, we have retained thegrowth rates of demand as in the September 2013 MTAOR.

The projections essentially reflect the differences in consumer demand preferences asincome levels rise. The changes in output composition in favour of non-cerealcommodities in domestic demand are projected to continue. The export demand isprojected at a slightly higher pace for cereals than estimated in the previous report.

Comparison of projected production and demand conditions point to the need formeasures to support growth in production and supplies in the case of wheat, coarse grains,onion and banana (or fruits more generally). Greater attention to development of marketswould be needed in the case of rice, potato and milk. In the case of sugar, the current paceof production matches the growth rate of demand and efforts to improve productivitywould result in scope for exports over the medium-term.


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The medium-term assessmentat the global leveland India points tothe increase inproduction andtrade in the majorcommodities.While India’sshare inincreasedproduction issignificant ingrains, its share ingrowing tradevolumes is notexpected to risesignificantly. Inother words,domestic marketswill be the driversof consumptionand demand forIndia’s food sectorover the medium-term.

The compound growth rate (CGR) of area, production and yield was calculated as follows:

Let yt denotes the observation (agricultural production, productivity, or area) at time t andlet r be the compound growth rate. Then,

yt = y0 (1 + r)t

Taking logarithms on both sides:

Iog (yt) = A + B*t

where, A = log (y0 ), and B = log ( 1 + r ).

Equation (2) is fitted to data using “method of least squares” and goodness of fit is assessedby the coefficient of determination R2. The compound growth rate r is estimated as:

r = antilog (B) - 1

To measure the variability in production, the Coefficient of Variation (CV) for production,area, and yield is used. The CV is computed using the formula:

CV = SD/AVG

Where SD is the Standard Deviation and AVG is the arithmetic mean derived from thedata.

To assess the relative contribution of yield and area to production is the Sackrin Methodas discussed below is used:

Pt = At * Yt

where Pt is production, At is the area and Yt is the yield in year t.

log Pt =log At + log Yt

(log Pt - log Pt-1) =( log At - log At-1 )+ (log Yt - log Yt-1)

Or

X1 = X2 + X3

where X1 = (log Pt - log Pt-1); X2 = ( log At - log At-1 ) and X3 = (log Yt - log Yt-1)

dX2/dX1 + dX3/dX1 = 1 where d denotes the differentiation.

Fitting linear regression equations:

X2 = c1 + d1 X1

X3 = c2+d2 X1

dX2/dX1 = d1 and dX3/dX1 = d2

APPENDIX I

Calculation of Growth, Variability andDecomposition of Growth of Production

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Coefficients d1and d2 measures change in area and yield respectively for a unit change inproduction. Furthermore, as d1+d2 = 1, d1 represents the relative contribution of area toproduction and d2 represents the relative contribution of yield.


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