Adoption of Agricultural Digital Services by Smallholder Farmers in the Central and Southern Zones of Senegal

Author(s)

Dada Gueye , Katim Toure , Alex Chigoverah , Amadou Cisse , Cheick Atab Mane , Saliou Ndiaye ,

Download Full PDF Pages: 45-53 | Views: 29 | Downloads: 11 | DOI: 10.5281/zenodo.17840665

Volume 9 - December 2025 (12)

Abstract

The use of digital services offers numerous benefits to agricultural value chain actors including smallholder farmers. However, knowledge gaps exist on the adoption of digital services in agriculture in sub-Saharan Africa. In this context, a survey was conducted to identify the determinants of farmers using digital agricultural services in the central and southern zones of Senegal. Descriptive analyses and simple logistic models were used to identify types of digital services farmers use and the key factors influencing their adoption. Overall, 30% of the sampled used digital agricultural services with the most frequently used services in order of importance being: rainfall forecasts (30%), cumulative rainfall (28%), and market information (7%). Other services such as online training (4%), air temperature forecasts, wind intensity and direction (3%), rainfall breaks (2%), flood risks (2%), seasonal forecasts (1%), out-of-season rainfall (1%) and wet sequences (1%) were rarely used in the two study sites. Highlighted adoption determinants included training in good agricultural practices, sensitization to digital services, and awareness of a producer who uses these services. Millet and cowpea producers were reported to be less likely to use digital agricultural services than those who do not grow one or other crops. By contrast, producers who grow maize are more likely to use digital services than non-maize growers. Finally, the higher the TLUs (Tropical Livestock Units) the producer owns, the more likely they are to use agricultural digital services. Young people and male producers are also more likely to use digital agricultural services.1.

Keywords

agricultural digital services, adoption, Senegal

References

Aubert, B.A., Schroeder, A., Grimaudo, J., 2012.  Informatics as a Catalyst for Sustainable Agriculture: An Empirical Analysis of Farmers' Decision to Adopt Precision Agriculture Technology. Decis. Support. Syst., 510-520. 10.1016/j.dss.2012.07.002.

Aymard, M., 1983. Self-consumption and Market: Chayanov, Labrousse Or The Roy Ladurie?  Annals. History, Social Sciences: 1392–1410. 10.3406/ahess.1983.411027

African Development Bank. 2022. Senegal digital market-oriented initiative for women smallholder farmers economic empowerment and financial inclusion_SDMo4SFI. Project RFTA.

Barnes, A.P., Soto, I., Eory, V., Beck, B., Balafoutis, A., S ́anchez, B., Vangeyte, J., Fountas, S., van der Wal, T., G ́omez-Barbero, M., 2019. Exploring the adoption of precision agricultural technologies: A cross-regional study of EU farmers. Land Use Policy, 163-174. 10.1016/j.landusepol.2018.10.004

DAPSA, 2020. Report on the final results of the Annual Agricultural Survey (EAA) 2018-2019

Diouf, N. S., Ouedraogo, I., Zougmoré, R. B., Ouedraogo, M, Partey, S. T. and Gumucio, T. 2019. Factors influencing gendered access to climate information services for farming in SenegalGender, Technology and Development, 23(2), 93-110.

FAO and ITU. 2022. Status of digital agriculture in 47 sub-Saharan African countries. FAo, Rome..https://doi.org/10.4060/cb7943en. .

Isgin, T., Bilgic, A., Forster, D.L., Batte, M.T., 2008. Use of counting data models to determine factors affecting farmers' quantitative decisions regarding the adoption of precision agriculture technology. Comput. Electron. Agric., 231-242. 10.1016/j.compag.2008.01.004

Lambert, D.M., Paudel, K.P., Larson, J.A., 2015. Cluster adoption of precision farming technologies by cotton producers. J. Agric. Resour. Econ: 325-345. 10.22004/ag.econ.206599

Lynne, G.D., Franklin Casey, C., Hodges, A., Rahmani, M., 1995. Conservation technology adoption decisions and theory of planned behavior. J. Econ. Psychol., 581-598. 10.1016/0167-4870(95)00029-1

Maziya, M., Mvelase, L. and Dlamini, M. M. 2024. Smallholder farmers’ climate change adaptation strategies and their effect on household food security: evidence from KwaZulu-Natal, South Africa. Agriculture, 14(10), 1729.

Pino, G., Toma, P., Rizzo, C., Miglietta, P., Peluso, A., Guido, G., 2017. Determinants of farmers' intention to adopt water-saving measures: evidence in Italy. Sustainability: 06-10. 10.3390/su9010077

Pivoto, D., Barham, B., Waquil, P.D., Foguesatto, C.R., Corte, V.F.D., Zhang, D., Talamini, E., 2019. Factors influencing the adoption of smart agriculture by Brazilian grain farmers. Int. Food Agribus. Manag. Rev. 571-588. 10.22434/IFAMR2018.0086

Tamirat, T.W., Pedersen, S.M., Lind, K.M., 2017. Farm and operator characteristics affecting the uptake of precision agriculture in Denmark and Germany. Acta Agric. Scand. B - Soil Plant Sci.: 349-357. 10.1080/09064710.2017.1402949

Sakho-Jimbira, S. and Hathie, I. 2020. The future of agriculture in sub-Saharan Africa.Policy Brief No 2. Southern Voice.

Shang L., Thomas H., Maria K. G, Jan B., Sebastian R. 2021. Adoption and diffusion of digital agricultural technologies - integration of evidence at the farm level and system interaction; 02-12. 10.1016/j.agsy.2021.103074

Cite this Article: