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SMALLHOLDER FARMERS’ PERCEPTIONS OF DROUGHT RISK AND ADOPTION OF MODERN MAIZE IN SOUTHERN MALAWI

Published online by Cambridge University Press:  03 March 2014

MONICA FISHER*
Affiliation:
International Maize and Wheat Improvement Center – Ethiopia Office, c/o ILRI Sholla Campus, P.O. Box 5689, Addis Ababa, Ethiopia
SIEGLINDE SNAPP
Affiliation:
W. K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI 49060, USA
*
Corresponding author. Email: [email protected]

Summary

Modern maize varieties have been bred for drought tolerance and early maturity, to assist farmers in avoiding or escaping the effects of moisture stress in drought-prone areas. This study evaluates the prospects for widespread adoption of these modern maize varieties as a climate change adaptation strategy for smallholder farmers. Data are from a detailed household survey completed in four rural villages in Southern Malawi between May and July 2010. The empirical analysis involves estimation of an ordered logit regression model because the dependent variable is categorical, with one category for nonadoption (has never grown modern maize varieties) and three categories for the duration of growing a modern maize variety among adopters (this year only, 2 to 5 years and 6 years or more). The empirical findings indicate a positive association between a farmer's perception of drought risk and the adoption and continued use of modern maize. Regression results also show that farmers that value the traits of early maturity and drought tolerance are more likely to adopt modern maize varieties. There is evidence of some disadoption among farmers dissatisfied with maize genotype performance, in terms of poor storability and yield under drought conditions. Finally, the study highlights the urgent need for maize breeders interested in sustained use of modern varieties to simultaneously address robust drought tolerance, early maturity and storability. This underscores the importance of cognizance of local farmer preferences in crop breeding efforts.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2014 

