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Pattern of crop diversification and its implications on undernutrition in India


Affiliations
1 ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
 

The present study explores the pattern and extent of food-crop diversification and its implications on nutritional indicators in India using district-level data for the most recent period. It relied on data from land-use statistics and the National Family Health Survey 2015–16. We estimated the Simpson index for food-crop diversification and undernutrition index for nutritio­nal status. The association of crop diversification and nutritional status was analysed employing bivariate copula function. The findings show striking regional differences in the extent of food-crop diversification and nutritional outcomes. The results of the copula function indicate a significant inverse relationship between crop diversification and undernutrition

Keywords

Bivariate copula, crop diversification, land use, nutritional status, undernutrition index.
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  • GoI, State of Indian agriculture. Ministry of Agriculture and Farmer’s Welfare, Government of India, 2016; http://agricoop.nic.in/otherreports/state-indian-agriculture-2017

  • Chand, R., Doubling farmers’ income: rationale, strategy, prospects and action plan. Policy Paper No. 1, NITI Aayog, GoI, 2017; https://niti.gov.in/writereaddata/files/document_publication/DOUBLING%20FARMERS%20INCOME.pdf

  • GoI, The Economic Survey 2017–18, Ministry of Finance, Government of India, 2018; http://mofapp.nic.in:8080/economicsurvey/

  • UN, #Envision2030 Goal 2: Zero Hunger, United Nations, New York, USA, 2015; https://www.un.org/development/desa/disabilities/envision2030-goal2.html

  • NITI Aayog, The SDG India Index 2019–20, GoI, 2019; https:// niti.gov.in/sdg-india-index-dashboard-2019-20

  • International Institute for Population Sciences (IIPS) and ICF, National Family Health Survey (NFHS-4), 2015–16, IIPS, Mumbai, 2017; http://rchiips.org/nfhs/NFHS-4Report.shtml

  • Radhakrishna, R. and Panda, M., Macroeconomics of poverty reduction: India case study, Indira Gandhi Institute of Development Research, Mumbai, 2006; http://oii.igidr.ac.in:8080/xmlui/handle/ 2275/180

  • Bobojonov, I. et al., Crop diversification in support of sustainable agriculture in Khorezm. In Cotton, Water, Salts and Soums Economic and Ecological Restructuring in Khorezm, Uzbekistan (eds Martius, C. et al.), Springer, Dordrecht, The Netherlands, 2012, pp. 219–233; https://link.springer.com/chapter/10.1007/978-94-0071963-7_14

  • Pingali, P. L. and Rosegrant, M. W., Agricultural commercialization and diversification: processes and policies. Food Policy, 1995, 20(3), 644–651; https://doi.org/10.1016/0306-9192(95)00012-4

  • Guvele, C. A., Gains from crop diversification in the Sudan Gezira scheme. Agric. Syst., 2001, 70, 319–333; https://doi.org/10.1016/ S0308-521X(01)00030-0.

  • Ryan, J. G. and Spencer, D. C., Future challenges and opportunities for agricultural R&D in the semi-arid tropics. International Crops Research Institute for the Semi-Arid Tropics, Patancheru, 2001; http://www.icrisat.org/PDF/Outlook%20rep%20Future%20Challenges%20in%20SAT-594.pdf

  • Joshi, P. K., Tewari, L. and Birthal, P. S., Diversification and its impact on smallholders: evidence from a study on vegetable production. Agric. Econ. Res. Rev., 2006, 19(2), 219–236; https://ageconsearch.umn.edu/record/57759.

  • Van den Berg, M. M., Hengsdijk, H., Wolf, J., Ittersum, M. K. V., Guanghuo, W., and Roetter, R. P., The impact of increasing farm size and mechanization on rural income and rice production in Zhejiang province, China. Agric. Syst., 2007, 94, 841–850; https://doi.org/10.1016/j.agsy.2006.11.010.

  • Kahan, D., Managing risk in farming. In Farm Management Extension Guide 3, Food and Agriculture Organization of the United Nations, Rome, Italy, 2008, pp. 29–87; 3-ManagingRiskInternLores.pdf (fao.org)

  • Sharma, H. R., Crop diversification in Himachal Pradesh; patterns, determinants and challenges. Indian J. Agric. Econ., 2011, 66(1), 97–114; https://ageconsearch.umn.edu/record/204738/files/11H.%20R%20Sharma.pdf

  • Feliciano, D., A review on the contribution of crop diversification to Sustainable Development Goal 1 ‘No poverty’ in different world regions. Sustain. Dev., 2019, 27(4), 795–808; https://doi.org/ 10.1002/sd.1923.

