Access and Use of Information for Enhanced Adoption of Climate Smart Agricultural Practices among Smallholder Farmers in Lake Victoria Basin, Kenya

Published on 26 June 2024 | AgroEnvironmental Sustainability
Vol. 2 No. 2 (2024): June Issue | DOI: 10.59983/s2024020201
Open Access
Download PDF
Check for updates via Crossmark
AgroEnvironmental Sustainability
Stephen Ajwang , Patrick Owoche , Jonathan Mutonyi

Abstract

The value of information in agricultural production cannot be overemphasized given the challenges caused by the impact of climate change. This study evaluated the importance of accessing and using information for enhanced adoption of climate-smart agriculture (CSA) practices in sorghum production among smallholder farmers in Lake Victoria Basin, Kenya. The study used a quantitative research method with a correlation design, collecting data from 382 farmers through a questionnaire. A pilot study was conducted with a 10% sample size to assess reliability and validity achieving a CVI value of 0.877445696 and Cronbach’s alpha (α) value of 0.809. Descriptive statistics were used to determine information access and use, while correlation analysis examined associations between age and education and information access and use. The findings showed that farmers obtained information primarily from television, radio, extension workers, and neighbors and friends. The accessibility and use of this information were influenced by age and level of education. The findings are significant since they can help agricultural stakeholders identify and use appropriate channel and context-specific information to disseminate information that would enhance the adoption of CSA practices for improved sorghum yield. This may increase farmers' resilience to climate variability and improve their farming knowledge and skills, potentially leading to better livelihoods for the farming communities in the region. By advocating the provision of easily accessible and relevant information in the appropriate format and media, the findings may aid in policy formulation by providing policymakers with insights when formulating agricultural policies and legislation.