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References

REFERENCES

Adesina, A. A. and Baidu-Forson, J. (1995). Farmers’ perceptions and adoption of new agricultural technology: evidence from analysis in Burkina Faso and Guinea, West Africa. Agricultural Economics 13:19.Google Scholar
Asfaw, A., Almekinders, C. J. M., Blair, M. W. and Struik, P. C. (2012). Participatory approach in common bean (Phaseolus vulgaris L.) breeding for drought tolerance for southern Ethiopia. Plant Breeding 131 (1):125134.CrossRefGoogle Scholar
Barham, B. L., Foltz, J. D., Jackson-Smith, D. and Moon, S. (2004). The dynamics of agricultural biotechnology adoption: lessons from rBST use in Wisconsin, 1994–2001. American Journal of Agricultural Economics 86:6172.Google Scholar
Cameron, A. C. and Trivedi, P. K. (2009). Microeconometrics using Stata. College Station, Texas: StataCorp LP.Google Scholar
Croppenstedt, A., Demeke, M. and Meschi, M. M. (2003). Technology adoption in the presence of constraints: the case of fertilizer demand in Ethiopia. World Development 7:58–70.Google Scholar
Denning, G., Kabambe, P., Sanchez, P., Malik, A., Flor, R., Harawa, R., Nkhoma, P., Zamba, C., Banda, C., Magombo, C., Keating, M., Wangila, J. and Sachs, J. (2009). Input subsidies to improve smallholder maize productivity in Malawi: toward an African green revolution. Plos Biology 7 (1):00020010.Google Scholar
Doss, C. R. (2006). Analyzing technology adoption using microstudies: limitations, challenges, and opportunities for improvement. Agricultural Economics 34:207219.Google Scholar
Evenson, R. E. and Gollin, D. (Eds.). (2003). Crop Variety Improvement and Its Effects on Productivity. Wallingford, England: CABI.Google Scholar
Feder, G., Just, R. E. and Zilberman, D. (1985). Adoption of agricultural innovations in developing countries: a survey. Economic Development and Cultural Change 33:255297.Google Scholar
Foster, A. D. and Rosenzweig, M. R. (2010). Microeconomics of technology adoption. Center Discussion Paper No. 984, Economic Growth Center, Yale University.CrossRefGoogle Scholar
Foster, A. D. and Rosenzweig, M. R. (1995). Learning by doing and learning from others: human capital and technical change in agriculture. Journal of Political Economy 103:11761209.Google Scholar
Funk, C., Dettinger, M. D., Michaelsen, J. C., Verdin, J. P., Brown, M. E., Barlow, M. and Hoell, A. (2008). Warming of the Indian Ocean threatens eastern and southern African food security but could be mitigated by agricultural development. Proceedings of the National Academy of Sciences 105:1108111086.CrossRefGoogle ScholarPubMed
Gee, G. W. and Bauder, J. W. (1986). Particle size analysis. In Methods of Soil Analysis. Part 1, 383411, 2nd edn. (Ed. Klute, A.). Agron. Monogr. 9. Madison, WI: ASA and SSSA.Google Scholar
Haussmann, B. I. G., Rattunde, F. H., Weltzien-Rattunde, E., Traore, P. S. C., vom Brocke, K. and Parzies, H. K. (2012). Breeding strategies for adaptation of pearl millet and sorghum to climate variability and change in West Africa. Journal of Agronomy and Crop Science. In press.Google Scholar
Hintze, L. H., Renkow, M. and Sain, G. (2003). Variety characteristics and maize adoption in Honduras. Agricultural Economics 29:307317.CrossRefGoogle Scholar
Kafle, B. (2010). Determinants of adoption of improved maize varieties in developing countries: a review. International Research Journal of Applied and Basic Statistics 1 (1):17.Google Scholar
Kitch, L. W., Boukar, O., Endondo, C. and Murdock, L. L. (1998). Farmer acceptability criteria in breeding cowpea. Experimental Agriculture 34:475486.CrossRefGoogle Scholar
Kostandini, G., Mills, B. F., Omamo, S. W. and Wood, S. (2009). Ex-ante analysis of the benefits of transgenic drought tolerance research on cereal crops in low-income countries. Agricultural Economics 40:477492.Google Scholar
Li, Y. P., Ye, W., Wang, M. and Yan, X. D. (2009). Climate change and drought: a risk assessment of crop-yield impacts. Climate Research 39:3146.Google Scholar
Long, J. S. and Freese, J. (2001). Regression Models for Categorical Dependent Variables Using Stata. College Station, TX: Stata Press.Google Scholar
Lunduka, R., Fisher, M. and Snapp, S. (2012). Could farmer interest in a diversity of seed attributes explain adoption plateaus for modern maize varieties in Malawi? Food Policy 37:504510.CrossRefGoogle Scholar
Lunduka, R., Ricker-Gilbert, J. and Fisher, M. (2013). What are the farm-level impacts of Malawi's farm input subsidy program? A critical review. Agricultural Economics 44 (6):563579.Google Scholar
Maddala, G., 1983. Limited-Dependent and Qualitative Variables in Econometrics. Cambridge, England: Cambridge University Press.Google Scholar
Mhango, W., Snapp, S. S. and Kanyama-Phiri, G. Y. (2012). Opportunities and constraints to legume diversification for sustainable cereal production on African smallholder farms. Regenerative Agriculture and Food Systems. In press.Google Scholar
Mhike, X., Okori, P., Kassie, G. T., Magorokoshu, C. and Chikobvu, S. (2012). An appraisal of farmer variety selection in drought prone areas and its implications to breeding for drought tolerance. Journal of Agricultural Science 4 (6):2743.Google Scholar
Moser, C. M. and Barrett, C. B. (2006). The complex dynamics of smallholder technology adoption: the case of SRI in Madagascar. Agricultural Economics 35:373388.Google Scholar
Osbahr, H., Dorward, P., Stern, R. and Cooper, S. 2011. Supporting agricultural innovation in Uganda to respond to climate risk: linking climate change and variability with farmer perceptions. Experimental Agriculture 47 (2):293316.Google Scholar
Salasya, B., Mwangi, W., Mwabu, D. and Diallo, A. (2007). Factors influencing adoption of stress-tolerant maize hybrid (WH 502) in Western Kenya. African Journal of Agricultural Research 2 (10):544551.Google Scholar
Smale, M. and Heisey, P. (1994). Maize research in Malawi revisited: an emerging success story? Journal of International Development 6 (6):689706.Google Scholar
Smale, M. and Mason, N. (2012). Demand for maize hybrids, seed subsidies, and seed decisionmakers in Zambia. HarvestPlus Working Paper, 8. Retrieved from http://www.harvestplus.org/publications/14.Google Scholar
Sperling, L. and Scheidegger, U. (1995). Participatory Selection of Beans in Rwanda: Results, methods, and Institutional Issues (Gatekeeper Series No. 51). London, England: International Institute for Environment and Development.Google Scholar
Staal, S. J., Baltenkweck, Il, Waithaka, M. M., de Wolff, T. and 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):295315.Google Scholar
Suri, T. (2011). Selection and comparative advantage in technology adoption. Econometrica 79:159209.Google Scholar
Syroka, J. and Nucifora, A. (2010). National Drought Insurance for Malawi. Policy Research Working Paper Number 5169, The World Bank, 20 pp.Google Scholar