A Framework for Enhancing Adoption of Mobile-based Surveillance for Crop Pest and Disease Management by Farmers in Kenya

Authors

  • Gordon Ouma Kisii University
  • Fredrick Mzee Awuor Kisii University
  • Cyprian Ratemo Makiya Mama Ngina University College
  • Paul Okanda United States International University, Kenya.

DOI:

https://doi.org/10.17700/jai.2024.15.1.700

Keywords:

digital solutions, surveillance technologies, incentive mechanisms, large-scale surveillance, mobile crowd-sensing

Abstract

Crop pests and diseases are ranked as some of the world’s leading threats to agricultural productivity. Though different digital solutions have been developed in the last decade to monitor and control biosecurity threats, their adoption in developing nations remain sluggish. The need to improve adoption of digital solutions prompted a review on the applicability of emerging digital solutions in large-scale surveillance of crop pest and diseases in developing nations. The study presents findings on key requirements for achieving digitized large-scale pest surveillance, fitness for purpose of common autonomous biosecurity surveillance technologies, and prospects of smartphones as alternative surveillance solution. Firstly, the research identified appropriateness of the solution, availability of supporting infrastructure and level of stakeholder involvement in solution formulation as some of the key determinants of digital solution adoption. Secondly, though most common autonomous biosecurity surveillance technologies are promising, their adoption in developing nations are limited by operational cost, legal requirements, required skillset, and operational environment among others. Thirdly, recent advancements in smartphones and wide spread ownership among farmers provide a unique opportunity for advancing Mobile Crowd-Sensing solutions in achieving large-scale pest surveillance. Lastly, we recommend designing an incentive mechanism to motivate farmers’ participation in MCS based surveillance solution.

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Published

2024-08-28

How to Cite

Ouma, G., Awuor, F. M., Makiya, C. R. ., & Okanda, P. . (2024). A Framework for Enhancing Adoption of Mobile-based Surveillance for Crop Pest and Disease Management by Farmers in Kenya. Journal of Agricultural Informatics, 15(1). https://doi.org/10.17700/jai.2024.15.1.700

Issue

Section

Journal of Agricultural Informatics