Post-Harvest Intelligence for Reducing Food Loss in Decentralized Markets

Neeraj Verma

Post-Harvest Intelligence for Reducing Food Loss in Decentralized Markets

Author(s)	Dr. Neeraj Verma
Country	United States
Abstract	Post-harvest food loss remains a persistent constraint on food availability, farmer income, market efficiency, and resource sustainability, particularly in decentralized food systems characterized by small farms, fragmented trading networks, informal wholesale markets, limited cooling infrastructure, variable transportation conditions, and incomplete information about product quality and demand. Conventional post-harvest management frequently responds to visible deterioration only after substantial quality loss has already occurred. Post-harvest intelligence offers a different approach by combining measurement, sensing, shelf-life estimation, market information, storage conditions, logistics data, and decision support to identify deterioration risks before products become unsalable. This conceptual review examines how post-harvest intelligence can reduce food loss in decentralized markets through affordable and context-appropriate digital and physical infrastructure. Current FAO information indicates that approximately 13.2% of food is lost globally after harvest and before retail, demonstrating that substantial food-system value is lost before products reach consumers. The paper synthesizes recent evidence concerning Internet of Things sensors, artificial intelligence, digital twins, smart cold chains, solar-powered decentralized cooling, quality monitoring, grain-storage technologies, market information, and smallholder adoption. Particular attention is given to the distinction between collecting data and creating actionable intelligence. A temperature sensor has limited value unless its measurements influence storage, routing, pricing, or selling decisions. Similarly, artificial intelligence becomes useful only when predictions can be converted into practical action within the limited time and financial resources available to decentralized market actors. A 2025 digital twin study demonstrated simulated food-loss reductions of 8.6% for strawberries, 12.1% for lychees, 13.6% for oranges, and 15.5% for apples through improved temperature and remaining-shelf-life intelligence. Evidence from 1,001 smallholder vegetable farmers in Ghana further shows the importance of access and usability: farmers reported average post-harvest losses of 25%, while 79% expressed willingness to adopt solar-powered cold storage, despite limited access to post-harvest training and extension services. The study concludes that effective post-harvest intelligence should be decentralized, affordable, interoperable, commodity-sensitive, and directly connected with decisions concerning harvest timing, cooling, storage, sorting, transport, market selection, and product prioritization. Technology should therefore function as a decision-support layer within local food markets rather than as an isolated digital intervention.
Keywords	: Post-harvest intelligence; food loss; decentralized markets; smart cold chain; shelf-life prediction; Internet of Things; artificial intelligence; smallholder agriculture; solar cold storage; market information
Field	Engineering
Published In	Volume 2, Issue 3, May-June 2021
Published On	2021-05-30

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American Journal of Advanced Multidisciplinary Innovation and Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Post-Harvest Intelligence for Reducing Food Loss in Decentralized Markets

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