Skip to main navigation menu Skip to main content Skip to site footer

Research Articles

Vol. 13 No. sp1 (2026): Recent Advances in Agriculture

Crop diversification for resilient farming: Determinants, challenges and policy implications for smallholder agriculture

DOI
https://doi.org/10.14719/pst.12104
Submitted
4 October 2025
Published
07-01-2026

Abstract

Crop diversification is a critical approach to minimizing risks from climatic variability, income instability and nutrition insecurity in cereal-based systems. In Odisha, overdependence on paddy, fragmented landholdings, inadequate irrigation and frequent climatic shocks render diversification indispensable for sustainable agriculture. The current research explores the factors influencing farmers' willingness to adopt crop diversification and identifies the major constraints hindering its spread in Odisha. A multi-stage sampling design was used to select 220 farm households from districts representing contrasting levels of cropping intensity. Data covering the period 2021–2024 were collected through structured surveys and secondary sources. The analysis employed Principal Component Analysis (PCA) to derive key socio-economic dimensions, Probit regression (PR) to estimate the adoption probability and the Garrett ranking to rank the constraints. Five major dimensions - land and income capital, demographic experience, market and institutional access, labour and finance and household labour reserve - were extracted through PCA, explaining a cumulative variance of 77.86 % . Probit regression revealed that land ownership, farm income and extension visits significantly increased the probability of diversification, whereas age, paddy yield, market access and credit access decreased the probability. Garrett ranking identified the most important hurdles as lacking market intelligence (rank I; score 66.05), excessive transportation costs (rank II; 60.76) and expensive labour (rank III; 55.08), followed by pest occurrence (rank IV; 53.12), malpractices by middlemen (rank V; 49.60) and poor irrigation (rank VII; 44.58). The results confirm that resource endowments (owned land and farm income), institutional support (extension services) and infrastructural development (market access and transport costs) strongly influence crop diversification. The study illustrates the need for targeted interventions, including improved market intelligence, accessible credit, decentralized infrastructure and the promotion of climate-resilient crops, to advance diversification, enhance farmer incomes and strengthen food and nutrition security, in alignment with the Sustainable Development Goals.

