Determinants of Farm Machinery Adoption Among Small-Scale Farmers: A Statistical Case Study from Borno State, Nigeria
Abstract
This study aimed to analyze the rate and determinants of farm machinery adoption among small- scale farmers using both descriptive and inferential statistical techniques. The study revealed that only 46% of respondents had adopted at least one form of farm machinery. Education level, farm size, access to credit, and extension services were statistically significant predictors of machinery adoption. A logistic regression model indicated that access to credit increases the likelihood of adoption by 17.1%, while an additional hectare of land increases the odds by 19.6%. The ROC curve had an AUC of 0.82, showing that the model had strong classification accuracy. The correlation matrix showed positive and significant relationships between machinery use and all other independent variables. Regional disparities in adoption rates were also significant (ANOVA, p < 0.01), suggesting location-specific factors influence adoption behavior among 200 small-scale farmers in Biu, Borno State.
Keywords
AnalysisFarm MachineryAdoption RateBorno StateFarmers
References
Gifford, R. C. (1981). Agricultural mechanization in development: guidelines for strategy formulation (No. 45, pp. 77-pp). Koebler, Jason (2024-05-12). "Solar Storm Knocks Out Farmers' Tractor GPS Systems During Peak Planting Season". 404 Media. Retrieved 2024-05-13. Rome: Food and Agriculture Organization of the United Nations (FAO). doi:10.4060/cb9479en. ISBN 978-92-5-136043-9. Rome: Food and Agriculture Organization of the United Nations (FAO). 2022. The State of Food and Agriculture 2022 ? Leveraging agricultural automation for transforming agrifood systems. doi:10.4060/cb9479en. ISBN 978-92-5-136043-9. Zhou, X.; Ma, W.; Li, G.; Qiu, H. Farm Machinery Use and Maize Yields in China: An Analysis Accounting for Selection Bias and Heterogeneity. Aust. J. Agric. Resour. Econ. 2020, 64, 1282–1307. [CrossRef] Akram, Nida, et al. “Study on the Socioeconomic Factors Affecting Adoption of Agricultural Machinery.” Unknown Journal, Feb. 2020, doi:10.7176/jesd/11-3-07. Quan, Xiuhao, and Reiner Doluschitz. “Factors Influencing the Adoption of Agricultural Machinery by Chinese Maize Farmers.” Agriculture, vol. 11, no. 11, Nov. 2021, pp. 1090– 1090, doi:10.3390/agriculture11111090. Iqbal, M. A., Iqbal, A., Afzal, S., Akbar, N., Abbas, R. N., & Khan, H. Z. (2015). In Pakistan, agricultural mechanization status and future prospects. American-Eurasian Journal of Agricultural & Environmental Sciences, 15(1), 122-128. "Nigeria at a glance". www.fao.org. Retrieved 2020-11-24 Santos Valle, S.; Kienzle, J. (2020). Agriculture 4.0 – Agricultural robotics and automated equipment for sustainable crop production. Integrated Crop Management No. 24. Rome: Food and Agriculture Organization of the United Nations (FAO) Food and Agriculture Organization of the United Nations (FAO). 2022. doi:10.4060/cc2459en. ISBN 978-92-5-137005-6. Santos Valle, S.; Kienzle, J. (2020) wiki.openag.media.mit.edu. Archived from the original on 2019-07-20. Retrieved 2019-07-20 Pingali, P. (2007). Agricultural mechanization: Adoption patterns and economic impact. Handbook of Agricultural Economics, 3, 2779–2805. Sims, B. G., & Kienzle, J. (2016). Making mechanization accessible to smallholder farmers in sub- Saharan Africa. Environments, 3(11), 1-18 Sarkar, Anupam. “Agricultural Mechanization in India: A Study on the Ownership and Investment in Farm Machinery by Cultivator Households across Agro-Ecological Regions.” Millennial Asia, vol. 11, no. 2, Aug. 2020, pp. 160–86, doi:10.1177/0976399620925440 Hu, Yuan, Ziyang Zhou. Li Zhou., Chunhua Liu (2024),. “Self-Owned or Outsourced? The Impact of Farm Machinery Adoption Decisions on Chinese Farm Households’ Operating Income.” Agriculture, vol. 14, no. 11, Oct. 2024, pp. 1936–1936, doi:10.3390/agriculture14111936. Coase, R.H (1995). The Nature of the Firm. In Essential Readings in Economics; Estrin, S., Marin, A., Eds.; Palgrave: