Food Security

, Volume 11, Issue 1, pp 151–166 | Cite as

Processing technologies for undervalued grains in rural India: on target to help the poor?

  • Evan J. Miller-Tait
  • Sandeep MohapatraEmail author
  • M. K. (Marty) Luckert
  • Brent M. Swallow
Original Paper


Finger millet (ragi) is increasingly recognized as a nutritious staple by Indian consumers and policy makers. Though previously regarded as a poor person’s crop, the benefits of enhanced ragi consumption may bypass the poor. Because home processing is arduous, small flour mills have been introduced to help. With geo-referenced survey data from a pilot area in the Kolli Hills region of Tamil Nadu, India, we examined determinants of mill use and use intensity employing a two stage multinomial selection model. Overall, we found that the mill technology was not pro-poor, in that poor people do not tend to use the mills more than wealthier people, or use them at higher rates. We identified the location of mills as being a key factor in preventing more use of mills by the poor. Therefore, to better serve the poor, external agencies would have to deliberately locate mills in poor communities. For this to be feasible, changes to make this technology work better with poor communities may be required, such as the use of less capital intensive technology such as hand- or pedal-power, rather than reliance on electrical power.


Mill use India Nutrition Women Adoption Multiple-selection model 



We would like to thank Vic Adamowicz for his help in the sampling design of data collected for this study. We acknowledge important inputs into the implementation of the survey from the M.S. Swaminathan Research Foundation as well as financial support of the International Development Research Centre and Global Affairs Canada (formerly Department for Foreign Affairs, Trade and Development) through the Canadian International Food Security Research Fund (IDRC Project Number 106505-001). We thank the following individuals at MSSRF for their contributions to the overall study design and implementation of the surveys: Nita Selena, Oliver King, Siddick Abubacker, Kumar Natarajan, Bala Murugam, and P. Hariharasudhan. We also extend our appreciation to the anonymous reviewers and editors for their helpful comments.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Adesina, A. A., & Baidu-Forson, J. (1995). Farmers’ perception and adoption of new agricultural technology: Evidence from analysis in Burkina Faso and Guinea, West Africa. Agricultural Economics, 13, 1–9.CrossRefGoogle Scholar
  2. Altieri, M., & Koohafkan, P. (2008). Enduring Farms: Climate Change, Smallholders and Traditional Farming Communities. Penang, Malaysia: Third World Network. Retrieved 01 10, 2013, from
  3. Arslan, A., McCarthy, N., Lipper, L., Asfaw, S., & Cattaneo, A. (2013). Adoption and Intensity of Adoption of Conservation Farming Practices in Zambia. Lusaka, Zambia: Indaba agricultural policy research institute and the agricultural development economics division of the food and agriculture organization of the UN . Retrieved august 15, 2013, From
  4. Barungi, M., & Maonga, B. (2011). Adoption of soil management technologies by smallholder farmers in central and southern Malawi. Journal of Sustainable Development in Africa, 13(3), 28–38.Google Scholar
  5. Becker, G. S. (1973). A theory of marriage: Part I. Journal of Political Economy, 81(4), 813–846.CrossRefGoogle Scholar
  6. Bergamini, N., Padulosi, S., Ravi, S., & Yenagi, N. (2013). Case study 8 minor millets in India: A neglected crop goes mainstream. Diversifying Food and Diets: Using Agricultural Biodiversity to Improve. Nutrition and Health, 313.Google Scholar
  7. Borjas, G. J. (1987). Self-selection and the earnings of immigrants. American Economic Review, 77(4), 531–553.Google Scholar
  8. Bourguignon, F., Fournier, M., & Gurgand, M. (2007). Selection bias correction based on the multinomial logit model: Monte-Carlo comparisons. Journal of Economic Surveys, 211, 174–205.CrossRefGoogle Scholar
  9. Business Standard (2017). Raise minimum support price for pulses, says CACP. April 7. Accessed 31 Jan 2019.
  10. Chatterjee, C., & Sheoran, G. (2007). Vulnerable groups in India. In Mumbai: The Centre for Enquiry into health and allied themes. India: Mumbai.Google Scholar