  • Anuja, A. R., Anjani Kumar, Saroj, S. and Singh, K. N., The impact of crop diversification towards high-value crops on economic welfare of agricultural households in eastern India. Curr. Sci., 2020, 118(10), 1575–1582; https://doi.org/10.18520/cs/v118/i10/ 1575-1582.

  • Pandey, S., Bhandari, H., Ding, S., Prapertchob, P., Sharan, R., Naik, D. and Taunk, S. K., Coping with drought in rice farming in Asia: insights from a cross-country comparative study. Agric. Econ., 2007, 37, 213–224; doi:10.1111/j.1574-0862.2007.00246.x

  • Lin, B. B., Resilience in agriculture through crop diversification: adaptive management for environmental change. BioScience, 2011, 61(3), 183–193; https://academic.oup.com/bioscience/article/ 61/3/183/238071

  • Barghouti, S., Kane, S., Sorby, K. and Ali, M., Agricultural diversification for the door: Guidelines for practitioners. Agriculture and Rural Development Discussion Paper 1. World Bank, Washington DC, USA, 2004; https://agris.fao.org/agris-search/search.do?recordID=GB2013203761

  • Birthal, P. S., Roy, D. and Negi, D. S., Assessing the impact of crop diversification on farm poverty in India. World Dev., 2015, 72, 70–92; https://doi.org/10.1016/j.worlddev.2015.02.015

  • Thapa, G., Kumar, A. and Joshi, P. K., Agricultural diversification in Nepal: status, determinants, and its impact on rural poverty. Discussion Paper No. 01634, International Food Policy Research Institute (IFPRI) – South Asia Office, New Delhi, 2017; https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2972291

  • McCord, P. F., Cox, M., Schmitt-Harsh, M. and Evans, T., Crop diversification as a small holder livelihood strategy within semiarid agricultural systems near Mount Kenya. Land Use Policy, 2015, 42, 738–750; https://doi.org/10.1016/j.landusepol.2014.10.012.

  • Jones, A. D., Shrivinas, A. and Bezner‐Kerr, R., Farm production diversity is associated with greater household dietary diversity in Malawi: findings from nationally representative data. Food Policy, 2014, 46, 1–12; https://doi.org/10.1016/j.foodpol.2014.02.001

  • Njeru, E. M., Crop diversification: a potential strategy to mitigate food insecurity by smallholders in sub-Saharan Africa. J. Agric. Food Syst. Community Dev., 2013, 3(4), 63–69; https://doi.org/10.5304/jafscd.2013.034.006.

  • Davis, K. F. et al., Assessing the sustainability of post-Green Revolution cereals in India. Proc. Natl. Acad. Sci. USA, 2019, 116(50), 25034–25041; doi:10.1073/pnas.1910935116.

  • Ecker, O., Mabiso, A., Kennedy, A. and Diao, X., Making agriculture pro-nutrition: opportunities in Tanzania. IFPRI Discussion Papers, 1124, International Food Policy Research Institute, Washington DC, 2011; https://www.ifpri.org/publication/making-agriculture-pro-nutrition

  • Makate, C., Wang, R., Makate, M. and Mango, N., Crop diversification and livelihoods of smallholder farmers in Zimbabwe: adaptive management for environmental change. SpringerPlus, 2016, 5(1), 1135; https://springerplus.springeropen.com/articles/10.1186/ s40064-016-2802-4

  • Census, Provisional Population Totals Paper 1 of 2011 (India & States/UTs). 2011; https://censusindia.gov.in/2011-prov-results/ census2011_ppt_paper1.html

  • Gulati, A., Ganesh Kumar, A., Shreedhar, G. and Nandakumar, T., Agriculture and malnutrition in India. Food Nutr. Bull., 2012, 33(1), 74–86; https://journals.sagepub.com/doi/pdf/10.1177/156482651203300108

  • Li, D., Zhang, L., Tang, X., Zhou, W., Li, J., Zhou, C. and Phoon, K., Bivariate distribution of shear strength parameters using copulas and its impact on geotechnical system reliability. Comput. Geotech., 2015, 68, 184–195; https://doi.org/10.1016/j.compgeo.2015.04.002.