References

  1. 1. Nayak CR, Kumar CR. Crop diversification in Odisha: an analysis based on panel data. Agric Econ Res Rev. 2019;32:67-80. https://doi.org/10.5958/0974-0279.2019.00006.5
  2. 2. Barman A, Saha P, Patel S, Bera A. Crop Diversification an Effective Strategy for Sustainable Agriculture Development. Sustainable Crop Production - Recent Advances. IntechOpen; 2022. https://doi.org/10.5772/intechopen.102635
  3. 3. Shibani G, Mehta G, Samriti. Determinants of crop diversification: a case study of farm households in Himachal Pradesh. Indian J Econ Dev. 2023;19(4):847-54. https://doi.org/10.35716/IJED-23326
  4. 4. Anuja AR, Shivaswamy GP, Ray M, Singh KN. Pattern of crop diversification and its implications on undernutrition in India. Curr Sci. 2022;122(10):1154-60. https://doi.org/10.18520/cs/v122/i10/1154-1160
  5. 5. Pattanaik S, Sarangi K, Mishra SN, Dash A, Priyadarshini A. A study on prevalence of predominant integrated farming systems in coastal Odisha. Biol Forum Int J. 2022;14(4a):729-32.
  6. 6. International Panel of Experts on Sustainable Food Systems (IPES-Food). From uniformity to diversity: a paradigm shift from industrial agriculture to diversified agroecological systems. 2016.
  7. 7. United Nations. Transforming our world: the 2030 agenda for sustainable development. New York: UN; 2015.
  8. 8. Food and Agriculture Organization. The state of food and agriculture: moving forward on food loss and waste reduction. Rome: FAO; 2019.
  9. 9. Singh T, Satapathy BS. Intensification of pulses and oilseeds in rice fallows. Indian Farming. 2019;69(10):31-4.
  10. 10. Pasupalak S, et al. Strategies for pulse production in rice fallows of Odisha. Bhubaneswar: Orissa University of Agriculture and Technology; 2016.
  11. 11. Abraham M, Pingali P. Shortage of pulses in India: understanding how markets incentivize supply response. J Agribus Dev Emerg Econ. 2021;11:411-34. https://doi.org/10.1108/JADEE-11-2017-0128
  12. 12. Pattanaik S, Priyadarshini A. Millets: super food for nutrition security and livelihood improvement. In: Pradhan J, Sahoo JP, Samal KC, Dash M, editors. Millets and other potential crops: ensuring climate resilience & nutritional security. London: CRC Press, Taylor & Francis; 2024. p. 11-22. https://doi.org/10.1201/9781003531937-2
  13. 13. Neogi S, Ghosh BK. Evaluation of crop diversification on Indian farming practices: a panel regression approach. 2022;14(24):1-18. https://doi.org/10.3390/su142416861
  14. 14. Paroda R. Crop diversification for sustainable agriculture. Ecol Econ Soc. 2022;5(1):15-21. https://doi.org/10.37773/ees.v5i1.611
  15. 15. Nayak CR. Crop diversification and land productivity in Odisha: role of rural infrastructure. Pragati J Indian Econ. 2015;2(2):1-18. https://doi.org/10.17492/pragati.v2i2.8613
  16. 16. Nayak CR, Kumar CR. Crop diversification in Odisha: an empirical assessment. In: Swain M, Nayak CR, editors. Agrarian distress and farmer's suicide in India. New Delhi: S.K. Book Agency; 2018. p. 164-78.
  17. 17. Organisation for Economic Co-operation and Development (OECD). Table A.6.2 - Rice projections: consumption, per capita. OECD-FAO Agricultural Outlook 2015. Paris: OECD Publishing; 2015.
  18. 18. QGIS Development Team. QGIS Geographic Information System. Version 3.44 "Solothurn". QGIS Association; 2025.
  19. 19. Gopinath K, et al. grapesAgri1: collection of Shiny apps for data analysis in agriculture. J Open Source Softw. 2021;6(63):3437. https://doi.org/10.21105/joss.03437
  20. 20. Garrett HE, Woodworth RS. Statistics in psychology and education. Bombay: Vakils, Feffer and Simons; 1969. p. 329.
  21. 21. Mahajan G. Crop diversification: an empirical analysis of Kangra farm of Himachal Pradesh. Agric Econ Rev. 2004;17:199-217.
  22. 22. Mohanty AK, Lepcha B, Kumar A. Constraints analysis in adoption of vegetable production technologies for livelihood perspective of tribal farmers in North Sikkim. Indian Res J Ext Educ. 2013;13(2):51-6.
  23. 23. Singh R, Dogra A, Sarker A, Saxena A, Singh B. Technology gap, constraint analysis and improved production technologies for yield enhancement of barley (Hordeum vulgare) and chickpea (Cicer arietinum) under arid conditions of Rajasthan. Indian J Agric Sci. 2018;88(2):109-15. https://doi.org/10.56093/ijas.v88i2.79207
  24. 24. Aribi F, Sghaier M. Determinants and strategies of farmers' adaptation to climate change: the case of Medenine Governorate, Tunisia. Agrofor Int J. 2020;5:122-9. https://doi.org/10.7251/AGRENG2002124A
  25. 25. Mazzocchi C, Orsi L, Ferrazzi G, Corsi S. The dimensions of agricultural diversification: a spatial analysis of Italian municipalities. Rural Sociol. 2020;85:316-45. https://doi.org/10.1111/ruso.12291
  26. 26. Dembele B, Bett HK, Kariuki IM, LeBars M, Ouko KO. Factors influencing crop diversification strategies among smallholder farmers in cotton production zone in Mali. Adv Agric Sci. 2018;6:1-16.
  27. 27. Anuja AR, Kumar A, Saroj S, Singh KN. The impact of crop diversification towards high-value crops on economic welfare of agricultural households in Eastern India. Curr Sci. 2020;118:1575-82. https://doi.org/10.18520/cs/v118/i10/1575-1582
  28. 28. Cramer JS. Logit models from economics and other fields. Cambridge: Cambridge University Press; 2003. https://doi.org/10.1017/CBO9780511615412
  29. 29. Hosmer DW, Lemeshow S. Applied logistic regression. New York: John Wiley & Sons; 2000. https://doi.org/10.1002/0471722146
  30. 30. Hoo ZH, Candlish J, Teare D. What is an ROC curve? Emerg Med J. 2017;34:357-9. https://doi.org/10.1136/emermed-2017-206735
  31. 31. Wojewodzic T, Jezowit-Jurek M, Rachwał P. Remuneration for labour on agricultural commodity farms in the Małopolska and Pogórze macroregion. Problemy Drobnych Gospodarstw Rolnych. 2015;73-87. https://doi.org/10.15576/PDGR/2015.1.73
  32. 32. George GP, Sharma HO. Determinants of crop diversification in Kerala: a temporal analysis. J Trop Agric. 2020;58:99-106.
  33. 33. Bansal H, Sharma S, Kumar R, Singh A. The factors influencing and various technological and socio-economic constraints for crop diversification in Haryana. Econ Aff. 2020;65:409-13. https://doi.org/10.46852/0424-2513.3.2020.13
  34. 34. Rehima M, Belay K, Dawit A, Rashid S. Factors affecting farmers' crops diversification: evidence from SNNPR, Ethiopia. Int J Agric Sci. 2013;3:558-65.
  35. 35. Makate C, Wang R, Makate M, Mango N. Crop diversification and livelihoods of smallholder farmers in Zimbabwe: adaptive management for environmental change. Springerplus. 2016;5(1):1135. https://doi.org/10.1186/s40064-016-2802-4
  36. 36. Mithiya D, Mandal K, Datta L. Trend, pattern and determinants of crop diversification of smallholders in West Bengal: a district-wise panel data analysis. J Dev Agric Econ. 2018;10(4):110-21. https://doi.org/10.5897/JDAE2018.0921
  37. 37. Nayak DK. Changing cropping pattern, agricultural diversification and productivity in Odisha: a district-wise study. Agric Econ Res Rev. 2016;29(1):93-104. https://doi.org/10.5958/0974-0279.2016.00022.7
  38. 38. Kumar CR. Crop diversification and its determinants: a comparative study between Cuttack and Kandhamal districts of Odisha, India. J Glob Resour. 2020;6. https://doi.org/10.46587/JGR.2020.v06i02.007
  39. 39. Mulwa CK, Visser M. Farm diversification as an adaptation strategy to climatic shocks and implications for food security in northern Namibia. World Dev. 2020;129:104906. https://doi.org/10.1016/j.worlddev.2020.104906
  40. 40. Dries L, Pascucci S, Gardebroek C. Diversification in Italian farm systems: are farmers using interlinked strategies? New Medit. 2012;4:7-15.

Downloads

Download data is not yet available.