Digitalization pathways for food loss and waste prevention in agri-food supply chains: Current evidence, challenges and future directions

Background Food loss and waste (FLW) remains a major challenge for global agri-food systems, generating substantial environmental, economic, and social impacts. Digitalization has emerged as a promising strategy to improve resource efficiency and support FLW prevention, yet the effectiveness of different digital technologies remains uneven and often insufficiently evaluated. Scope and approach This critical review examines the contribution of Industry 4.0 and Agriculture 4.0 technologies, including the Internet of Things (IoT), artificial intelligence (AI), big data analytics, blockchain, and consumer-oriented digital platforms, to FLW prevention across the entire agri-food supply chain. Rather than cataloguing technological applications, the review critically distinguishes between demonstrated reductions in FLW and improvements in technical performance that are frequently assumed to translate into waste prevention, while evaluating technological maturity, implementation barriers, and future research priorities. Key findings and conclusions IoT-enabled monitoring and smart logistics provide the strongest direct evidence for reducing spoilage risks; among AI applications, inventory management is comparatively well supported, although much of the broader AI/ML evidence remains based on operational proxies. Evidence for blockchain applications, dynamic pricing, and consumer-facing technologies remains limited or highly context dependent. Persistent barriers include fragmented data infrastructures, interoperability constraints, unequal digital capabilities, uncertain economic returns, and rebound effects. Digital technologies can contribute meaningfully to FLW prevention only when integrated with organizational, behavioural, and governance strategies. Future research should prioritize standardized impact metrics, longitudinal system-level evaluations, and integrated environmental assessments capable of quantifying real reductions in FLW and associated sustainability trade-offs.

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Publication Details

Journal
Trends in Food Science & Technology
Published
2026-09-12
DOI
https://doi.org/10.1016/j.tifs.2026.106084
Primary Topic
Food Waste Reduction and Sustainability
Type
article
Field-Weighted Citation Impact
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article

Digitalization pathways for food loss and waste prevention in agri-food supply chains: Current evidence, challenges and future directions

Ana S. Ramírez, Conrado Carrascosa, Mona N. BinMowyna, António Raposo et al.
Trends in Food Science & Technology
Food Waste Reduction and Sustainability
article

Digitalization pathways for food loss and waste prevention in agri-food supply chains: Current evidence, challenges and future directions

Ana S. Ramírez, Conrado Carrascosa, Mona N. BinMowyna, António Raposo, Hani A. Alfheeaid, Ariana Saraiva, Esther Sanjuán Velázquez, José Raduán Jáber, Esteban Pérez-García
article en

Abstract

Background Food loss and waste (FLW) remains a major challenge for global agri-food systems, generating substantial environmental, economic, and social impacts. Digitalization has emerged as a promising strategy to improve resource efficiency and support FLW prevention, yet the effectiveness of different digital technologies remains uneven and often insufficiently evaluated. Scope and approach This critical review examines the contribution of Industry 4.0 and Agriculture 4.0 technologies, including the Internet of Things (IoT), artificial intelligence (AI), big data analytics, blockchain, and consumer-oriented digital platforms, to FLW prevention across the entire agri-food supply chain. Rather than cataloguing technological applications, the review critically distinguishes between demonstrated reductions in FLW and improvements in technical performance that are frequently assumed to translate into waste prevention, while evaluating technological maturity, implementation barriers, and future research priorities. Key findings and conclusions IoT-enabled monitoring and smart logistics provide the strongest direct evidence for reducing spoilage risks; among AI applications, inventory management is comparatively well supported, although much of the broader AI/ML evidence remains based on operational proxies. Evidence for blockchain applications, dynamic pricing, and consumer-facing technologies remains limited or highly context dependent. Persistent barriers include fragmented data infrastructures, interoperability constraints, unequal digital capabilities, uncertain economic returns, and rebound effects. Digital technologies can contribute meaningfully to FLW prevention only when integrated with organizational, behavioural, and governance strategies. Future research should prioritize standardized impact metrics, longitudinal system-level evaluations, and integrated environmental assessments capable of quantifying real reductions in FLW and associated sustainability trade-offs.

Trends in Food Science & TechnologyVol. 178
Universidad de Las Palmas de Gran Canaria (ES), Qassim University (SA), Shaqra University (SA), Technologies pour la Santé (FR), Universidade Lusófona (PT)
Decent work and economic growth
Openalex Percentile: Top 13%
Food Waste Reduction and Sustainability
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