Keywords

agronomic information climate-smart agriculture decision making decision support

References

  1. Abdul-Salam, Y., & Phimister, E. (2017). Efficiency Effects of Access to Information on Small-scale Agriculture: Empirical Evidence from Uganda using Stochastic Frontier and IRT Models. Journal of Agricultural Economics, 68(2), 494–517. https://doi.org/10.1111/1477-9552.12194 [Google Scholar]
  2. Ahmed, B., Haji, J., Ketema, M., & Jemal, K. (2023). Impacts and adaptation extents of climate smart agricultural practices among smallholder farmers of Ethiopia: Implication to food and nutrition security. Cogent Economics & Finance, 11(1), 2210911. https://doi.org/10.1080/23322039.2023.2210911 [Google Scholar]
  3. Alamgir, W., & Shan, H. (2023). The Multifaceted Consequences of Climate Change on Human Health. Life and Science, 4(1), 1-10. https://doi.org/10.37185/343 [Google Scholar]
  4. Amrote, A. (2020, November). Data-driven agriculture can solve the challenge of food security in Africa. Microsoft News Center. Available online: https://news.microsoft.com/en-xm/2020/11/02/data-driven-agriculture-can-solve-the-challenge-of-food-security-in-africa/ (accessed on 16 January 2024). [Google Scholar]
  5. Apriyana, Y., Surmaini, E., Estiningtyas, W., Pramudia, A., Ramadhani, F., Suciantini, S., Susanti, E., Purnamayani, R., & Syahbuddin, H. (2021). The Integrated Cropping Calendar Information System: A Coping Mechanism to Climate Variability for Sustainable Agriculture in Indonesia. Sustainability, 13(11), 6495. https://doi.org/10.3390/su13116495 [Google Scholar]
  6. Atsiaya, G. O., Gido, E. O., & Waluse Sibiko, K. (2023). Uptake of climate-smart agricultural practices among smallholder sorghum farmers in Busia County, Kenya. Cogent Food & Agriculture, 9(1), 2204019. https://doi.org/10.1080/23311932.2023.2204019 [Google Scholar]
  7. Aturihaihi, C., Tumwesigye, W., Opio, F., & Beyihayo, G. A. (2023). Knowledge, Attitude and the Practice of Climate-Smart Agriculture among Smallholder Farmers in Isingiro District, South Western Uganda. East African Journal of Agriculture and Biotechnology, 6(1), 82-97. https://doi.org/10.37284/eajab.6.1.1154 [Google Scholar]
  8. Balo, S., & Mahata, D. (2022). A Review of Climate-smart Agriculture is a New Approach to Farming System. International Journal of Environment and Climate Change, 12(1): 2682–2692. https://doi.org/10.9734/ijecc/2022/v12i1131256 [Google Scholar]
  9. Biswas, R. (2018). The Impact of Climate Change. In R. Biswas (Ed.), Emerging Markets Megatrends (pp. 207–216). Springer International Publishing. https://doi.org/10.1007/978-3-319-78123-5_12 [Google Scholar]
  10. Bregni, S. (2015). Global Communications Newsletter. IEEE Communications Magazine, 53(6), 1–4. https://doi.org/10.1109/MCOM.2015.7120009 [Google Scholar]
  11. Byamukama, W., Businge, P. M., & Kalibwani, R. (2023). Mobile Telephony as an ICT Tool for Agricultural Information Dissemination in Developing Countries: A Review. East African Journal of Agriculture and Biotechnology, 6(1), 82. https://doi.org/10.37284/eajab.6.1.1082 [Google Scholar]
  12. Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches, 3rd ed (pp. 260). Sage Publications, Inc. [Google Scholar]
  13. Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed). SAGE Publications. pp. 127-161. [Google Scholar]
  14. Das, R., & Jha, K. K. (2022). Information Sources Utilization among Potato Farmers in North East India. Indian Research Journal of Extension Education, 22(1), 44–49. https://doi.org/10.54986/irjee/2022/jan_mar/44-49 [Google Scholar]
  15. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 [Google Scholar]
  16. Drafor, I. (2016). Access to Information for Farm-Level Decision-Making. Journal of Agricultural & Food Information, 17(4), 230–245. https://doi.org/10.1080/10496505.2016.1213170 [Google Scholar]
  17. Fabiyi, S. D., Ren, J., Han, Y., Zhu, Q., & Barclay, D. (2022). Mobile Platform for Livestock Monitoring and Inspection. 2022 3rd International Informatics and Software Engineering Conference (IISEC), 1–6. https://doi.org/10.1109/IISEC56263.2022.9998297 [Google Scholar]
  18. GSMA. (2017). Twiga Foods Improved market access for farmers and a reliable supply for vendors. Available online: https://www.gsma.com/solutions-and-impact/connectivity-for-good/mobile-for-development/wp-content/uploads/2018/05/Twiga-Foods-Improved-market-access-for-farmers-and-a-reliable-supply-for-vendors.pdf (accessed on 20 November 2023). [Google Scholar]
  19. Gudeta, A. (2022). Importance of Available Information Sources for Users: The Case of Fadis and Mechara Agricultural Research Centers, Ethiopia. International Journal of Agriculture Extension and Rural Development Studies, 9(4), 38–44. https://doi.org/10.37745/ijaerds.15/vol9n43844 [Google Scholar]
  20. Hossain, M. R., Uddin, Md. D., Khatun, S., Nizami, Md. R., Karim, Md. R., & Sheikh, Md. E. (2022). Information Requirements for Farmers and Search Behavior: A Case Study in Manda Upazila, Naogaon. British Journal of Arts and Humanities, 4(3), 63–71. https://doi.org/10.34104/bjah.022063071 [Google Scholar]
  21. Joshi, H., Rani, B., Meena, D. D., & Mundra, S. (2019). Climate smart agriculture (CSA)-building resilience to climate change. Journal of Pharmacognosy and Phytochemistry, 8(5), 124–127. [Google Scholar]
  22. Kalita, D., & Kumar Das, P. (2022). Factors Influencing the Information Needs and Information Seeking Behaviours of Farmers with Reference to Climate Change Adaptation. International Journal of Current Microbiology and Applied Sciences, 11(4), 45–49. https://doi.org/10.20546/ijcmas.2022.1104.007 [Google Scholar]
