Do Rice Farmers Share a Similar Perspective on the Choice of Varieties? Evidence from a Survey Across Selected Rice Growing Counties in Kenya
DOI:
https://doi.org/10.58425/ijas.v4i1.393Keywords:
Attributes, grid analysis approach, rational farmer, rice varieties, variety choiceAbstract
Aim: This baseline survey was designed to explore the demand for improved certified rice seed in Kenya, focusing on farmers’ decision-making frameworks for selecting rice varieties.
Methods: Through participatory methods710 respondents were selected For a more in-depth understanding, four counties were purposefully selected based on their differing histories and intensity of rice production: two counties with a long history and high intensity of rice farming, and two with a more moderate history and two with relatively low production intensity. The survey employed a cross-sectional design of a descriptive nature, involving 30 days of rigorous data collection using questionnaires across all rice production regions nested within counties. Key attributes/criteria that farmers use to select rice varieties were identified from data points across the four counties. These attributes were analyzed using a Grid Analysis approach, allowing for county-based and overall rankings of the varieties selected.
Results: The study found that farmers consistently prioritize attributes such as market demand, early maturity, head rice recovery, taste and high yield, irrespective of spatial separation. These influential variables govern attributes’ preference and choice decisions. This influence is largely attributed to the shared public good of research and extension services.
Conclusion: The study confirms that Kenyan rice farmers are rational decision-makers, driven by the objective of profit maximization, as shown in their unanimous selection of market demand as the most critical attribute when choosing a rice variety to grow.
Recommendation: The study recommend that research planning and implementation of the rice improvement programme needs to involve farmers from the initial stages to ensure that their rational behaviour is integrated into future agricultural strategies.
References
Anang, B. T., Adjei, S. N., & Abiriwe, S. A. (2011). Consumer preferences for rice quality characteristics and the effects on price in the Tamale Metropolis, Northern Region, Ghana. International Journal of AgriScience, 1(2), 67–74. http://www.inacj.com
Aurier, P., & Mejia, V. (2014). Multivariate logit and probit models for simultaneous purchases: Presentation, uses, appeal and limitations.
Bhuiyan, F. R., & Rahim, A. T. M. (2015). Consumer’s sensory perception of food attributes: A survey on flavor. Journal of Food and Nutrition Sciences, 3(1–2), 157–160. https://doi.org/10.11648/j.jfns.s.2015030102.40
Chukwuma, J. O., Emeka, D. U., Amuche, J. A., Gorgio, O. O., Ekene, C. U., & Agwu, E. A. (2023). Perceived factors influencing farmers’ preference for rice varieties in Enugu State, Nigeria. Journal of Agricultural Extension, 27(1).
Everest, T., Sungur, A., & Ozcan, H. (2020). Determination of agricultural land suitability with a multiple criteria decision-making method in Northwestern Turkey. International Journal of Environmental Science and Technology, 18(4), 1073–1088. https://doi.org/10.1007/s13762-020-02869-9
Food and Agriculture Organization of the United Nations. (2015). The economic lives of smallholder farmers: An analysis based on household data from nine countries. FAO.
Haghani, M., & Hensher, D. A. (2021). The landscape of econometric discrete choice modelling research. Journal of Choice Modelling, 38, 100249.
Ingram, J. (2010). Technical and social dimensions of farmer learning: An analysis of the emergence of reduced tillage systems in England. Journal of Sustainable Agriculture, 34(2), 183–201. https://doi.org/10.1080/10440040903482589
Jha, C. K., & Gupta, V. (2021). Farmer’s perception and factors determining the adaptation decisions to cope with climate change: Evidence from rural India. Environmental Challenges, 4, 100138.
Juan P. Taramuel, J. P., Restrepo, I. A. M., & Barrios, D. (2023). Drivers linking farmers’ decision-making with farm performance: A systematic review and future research agenda. Sustainability, 15(14), 11025.
Kengo, M., Kimani, J., & Ho-Kang, K. (2022). Farmers’ preference for rice trait: Insights from farm surveys in Busia County, Kenya. International Journal of Agriculture, 7(1), 1–12.
Kengo, M., Kimani, J., & Sang-Bok, L. (2022). Farmers demonstrate rationality and transitivity in variety choice: Empirical evidence from two rice growing niches in coastal Kenya. International Journal of Agriculture, 6(1), 46–55. https://doi.org/10.47604/ija.1464
Kioko, J. N. (2023). Overview of Kenyan agriculture.
Langyintuo, A. S., & Bungoma, C. (2008). The effect of household wealth on the adoption of improved maize varieties in Zambia. Food Policy, 33(6), 550–559. https://doi.org/10.1016/j.foodpol.2008.04.002
Lenth, R. V. (2001). Some practical guidelines for effective sample size determination. The American Statistician, 55(3), 187–193. https://doi.org/10.1198/000313001317098149
Mutisya, M. S. (2022). Impacts of climate variability on rice farming in Mwea, Kirinyaga County, Kenya (Doctoral dissertation). Kenyatta University.
Ouattara, N., Xioping, X., & Ballo, Z. (2022). Econometric analysis of the determinants of rice farming systems choice in Côte d’Ivoire. Journal of Development and Agricultural Economics, 14(1), 1–10.
Simutowe, E., Ngoma, H., Manyanga, M., Silva, J. V., Baudron, F., Nyagumbo, I., Kalala, K., Habeenzu, M., & Thierfelder, C. (2024). Risk aversion, impatience, and adoption of conservation agriculture practices among smallholders in Zambia. PLOS ONE, 19(2), e0298421.
Solano, C., León, H., Pérez, E., Tole, L., Fawcett, R. H., & Herrero, M. (2006). Using farmer decision-making profiles and managerial capacity as predictors of farm management and performance in Costa Rican dairy farms. Agricultural Systems, 88(2–3), 395–428. https://doi.org/10.1016/j.agsy.2005.07.003
Wale, E., & Yalew, A. (2007). Farmers’ variety attribute preferences: Implications for breeding priority setting and agricultural extension policy in Ethiopia. African Development Review, 19(2), 379–396. https://doi.org/10.1111/j.1467-8268.2007.00167.x
Wang, S., Tian, Y., Liu, X., & Foley, M. (2020). How farmers make investment decisions: Evidence from a farmer survey in China. Sustainability, 12(1), 1–16.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Ruth N. Musila, Anita N. Ijayi, Sang Yeol Kim, Emily W. Gichuhi, Lucy M. Muthoni, Ji Gang Kim, Lusike Wasilwa, John Ndung’u, Milton K. Danda

This work is licensed under a Creative Commons Attribution 4.0 International License.
The authors retain the copyright and grant this journal right of first publication. This license allows other people to freely share and adapt the work but must give appropriate credit, provide a link to the license, and indicate if changes were made. They may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.