  11. Diskin, P. (1994a). Understanding linkages among food availability, access, consumption, and nutrition in Africa: Empirical findings and issues from the literature. Washington, D.C.: Report to USAID/AFR/ARTS/FARA.Google Scholar
  12. Diskin, P. (1994b). Management of the Drought and Post-Drought Recovery in Zambia: The effectiveness of maize market reforms and direct government assistance in ensuring food security. Draft Mimeo. In East Lansing. Michigan: Michigan State University.Google Scholar
  13. Dubin, J. A., & McFadden, D. L. (1984). An econometric analysis of residential electric appliance holdings and consumption. Econometrica, 52, 345–362.CrossRefGoogle Scholar
  14. Feder, G. (1980). Farm size, risk aversion and the adoption of new technology under uncertainty. Oxford Economic Papers, 32(2), 263–283.CrossRefGoogle Scholar
  15. Feder, G., & O'Mara, G. T. (1981). Farm size and the diffusion of green revolution technology. Economic Development and cultural change, 30(1), 59–76.Google Scholar
  16. Finnis, E. (2009). “Now it is an easy life”: women’s accounts of cassava, millets, and labor in South India. Culture and Agriculture, 31(2), 88–94.CrossRefGoogle Scholar
  17. Glewwe, P., & van der Gaag, J. (1990). Identifying the poor in developing countries: Do different definitions matter? World Development, 18(6), 803–814.CrossRefGoogle Scholar
  18. Goodhue, R., Klonsky, K., & Mohapatra, S. (2010). Can an education program be a substitute for a regulatory [rogram that bans pesticides? Evidence from a panel selection model. American Journal of Agricultural Economics, 92(4), 956–971.Google Scholar
  19. Google Inc. (2012). Google Earth (Version 6.2) . Available from
  20. Greene, W. (2007). LIMDEP version 9.0/NLOGIT version 4.0 Econometric Modelling Guide. Plainview, New York: Econometric Software.Google Scholar
  21. Heckman, J. (1979). Sample selection bias as a specification error. Econometrica, 47, 153–161.CrossRefGoogle Scholar
  22. Holloway, G., Shankar, B., & Rahman, S. (2002). Bayesian spatial Probit estimation: A primer and an application to HYV rice adoption. Agricultural Economics, 27(3), 383–402.CrossRefGoogle Scholar
  23. Huang, T., Farmer, A. P., Goddard, E., Willows, N., & Subhan, F. (2017). An ethnographic exploration of perceptions of changes in dietary variety in the Kolli Hills, India. Food Security, 9(4), 759–771.CrossRefGoogle Scholar
  24. Jayne, T., Tschirley, D., Staatz, J., Shaffer, J., Weber, M., & Chisvo, M. (1995). Market-Oriented Strategies to Improve Household Access to Food: Experience from Sub-Saharan Africa. MSU International Development Paper no. 15.Google Scholar
  25. Jukanti, A. K., Gowda, C. L. L., Rai, K. N., Manga, V. K., & Bhatt, R. K. (2016). Crops that feed the world 11. Pearl millet (Pennisetum glaucum L.): An important source of food security, nutrition and health in the arid and semi-arid tropics. Food Security, 8(2), 307–329.CrossRefGoogle Scholar
  26. Just, R., & Zilberman, D. (1983). Stochastic structure, farm size and technology adoption in developing agriculture. Oxford Economic Papers, 35(2), 307–328.CrossRefGoogle Scholar
  27. Katchova, A. L., & Miranda, M. J. (2004). Two-step econometric estimation of farm characteristics affecting marketing contract decisions. American Journal of Agricultural Economics, 86(1), 88–102.Google Scholar
  28. Kumar, P., Kumar, A., Parappurathu, S., & Raju, S. S. (2011). Estimation of demand elasticitiy for food commodities in India. Agricultural Economics Research Review, 24, 1–14.Google Scholar
  29. Lee, L. (1983). Generalized econometric models with selectivity. Econometrica, 51, 507–512.CrossRefGoogle Scholar
  30. Mal, B., Padulosi, S., & Ravi, S. B. (2010). Minor millets in South Asia: learnings from IFAD-NUS Project in India and Nepal. Bioversity International, Maccarese, Rome, Italy and the MS Swaminathan Research Foundation, Chennai, India, 185.Google Scholar
  31. McFadden, D. (1973). Conditional logit analysis of qualitative choice behavior. In P. Zarembka (Ed.), Frontiers in econometrics. New York: Academic Press.Google Scholar
  32. National Research Council. (1996). Finger Millet. In Lost Crops of Africa: Volume 1: Grains (pp. 39–57). National Academy of Sciences.Google Scholar