  23. Kumar, A., Kumar, P., & Sharma, R. (2023). Awareness of Farmers towards Information and Communication Technology (ICT) in the Indian Agriculture Sector. Journal of Informatics Education and Research, 3(2), 210-215. https://doi.org/10.52783/jier.v3i2.94 [Google Scholar]
  24. Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x [Google Scholar]
  25. Michael, A., Polycarp, M., Abakura, H. J., & Yidau, J. J. (2022). Analysis of poultry farmers’ information needs in Adamawa State, Nigeria. Agricultura Tropica et Subtropica, 55(1), 74–82. https://doi.org/10.2478/ats-2022-0009 [Google Scholar]
  26. Mthethwa, K. N., Ngidi, M. S. C., Ojo, T. O., & Hlatshwayo, S. I. (2022). The Determinants of Adoption and Intensity of Climate-Smart Agricultural Practices among Smallholder Maize Farmers. Sustainability, 14(24), 16926. https://doi.org/10.3390/su142416926 [Google Scholar]
  27. Mugenda, O., & Mugenda, A. (2003). Research methods: Quantitative and Qualitative methods. Revised in Nairobi, 56(12), 23–34. [Google Scholar]
  28. Nakasone, E., Torero, M., & Minten, B. (2014). The Power of Information: The ICT Revolution in Agricultural Development. Annual Review of Resource Economics, 6(2014), 533–550. https://doi.org/10.1146/annurev-resource-100913-012714 [Google Scholar]
  29. Ngigi, M. W., & Muange, E. N. (2022). Access to climate information services and climate-smart agriculture in Kenya: A gender-based analysis. Climatic Change, 174(3), 21. https://doi.org/10.1007/s10584-022-03445-5 [Google Scholar]
  30. Odini, S. (2014). Access to and Use of Agricultural Information by Small Scale Women Farmers In Support of Efforts to Attain Food Security in Vihiga County, Kenya. Journal of Emerging Trends in Economics and Management Sciences, 5(2), 80-86. [Google Scholar]
  31. Phiri, A., Chipeta, G. T., & Chawinga, W. D. (2019). Information needs and barriers of rural smallholder farmers in developing countries: A case study of rural smallholder farmers in Malawi. Information Development, 35(3), 421-434. https://doi.org/10.1177/0266666918755222 [Google Scholar]
  32. Revanth. (2019). Towards Future Farming: How Artificial Intelligence is transforming the Agriculture Industry. Available online: https://www.wipro.com/holmes/towards-future-farming-how-artificial-intelligence-is-transforming-the-agriculture-industry/ (accessed on 11 September 2023). [Google Scholar]
  33. Rogers, E. M. (1964). Review of Diffusion of Innovations [Review of Review of Diffusion of Innovations, by O. Benoit]. Revue Française de Sociologie, 5(2), 216–218. https://doi.org/10.2307/3319808 [Google Scholar]
  34. Shi, J., Mo, X., & Sun, Z. (2012). Content validity index in scale development. Journal of Central South University. Medical Sciences, 37, 152–155. https://doi.org/10.3969/j.issn.1672-7347.2012.02.007 [Google Scholar]
  35. Sisay, T., Tesfaye, K., Ketema, M., Dechassa, N., & Getnet, M. (2023). Climate-Smart Agriculture Technologies and Determinants of Farmers’ Adoption Decisions in the Great Rift Valley of Ethiopia. Sustainability, 15(4), 3471. https://doi.org/10.3390/su15043471 [Google Scholar]
  36. Van Asseldonk, M., Girvetz, E., Pamuk, H., Wattel, C., & Ruben, R. (2023). Policy incentives for smallholder adoption of climate-smart agricultural practices. Frontiers in Political Science, 5, 1112311. https://doi.org/10.3389/fpos.2023.1112311 [Google Scholar]
  37. Venkat, M. (2021). AI for Accelerating Evergreen Revolution. SourceTrace. Available online: https://www.sourcetrace.com/wp-content/themes/sts-v3/img/media/agriculture-today-may-2021.pdf (accessed on 16 January 2024). [Google Scholar]
  38. Venkatramanan, V., & Shah, S. (2019). Climate Smart Agriculture Technologies for Environmental Management: The Intersection of Sustainability, Resilience, Wellbeing and Development. In S. Shah, V. Venkatramanan, & R. Prasad (Eds.), Sustainable Green Technologies for Environmental Management (pp. 29–51). Springer. https://doi.org/10.1007/978-981-13-2772-8_2 [Google Scholar]
  39. Widiyanti, E., Karsidi, R., Wijaya, M., & Utari, P. (2021). Information Needs and Behaviour for Sustainable Farming Among Millennial and Progressive farmers. IOP Conference Series: Earth and Environmental Science, 828(1), 1-6. https://doi.org/10.1088/1755-1315/828/1/012052 [Google Scholar]
  40. Yegbemey, R. N., Aloukoutou, A. M., & Aihounton, G. B. D. (2020). Impact Pathways of Weather Information for Smallholder Farmers: A Qualitative ex ante Analysis. Africa Development / Afrique et Développement, 45(4), 133–156. [Google Scholar]
  41. Zhang, Y., Wang, L., & Duan, Y. (2016). Agricultural information dissemination using ICTs: A review and analysis of information dissemination models in China. Information Processing in Agriculture, 3(1), 17–29. https://doi.org/10.1016/j.inpa.2015.11.002 [Google Scholar]
Article Statistics

Usage statistics will be available soon.

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Ajwang, S., Owoche, P., & Mutonyi, J. (2024). Access and Use of Information for Enhanced Adoption of Climate Smart Agricultural Practices among Smallholder Farmers in Lake Victoria Basin, Kenya. AgroEnvironmental Sustainability, 2(2), 62-73. https://doi.org/10.59983/s2024020201

Search author on: PubMed | Google Scholar

Similar Articles

1-10 of 67

You may also start an advanced similarity search for this article.