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Logistic modelling of smallholder livestock farmers’ adoption of tree-based fodder technology in Zimbabwe

Author

Listed:
  • Jera, R.
  • Ajayi, Olu Clifford

Abstract

Based on field data collected from 131 small scale dairy farmers that were randomly selected from four agro-ecological zones, this study assessed the potential of adoption of fodder bank technology as a means for improving livestock production and income generation for smallholder farmers in Zimbabwe. Using a logit modelling approach, it also identified the drivers of adoption of the technology by analysing the influence of household characteristics and ecological factors on farmers’ decision to adopt the technology. The model correctly predicted 75% of observed adoption and non-adoption by farmers. Results reveal that dairy herd size, land holding size, membership of dairy association and agro-ecological potential are the key factors influencing farmers’ adoption of fodder bank. Age, sex, household size and educational level of farmers play lesser role. Male and female farmers were equally likely to take up and practice fodder bank if they are given equal access to information and incentives. The study recommends farmer-led extension approaches where farmers who possess certain key characteristics should constitute the initial group for disseminating information regarding the technology in rural communities. The results highlight the importance of access to dairy product markets as a driver for the adoption of fodder banks. It is recommended that forging a strategic partnership with the Dairy Development Programme (DDP) will offer high potential for enhancing the scaling up of the adoption and impact of fodder bank technology in the country.

Suggested Citation

  • Jera, R. & Ajayi, Olu Clifford, 2008. "Logistic modelling of smallholder livestock farmers’ adoption of tree-based fodder technology in Zimbabwe," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 47(3), pages 1-14, September.
    • Handle: RePEc:ags:agreko:44033
    DOI: 10.22004/ag.econ.44033
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    Cited by:

    1. Sharimakin Akinwumi & Dada James Temitope, 2020. "Access to Finance, Indigenous Technology and Food Security in Nigeria: Case Study of Ondo Central Senatorial District," Economics and Culture, Sciendo, vol. 17(2), pages 75-87, December.
    2. Yusuph J. Kulindwa, 2016. "Key factors that influence households’ tree planting behaviour," Natural Resources Forum, Blackwell Publishing, vol. 40(1-2), pages 37-50, February.
    3. Soto, Iria & Achten, Wouter M.J. & Muys, Bart & Mathijs, Erik, 2015. "Who benefits from energy policy incentives? The case of jatropha adoption by smallholders in Mexico," Energy Policy, Elsevier, vol. 79(C), pages 37-47.
    4. Aslihan Arslan & Kristin Floress & Christine Lamanna & Leslie Lipper & Solomon Asfaw & Todd Rosenstock, 2020. "IFAD RESEARCH SERIES 63 - The adoption of improved agricultural technologies - A meta-analysis for Africa," IFAD Research Series 304758, International Fund for Agricultural Development (IFAD).
    5. Beatrice Dingha & Leah Sandler & Arnab Bhowmik & Clement Akotsen-Mensah & Louis Jackai & Kevin Gibson & Ronald Turco, 2019. "Industrial Hemp Knowledge and Interest among North Carolina Organic Farmers in the United States," Sustainability, MDPI, vol. 11(9), pages 1-17, May.
    6. Kampmann, Willi & Kirui, Oliver Kiptoo, 2021. "Role of Farmers’ Organizations in Agricultural Transformation in Africa: Overview of Continental, Regional, and Selected National Level Organizations," Working Papers 309358, University of Bonn, Center for Development Research (ZEF).
    7. Mofokeng, Maine & Vink, Nick, 2013. "Factors Affecting the Hedging Decision of Maize Farmers in Gauteng Province," 2013 Fourth International Conference, September 22-25, 2013, Hammamet, Tunisia 161465, African Association of Agricultural Economists (AAAE).
    8. Birhanu, Mulugeta Yitayih & Girma, Anteneh & Puskur, Ranjitha, 2017. "Determinants of success and intensity of livestock feed technologies use in Ethiopia: Evidence from a positive deviance perspective," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 15-25.
    9. John N. Ng’ombe & Thomson H. Kalinda & Gelson Tembo, 2017. "Does adoption of conservation farming practices result in increased crop revenue? Evidence from Zambia," Agrekon, Taylor & Francis Journals, vol. 56(2), pages 205-221, April.
    10. Kebebe, E. G., 2017. "Household nutrition and income impacts of using dairy technologies in mixed crop–livestock production systems," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(4), October.
    11. Ayuya, Oscar Ingasia, 2010. "Evaluation Of Willingness To Accept And Adopt Clean Development Mechanism Projects Among Smallscale Farmers In Njoro District, Kenya," Research Theses 117799, Collaborative Masters Program in Agricultural and Applied Economics.
    12. Kinuthia, Emmanuel K., 2010. "The Effects Of The International Smallgroup And Tree Planting Program On Household Income In Nyeri District, Kenya," Research Theses 117709, Collaborative Masters Program in Agricultural and Applied Economics.
    13. Zabala, Aiora & Barrios, Luis Enrique García & Pascual, Unai, 2022. "From participation to commitment in silvopastoral programmes: Insights from Chiapas, Mexico," Ecological Economics, Elsevier, vol. 200(C).

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