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Participatory Evaluation of Integrated Pest and Soil Fertility Management Options Using Ordered Categorical Data Analysis

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  • Rutto, Esther
  • De Groote, Hugo
  • Vanlauwe, Bernard
  • Kanampiu, Fred
  • Odhiambo, George D.
  • Khan, Zeyaur R.

Abstract

During participatory rural appraisals, farmers at the Lake Victoria basin of Kenya and Uganda identified Striga, stemborer and declining soil fertility as three major constraints to maize production To reduce food insecurity, several innovative integrated technologies to address these constraints have been developed, including push-pull (maize intercropped with Desmodium and surrounded by napier grass), maize-soybean and maize-crotalaria rotations, and Imazapyrresistant (IR) maize seed coated with the herbicide. To let farmers evaluate the new technologies, 12 demonstration trials, comparing the different technologies, were established in four villages in Siaya and Vihiga districts (Western Kenya) and two villages in Busia (Uganda). These evaluations, where farmers' appreciation and feedback on the technology are captured, are an important step in technology development. During field days at the end of short rainy seasons of 2003 and 2004, 504 farmers individually observed and rated each treatment under the different cropping systems, with and without IR maize, and with and without fertilizer, with a maize continuous monocrop as control. Farmers scored each of the 16 treatments on an ordered scale of five categories: very poor, poor, average, good, and very good. The treatments were scored for each of the criteria farmers has previously determined (including yield, resistance to Striga and stemborer, and improvement of soil fertility). Analysis of the evaluation, using ordinal regression, show significant differences in farmers' preference by year and site. There was, however, little effect of farm and farmer characteristics such as farm size and gender of the observer. Ordinal regression of farmers' scores are not as intuitive and also bit cumbersome to use, but they have a better theoretical foundation than other methods, in particular the use of means. This paper shows how the method can be used, and concludes that, with some effort, it is a convenient way to analyse farmers' ranking of a large number of options.

Suggested Citation

  • Rutto, Esther & De Groote, Hugo & Vanlauwe, Bernard & Kanampiu, Fred & Odhiambo, George D. & Khan, Zeyaur R., 2006. "Participatory Evaluation of Integrated Pest and Soil Fertility Management Options Using Ordered Categorical Data Analysis," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25317, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae06:25317
    DOI: 10.22004/ag.econ.25317
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    References listed on IDEAS

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    1. Bellon, Mauricio R. & Adato, Michelle & Becerril, Javier & Mindek, Dubravka, 2006. "Poor farmers' perceived benefits from different types of maize germplasm: The case of creolization in lowland tropical Mexico," World Development, Elsevier, vol. 34(1), pages 113-129, January.
    2. Duflo, Esther & Glennerster, Rachel & Kremer, Michael, 2008. "Using Randomization in Development Economics Research: A Toolkit," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 61, pages 3895-3962, Elsevier.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    4. De Groote, Hugo & Wangare, Lucy & Kanampiu, Fred & Odendo, Martins & Diallo, Alpha & Karaya, Haron & Friesen, Dennis, 2008. "The potential of a herbicide resistant maize technology for Striga control in Africa," Agricultural Systems, Elsevier, vol. 97(1-2), pages 83-94, April.
    5. Rosegrant, Mark W. & Paisner, Michael S. & Meijer, Siet & Witcover, Julie, 2001. "2020 Global food outlook," Food policy reports 30, International Food Policy Research Institute (IFPRI).
    6. Versteeg, M. N. & Amadji, F. & Eteka, A. & Gogan, A & Koudokpon, V., 1998. "Farmers' adoptability of Mucuna fallowing and agroforestry technologies in the coastal savanna of Benin," Agricultural Systems, Elsevier, vol. 56(3), pages 269-287, March.
    7. Bellon, Mauricio R. & Reeves, Jane, 2002. "Quantitative Analysis Of Data From Participatory Methods In Plant Breeding," Manuals 23718, CIMMYT: International Maize and Wheat Improvement Center.
    8. De Groote, Hugo & Wangare, Lucy & Kanampiu, Fred & Odendo, Martins & Friesen, Dennis, 2005. "Potential Markets for Herbicide Resistant Maize Seed for Striga Control in Africa," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24690, European Association of Agricultural Economists.
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    1. Hugo De Groote & Bernard Vanlauwe & Esther Rutto & George D. Odhiambo & Fred Kanampiu & Zeyaur R. Khan, 2010. "Economic analysis of different options in integrated pest and soil fertility management in maize systems of Western Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 41(5), pages 471-482, September.

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