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Why Farmers Are Hesitant to Adopt What Appears Good on the Basis of Science: Understanding Farmers’ Perceptions of Biophysical Research

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  • Joel Buyinza
  • Ian K. Nuberg
  • Catherine W. Muthuri
  • Matthew D. Denton

Abstract

This study conducted a series of extension events that were followed by farmer interviews with 394 farmers who had participated in an initial household survey in 2018, involving four farmer categories- 1] those actively participating in the Trees for Food Security (T4FS) project from phase 1 (2014); 2] farmers neighbouring those actively participating in the T4FS project from phase 1; 3] farmers actively participating in the T4FS project from phase 2 (2017) and; 4] farmers living distant and unaware of the T4FS project. The study drew upon knowledge generated from biophysical experiments on tree water use, shade tree planting and management in smallholder coffee-bean agroforestry systems to assess farmers’ perceptions and willingness to adopt practices emanating from the study following exposure to the research outputs. The main form of extension used was through display and viewing of posters and a translated power point presentation of the research outputs on impact of tree canopy pruning on tree and coffee plant water use and productivity of coffee and common beans. We present the key messages obtained by the participants from the extension activities conducted, their preferred crop and management combinations, perceptions towards the research outputs and willingness to adopt the practices recommended by the study. We contend that smallholder farmers are hesitant to adopt innovations due to an underlying culture of financial expectancy leading to ‘pseudo adoption’, underutilisation of existing social networks during research and extension, period of exposure to a technology, and limitations in measuring and predicting adoption. We align the four farmer categories to the Process of Agricultural Utilisation Framework (PAUF) criteria, leading to a better understanding of the impact of research and development projects and agroforestry tree planting and management adoption pathways among smallholder farmers. This would enable introduction of socially and biophysically appropriate agroforestry interventions into local realities.

Suggested Citation

  • Joel Buyinza & Ian K. Nuberg & Catherine W. Muthuri & Matthew D. Denton, 2022. "Why Farmers Are Hesitant to Adopt What Appears Good on the Basis of Science: Understanding Farmers’ Perceptions of Biophysical Research," Journal of Sustainable Development, Canadian Center of Science and Education, vol. 15(3), pages 1-68, May.
  • Handle: RePEc:ibn:jsd123:v:15:y:2022:i:3:p:68
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    References listed on IDEAS

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    1. Kazushi Takahashi & Rie Muraoka & Keijiro Otsuka, 2020. "Technology adoption, impact, and extension in developing countries’ agriculture: A review of the recent literature," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 31-45, January.
    2. Kuehne, Geoff & Llewellyn, Rick & Pannell, David J. & Wilkinson, Roger & Dolling, Perry & Ouzman, Jackie & Ewing, Mike, 2017. "Predicting farmer uptake of new agricultural practices: A tool for research, extension and policy," Agricultural Systems, Elsevier, vol. 156(C), pages 115-125.
    3. Kiptot, Evelyne & Hebinck, Paul & Franzel, Steven & Richards, Paul, 2007. "Adopters, testers or pseudo-adopters? Dynamics of the use of improved tree fallows by farmers in western Kenya," Agricultural Systems, Elsevier, vol. 94(2), pages 509-519, May.
    4. Samuel Benin & Ephraim Nkonya & Geresom Okecho & Joseé Randriamamonjy & Edward Kato & Geofrey Lubade & Miriam Kyotalimye, 2011. "Returns to spending on agricultural extension: the case of the National Agricultural Advisory Services (NAADS) program of Uganda," Agricultural Economics, International Association of Agricultural Economists, vol. 42(2), pages 249-267, March.
    5. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    6. Van Loon, Jelle & Woltering, Lennart & Krupnik, Timothy J. & Baudron, Frédéric & Boa, Maria & Govaerts, Bram, 2020. "Scaling agricultural mechanization services in smallholder farming systems: Case studies from sub-Saharan Africa, South Asia, and Latin America," Agricultural Systems, Elsevier, vol. 180(C).
    7. Graeme Larsen, 2011. "Understanding the early stages of the innovation diffusion process: awareness, influence and communication networks," Construction Management and Economics, Taylor & Francis Journals, vol. 29(10), pages 987-1002.
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    Cited by:

    1. Karl Wienhold & Luis F. Goulao, 2023. "The Embedded Agroecology of Coffee Agroforestry: A Contextualized Review of Smallholder Farmers’ Adoption and Resistance," Sustainability, MDPI, vol. 15(8), pages 1-30, April.

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    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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