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All Journal Agricultural Science
Enock Musau Gideon
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Agriculture, Biological Sciences & Forestry

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Journal : Agricultural Science

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Sustainable Agriculture Leveraging Artificial Intelligence Systems in Kenya's Agri-food Supply Chain: Leveraging Artificial Intelligence Systems in Kenya's Agri-food Supply Chain Enock Musau Gideon
Agricultural Science Vol. 7 No. 2 (2024): March
Publisher : Faculty of Agriculture, Merdeka University Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55173/agriscience.v7i2.128

Abstract

The Agro-food supply chain is crucial for achieving Sustainable Development Goal No. 2 of zero hunger and sustainable agriculture. However, Kenya faces significant post-harvest losses, mainly attributed to challenges in first and last-mile logistics. In the era of technological advancements, this research paper explores the potential of Artificial Intelligence (AI) to enhance the Kenyan agri-food supply chain. Building on existing information, the study focuses on AI's role in monitoring and controlling farmland outputs, optimizing supply chain logistics, and addressing fraud and counterfeiting. The research objectives include assessing AI's utility in monitoring and controlling outputs in farmlands improving supply chain efficiency, and combating fraud in agricultural inputs. Research methods involve a comprehensive literature review, analyzing case studies such as Project FARM and FAO's Fall Armyworm Monitoring and Early Warning System, and reviewing scholarly articles on AI applications in agriculture. The research results highlight the benefits of leveraging AI in farmland monitoring, climate change adaptation, supply chain logistics, and fraud prevention. AI technologies can enhance agricultural productivity, reduce transportation costs, and eliminate corruption in the supply chain. The findings suggest that integrating AI systems into the agri-food supply chain is vital for achieving sustainable agriculture in Kenya. The study concludes that AI offers innovative solutions to address the challenges faced by smallholder farmers, enhance supply chain efficiency, and contribute to achieving zero hunger and sustainable agricultural practices.
Inventory Management as a Driver of Supply Chain Performance in Agricultural Value Chains: A Lean Theory Perspective from Kenya Enock Musau Gideon
Agricultural Science Vol. 9 No. 2 (2026): March In Progress
Publisher : Faculty of Agriculture, Merdeka University Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55173/agriscience.v9i2.185

Abstract

Inventory management is a critical supply chain practice with significant implications for supply chain performance, especially in agricultural value chains that face challenges of perishability, demand fluctuations, and resource constraints. Guided by Lean Theory, this study examined the effect of inventory management on supply chain performance within Kenya’s agricultural supply chains using a quantitative explanatory research design. Primary data were collected through a structured questionnaire administered to employees across agricultural directorates. Reliability analysis confirmed strong internal consistency (α = 0.743 for inventory management; α = 0.850 for supply chain performance). Principal component analysis validated construct measurement (KMO = 0.769, p < 0.001). Regression results showed that inventory management significantly and positively predicts supply chain performance (β = 0.265, t = 6.120, p < 0.001), highlighting its role as a key determinant of efficiency and competitiveness. The study concludes that inventory management practices such as vendor-managed inventory, just-in-time replenishment, and stock transparency are indispensable for enhancing supply chain performance in Kenya’s agricultural sector. It recommends that policymakers and managers invest in Lean-inspired inventory strategies to optimize resource use, reduce waste, and build resilient agricultural supply chains.
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