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Smart Postharvest Management: Leveraging AI for Reduced Food Loss, Waste, and Improved Quality

Author

Listed:
  • Blessing Iyanuoluwa Adediran

    (Perishable Crops Research Department, Nigerian Stored Products Research Institute (NSPRI) Ilorin, Kwara State, Nigeria)

  • Akudo Francilia Onyegbula

    (Perishable Crops Research Department, Nigerian Stored Products Research Institute (NSPRI) Ilorin, Kwara State, Nigeria)

  • Stephen Olufemi Oyeyipo

    (Perishable Crops Research Department, Nigerian Stored Products Research Institute (NSPRI) Ilorin, Kwara State, Nigeria)

  • Tawakalitu Ahmed

    (Perishable Crops Research Department, Nigerian Stored Products Research Institute (NSPRI) Ilorin, Kwara State, Nigeria)

  • Titilope Abosede Fashanu

    (Perishable Crops Research Department, Nigerian Stored Products Research Institute (NSPRI) Ilorin, Kwara State, Nigeria)

  • Damilola Olubunmi Ariyo

    (Perishable Crops Research Department, Nigerian Stored Products Research Institute (NSPRI) Ilorin, Kwara State, Nigeria)

Abstract

Food loss continues to be a major global challenge that impacts environmental sustainability, economic stability and food security. An inventive strategy for lowering food loss across the supply chain is AI-driven monitoring. The foundation of human civilization has always been agriculture, which supplies the vital resources needed for growth and nutrition. Higher quality crops with improved nutritional value, increased resilience to pests and diseases and improved adaptability to varying climatic conditions are in greater demand as the world's population continues to grow. Despite their effectiveness, traditional agricultural methods frequently fail to effectively meet these objectives; therefore, an innovative strategy for raising crop quality is the incorporation of artificial intelligence (AI) into agricultural operations. This paper examines the role of AI-driven monitoring in reducing food loss, focusing on its applications, benefits and implications for the food industry. AI driven technologies like machine learning, IoT-based smart sensors and computer vision can enhance efficiency in food production, storage, transportation and retail. By utilizing AI-driven solutions, stakeholders can optimize resource utilization, reduce waste, and contribute to sustainable food systems. AI-assisted processing can optimize various stages of crop production, from planting and growing to harvesting and postharvest management, thereby improving the overall quality of agricultural produce.

Suggested Citation

  • Blessing Iyanuoluwa Adediran & Akudo Francilia Onyegbula & Stephen Olufemi Oyeyipo & Tawakalitu Ahmed & Titilope Abosede Fashanu & Damilola Olubunmi Ariyo, 2025. "Smart Postharvest Management: Leveraging AI for Reduced Food Loss, Waste, and Improved Quality," Journal of Agriculture and Rural Development Studies, "Dunarea de Jos" University of Galati, Doctoral Field Engineering and Management in Agriculture and Rural Development, issue 3, pages 5-16.
    • Handle: RePEc:ddj:ejards:y:2025:i:3:p:5-16
    DOI: https://doi.org/10.35219/jards.2025.3.01
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    References listed on IDEAS

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