  • Fan, L. and Qian, Z., Probabilistic modelling of flood events using the entropy copula. Adv. Water Resour., 2016, 97, 233–240; https://doi.org/10.1016/j.advwatres.2016.09.016.

  • Mazdiyasni, O. et al., Increasing probability of mortality during Indian heat waves. Sci. Adv., 2017, 3, 1–5; doi:10.1126/sciadv.1700066.

  • Nguyen-Huy, T., Deo, R. C., An-Vo, D., Mushtaq, S. and Khan, S., Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones. Agric. Water Manage, 2017, 191, 153–172;

  • https://doi.org/10.1016/j.agwat.2017.06.010.

  • Gill, S., Water crisis in Punjab and Haryana. Econ. Polit. Wkly, 2016, 51(50), 37–41; https://www.epw.in/journal/2016/50/insight/water-crisis-punjab-and-haryana.html

  • Ghuman, R. S. and Sharma, R., Green revolution, cropping pattern and water scarcity in India: evidence from Punjab. Man Dev., 2016, XXXVIII(2), 1–20; http://esaharyana.gov.in/Portals/0/agriculture.pdf

  • Harzana, J., Birtal, P. S., Negi, D. S., Mani, G. and Pandey, G., Spatial spill-overs, structural transformation and economic growth in India. Agric. Econ. Res. Rev., 2019, 32(2), 145–158; https://10.5958/0974-0279.2019.00028.4.

  • Meera, S., Nutrition and agriculture: bridging the gap, 2015; https://blogs.worldbank.org/health/nutritionandagriculturebridginggap#:~:text=Physical%20and%20economic%20access%20to,costs-%20which%20can%20lower%20food

  • Chinnadurai, M., Karunakaran, K. R., Chandrasekaran, R., Balasubramanian, R. and Umanath, M., Examining linkage between dietary pattern and crop diversification: an evidence from Tamil Nadu. Agric. Econ. Res. Rev., 2016, 29, 149–160; doi:10.5958/0974-0279.2016.00042.2.

  • Mango, N., Makate, C., Mapemba, L. and Sopo, M., The role of crop diversification in improving household food security in central Malawi. Agric. Food Policy, 2018, 7, 7; https://doi.org/10.1186/s40066-018-0160-x.

  • Adjimoti, G. O. and Kwadzo, G. T., Crop diversification and household food security status: evidence from rural Benin. Agric. Food Secur., 2018, 7, 82; https://doi.org/10.1186/s40066-018-0233-x.

  • Johns, T. and Sthapit, B. R., Biocultural diversity in the sustainability of developing-country food systems. Food Nutr. Bull., 2004, 25(2), 143–155; https://doi.org/10.1177/156482650402500207.

  • Mofya-Mukuka, R. and Kuhlgatz, C. H., Child malnutrition, agricultural diversification and commercialization among smallholders in Eastern Zambia. Working Paper No. 90, Indaba Agricultural Policy Research Institute, Lusaka, Zambia, 2015; https://ageconsearch.umn.edu/record/198189/files/wp90_rev.pdf


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  • Pattern of crop diversification and its implications on undernutrition in India

Abstract Views: 320  |  PDF Views: 139

Authors

A. R. Anuja
ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
G. P. Shivaswamy
ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
Mrinmoy Ray
ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
K. N. Singh
ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India

Abstract


The present study explores the pattern and extent of food-crop diversification and its implications on nutritional indicators in India using district-level data for the most recent period. It relied on data from land-use statistics and the National Family Health Survey 2015–16. We estimated the Simpson index for food-crop diversification and undernutrition index for nutritio­nal status. The association of crop diversification and nutritional status was analysed employing bivariate copula function. The findings show striking regional differences in the extent of food-crop diversification and nutritional outcomes. The results of the copula function indicate a significant inverse relationship between crop diversification and undernutrition

Keywords


Bivariate copula, crop diversification, land use, nutritional status, undernutrition index.

References





DOI: https://doi.org/10.18520/cs%2Fv122%2Fi10%2F1154-1160