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Economic impact analysis of marker-assisted breeding for resistance to pests and post harvest deterioration in cassava

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  • Rudi, Nderim
  • Norton, George W.
  • Alwang, Jeffrey Roger
  • Asumugha, Godwin N.

Abstract

Marker-assisted breeding could have a major impact in relieving productivity constraints that cannot as easily or rapidly be relieved by conventional breeding alone. This paper estimates the benefits of using marker-assisted breeding, as compared to conventional breeding alone, in developing cassava varieties resistant to cassava mosaic disease, green mite, whitefly and post-harvest physiological deterioration in Nigeria, Ghana and Uganda. Marker-assisted breeding is estimated to save at least four years in the breeding cycle for varieties resistant to the pests and to result in incremental net benefits over 25 years in the range of $34 to $800 million depending on the country, the particular constraint and various assumptions. Benefits may reach as high as $3 billion for resistance to post-harvest physiological deterioration, as conventional breeding is not projected to solve the problem within a reasonable time frame.

Suggested Citation

  • Rudi, Nderim & Norton, George W. & Alwang, Jeffrey Roger & Asumugha, Godwin N., 2010. "Economic impact analysis of marker-assisted breeding for resistance to pests and post harvest deterioration in cassava," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 4(2), pages 1-13, June.
    • Handle: RePEc:ags:afjare:93862
    DOI: 10.22004/ag.econ.93862
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    References listed on IDEAS

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    1. Michael E. Johnson & William A. Masters & Paul V. Preckel, 2006. "Diffusion and spillover of new technology: a heterogeneous‐agent model for cassava in West Africa," Agricultural Economics, International Association of Agricultural Economists, vol. 35(2), pages 119-129, September.
    2. Nweke, Felix, 2004. "New challenges in the cassava transformation in Nigeria and Ghana:," EPTD discussion papers 118, International Food Policy Research Institute (IFPRI).
    3. Bénédicte Vidaillet & V. d'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
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    Cited by:

    1. Naseem, Anwar & Singla, Rohit, 2013. "Ex Ante Economic Impact Analysis of Novel Traits in Canola," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(2), pages 1-21, August.
    2. Jeffrey Alwang & Samy Sabry & Kamel Shideed & Atef Swelam & Habib Halila, 2018. "Economic and food security benefits associated with raised-bed wheat production in Egypt," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 589-601, June.
    3. Kergna, Alpha & Smale, Melinda & Assima, Amidou & Diallo, Abdoulaye & Weltzien, Eva & Rattunde, Fred, 2017. "The potential economic impact of Guinea-race sorghum hybrids in Mali: A comparison of research and development paradigms," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 12(01), March.
    4. Kergna, Alpha & Smale, Melinda & Assima, Amidou & Weltzien, Eva & Rattunde, Fred, 2016. "The potential economic impact of guinea-race sorghum hybrids in Mali: Comparing research paradigms," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246964, African Association of Agricultural Economists (AAAE).
    5. Thornton, Philip K. & Whitbread, Anthony & Baedeker, Tobias & Cairns, Jill & Claessens, Lieven & Baethgen, Walter & Bunn, Christian & Friedmann, Michael & Giller, Ken E. & Herrero, Mario & Howden, Mar, 2018. "A framework for priority-setting in climate smart agriculture research," Agricultural Systems, Elsevier, vol. 167(C), pages 161-175.

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