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September 25, 2025Journal of Information and TechnologyOpen Access

AI-Driven Precision Agriculture for Smallholder Farmers in Rwanda: A Case Study in Kayonza District

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Authors

JNJonathan NturoUniversity of Lay Adventists of KigaliDSDjuma SumbiriUniversity of Lay Adventists of KigaliJNJonathan Ngugi

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Implication

Research demonstrates improved crop yield prediction and resilience in smallholder farming, indicating broader implications for sustainable agriculture.

Key Points

  • The study shows robust yield predictions with an R² of 0.83, highlighting key determinants like soil moisture and rainfall anomalies.
  • Integration of AI and IoT technologies enhanced drought monitoring and improved risk management strategies for farmers in Rwanda.
  • Field trials of the Tekana Bundled Plus product indicated successful delivery of crop and livestock insurance with mobile advisory services.
  • The findings emphasize scalable AI applications in agriculture, promoting sustainable practices and improved livelihoods for smallholder farmers.

Cite This Study

Nturo et al. (2025) studied this question.

synapsesocial.com/papers/68d5bd69dc445aa9033b05a8https://doi.org/10.70619/vol5iss9pp28-45
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