  33. Padulosi, S., Mal, B., Bala Ravi, S., Gowda, J., Gowda, K. T. K., Shanthakumar, G., Yenagi, N., & Dutta, M. (2009). Food security and climate change: role of plant genetic resources of minor millets. Indian Journal of Plant Genetic Resources, 22(1), 1.Google Scholar
  34. Padulosi, S., Amaya, K., Jäger, M., Gotor, E., Rojas, W., & Valdivia, R. (2014). A holistic approach to enhance the use of neglected and underutilized species: the case of Andean grains in Bolivia and Peru. Sustainability, 6(3), 1283–1312.Google Scholar
  35. Padulosi, S., Mal, B., King, O. I., & Gotor, E. (2015). Minor millets as a central element for sustainably enhanced incomes, empowerment, and nutrition in rural India. Sustainability, 7(7), 8904–8933.Google Scholar
  36. Palaniswamy, S. (2018). Development of a millet dehuller (hand-operated) to reduce drudgery in processing and utilization of millet waste (hulls) in antioxidant extraction. MSc thesis, McGill University.Google Scholar
  37. Parmanand, A. V. (2015). Development and testing of pedal operated thresher for finger millet. International Journal of Agricultural Science and Research (IJASR), 5(3), 299–307.Google Scholar
  38. Raghu, P., Swallow, B., Manaloor, V., Kalaiselvan, N., Mahana, R., Arunraj, R., et al. (2013). Alleviating Poverty and Malnutrition in Agro-biodiversity Hotspots: Baseline Report. University of Alberta / M.S. Swaminathan Research Foundation.Google Scholar
  39. Rosegrant, M., & Hazell, P. (2000). Transforming the Rural Asian Economy: the Unfinished Revolution. Asian Development Bank, Manila, the Philippines.Google Scholar
  40. Rubey, L. (1993a). Consumer Maize Meal Preferences in Zimbabwe. USAID Report. Harare, Zimbabwe.Google Scholar
  41. Rubey, L. (1993b). Yellow Maize, Consumer Preferences and Food Security in Zimbabwe. Report to USAID/Zimbabwe, Harare, Zimbabwe.Google Scholar
  42. Seetharam, A., Riley, K., & Harinarayana, G. (Eds.). (1989). Small millets in global agriculture. Proceedings of the First International Small Millets Workshop Bangalore, India. New Delhi, India: IDRC / IBH Publishing Co.Google Scholar
  43. Shobana, S., Krishnaswamy, K., Sudha, V., Malleshi, N. G., Anjana, R. M., Palaniappan, L., & Mohan, V. (2013). Finger millet (Ragi, Eleusine coracana L.): a review of its nutritional properties, processing, and plausible health benefits. In Advances in food and nutrition research (Vol. 69, pp. 1–39). Academic Press.Google Scholar
  44. Singh, P., & Raghuvanshi, R. (2012). Finger millet for food and nutritional security. African Journal of Food Science, 6(4), 77–84.Google Scholar
  45. Singh, K. P., Poddar, R. R., Agrawal, K. N., Hota, S., & Singh, M. K. (2015). Development and evaluation of multi-millet thresher. Journal of Applied and Natural Science, 7(2), 939–948.CrossRefGoogle Scholar
  46. Sonalde, D., Dubey, A., Joshi, B., Sen, M., Sheriff, A., & Vanneman, R. (2008). India human development survey. College Park, MD: University of Maryland.Google Scholar
  47. Staal, S., Baltenwick, I., Waithaka, M., deWolff, T., & Njoroge, L. (2002). Location and uptake: Integrated household and GIS analysis of technology adoption and land use, with application to smallholder dairy farms in Kenya. Agricultural Economics, 27(3), 295–315.CrossRefGoogle Scholar
  48. Stifel, D., & Minten, B. (2008). Isolation and agricultural productivity. Agricultural Economics, 39(1), 1–15.Google Scholar
  49. Sunding, D., & Zilberman, D. (2001). The agricultural innovation process: Research and technology adoption in a changing agricultural sector. In B. Gardner & G. Rausser (Eds.), Handbook of Agricultural Economics (Vol. I, pp. 207–261) Elsevier Science B.V.Google Scholar
  50. Vijaya Bhaskar, A. V., Nithya, D. J., Raju, S., & Bhavani, R. V. (2017). Establishing integrated agriculture-nutrition programmes to diversify household food and diets in rural India. Food Security, 9(5), 981–999.CrossRefGoogle Scholar

Copyright information

© International Society for Plant Pathology and Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Resource Economics and Environmental SociologyUniversity of AlbertaEdmontonCanada
  2. 2.Department of Agriculture and ForestryEdmontonCanada

Personalised recommendations