Food Science and Agriculture: Research Highlights Vol. 11

Digital cold chains are increasingly expected to manage the condition of individual products rather than merely document refrigerated transport. Their practical value nevertheless depends on several transitions that are often evaluated separately: from environmental measurements to biological condition, from condition to remaining shelf life, and from prediction to an executable logistics decision. This critical narrative review integrates evidence on product-associated sensing, predictive microbiology, quality kinetics, machine learning, digital twins and first-expire-first-out allocation. Literature eligible through 27 July 2026 was identified through targeted searches of open scholarly indexes, institutional sources and citation networks. Studies were appraised according to measurement validity, independence of validation, uncertainty treatment and the distinction between simulated and observed operational outcomes. Temperature histories can reveal otherwise hidden exposure differences, but ambient measurements do not necessarily represent product temperature, and temperature alone cannot reconstruct initial quality, contamination or pre-harvest susceptibility. Chemical indicators and imaging provide complementary observations, although freshness classification and elapsed-storage prediction should not be mistaken for prospective shelf-life validation. Digital twins offer a useful structure for combining these observations with mechanistic knowledge, but thermal accuracy does not establish biological accuracy or prove waste reduction. Remaining shelf life is best treated as an endpoint-specific distribution conditional on future handling, with food safety maintained as a separate eligibility constraint. First-expire-first-out logistics therefore requires destination compatibility, demand information, operational capacity and timely intervention, not simply an ascending list of predicted expiry dates. Evidence for sensing and modelling is more developed than evidence for sustained, causally attributable reductions in commercial food waste. The review proposes a decision-centred validation sequence linking representative sensing, prospective biological prediction, feasible allocation and independently measured system outcomes. Priority should be given to comparative field trials, uncertainty-aware decisions, interoperable product histories and net environmental and economic evaluation before increasingly complex systems are deployed at scale.