London, UK. Claude, M.; Shirley, M.M. (Eds.) Handbook of New Institutional Economics; Springer: Berlin/Heidelberg, Germany, 2005 Tufa, A.; Alene, A.; Ngoma, H.; Marenya, P.; Manda, J.; Matin, A.; Thierfelder, C.; Chikoye, D. Willingness to pay for agricultural mechanization services by smallholder farmers in Malawi. Agribusiness 2024, 40, 248–276. [CrossRef] Doss, C. R. (2006). Analyzing technology adoption using microstudies: Limitations, challenges, and opportunities for improvement. Agricultural Economics, 34(3), 207–219 Pingali, P. (2007). Agricultural mechanization: Adoption patterns and economic impact. In Handbook of Agricultural Economics (Vol. 3, pp. 2779–2805) Feder, G., Just, R. E., & Zilberman, D. (1985). Adoption of agricultural innovations in developing countries: A survey. Economic Development and Cultural Change, 33(2), 255–298 Mottaleb, K. A., Krupnik, T. J., & Erenstein, O. (2017). Factors associated with small-scale agricultural machinery adoption in Bangladesh: Insights from nationally representative survey data. Renewable Agriculture and Food Systems, 32(5), 450–465. Biggs, S., & Justice, S. (2015). Rural and agricultural mechanization: A history of the spread of small engines in selected Asian countries. IFPRI Discussion Paper 01443 Dube-Takaza, T., Maumbe, B. M., & Parwada, C. (2023). Agricultural technology adoption for smallholder small grain farmers in Zimbabwe. Implications for food system transformation and sustainability. International Food and Agribusiness Management Review, 26(5), 882- https://doi.org/10.22434/ifamr2022.0114 FAO. 2016. Food and Agriculture Key to achieving the 2030 Agenda for Sustsianable Dvelopment. Food and Agriculture Organization of the United Nations. Rome. United Nations. 2015. Transforming our world the 2030 agenda for sustainable development A/RES/70/1. United Nations, New York, NY Beyene, N.A. 2019. Impact of technology adoption on agricultural productivity and income: a case study of improved teff variety adoption in north eastern Ethiopia. Agricultural & Technology Journal 20(4): 205–216 Feder, G., E.R. Just and D. Zilberman. 1985. Adoption of Agricultural Innovations in Developing Countries: A Survey. Economic Development and Cultural Change 33(2): 255–298. Feder, G., R. Murgai and J. Quizon. 2003. Sending farmers back to school: the impact of farmer field schools in Indonesia. Review of Agriculture Economics 26(1): 45–46 Muzari, W., W. Gatsi and S. Muvhunzi. 2013. The impact of technology adoption on smallholder agricultural productivity in sub-Saharan Africa: a review. Journal of Sustainable Development 5(8): 69–77. Rogers, E. 2003. Diffusion of innovations, 5th edn. Free Press, New York, NY. Ugochukwu, A. and P.W.B. Philip 2018. Technology adoption by agricultural producers: a review of the literature. In N. Kalaitzandonakes, E.G. Carayannis, E. Grigoroudis and S. Rozakis (eds.) From Agriscience to Agribusiness. Springer, Berlin, pp. 361–377. Denning, P. and T. Lewis. 2019. Uncertainty. Communications of the ACM 62(12): 26–28 Mathew, A. 2015. The feasibility of small grains as an adoptive strategy to climate change. Russian Journal of Agricultural and Socio-Economic Sciences 41(5): 40–55
More Articles from INTERNATIONAL JOURNAL OF AGRICULTURAL AND EARTH SCIENCE
Influence of Tree Species on Soil Nutrients Status in Murke Grassland and Nkafamiya Montane Soils of Adamawa State, Nigeria
Author: Mustapha DAUDA, Emmanuel Ephraim DISHAN, B. Y. Duhu, AbdulRahman AHMAD
Effect of Different Cropping Systems on Soil Fungi and Nematodes in Obelle, Emohua Local Government Area
Author: Ikechi, B. A., and Ene, D. U.
Spatio-Temporal Dynamics of Land Use Change in Uyo Capital City, Akwa Ibom State, Nigeria
Author: Elijah, U.D Uwem Ituen
Effect of Organic Materials on Soil Bacteria Population and Carbon Dioxide (Co2) Evolution in an Ultisol
Author: Osiriamhe, P. W., and Ene, D. U.
Isolation and Identification of Bacteria in Soils Under Different Land Use in Obelle, Emuoha Local Government Area, Rivers State, Nigeria
Author: Nweke, A. F., and Ene, D. U.