Dynamic shelf life: a new concept and direction for the 22nd-century poultry processing industry

Abstract Poultry meat and eggs are highly perishable, yet their shelf life is still communicated through fixed dates that assume ideal storage conditions. Because the actual temperature, packaging, and handling history differs from one package to the next, a fixed date can overstate the quality of an abused product or force the disposal of one that is still safe and wholesome. This Comment proposes dynamic shelf life as a guiding direction for the poultry processing industry: the remaining shelf life of each product is estimated continuously from its measured condition and history rather than assigned once at packaging. The proposed framework links four layers. First, multimodal sensing during processing records the initial quality of carcasses, meat cuts, and eggs. Second, flexible smart-packaging sensors extend monitoring through cold storage, transportation, retail, and the household by tracking temperature, humidity, headspace gases, and spoilage volatiles. Third, explainable machine learning converts these data into freshness scores and remaining-shelf-life estimates that processors, retailers, and regulators can interpret and verify. Fourth, digital twins integrate this data stream into continuously updated virtual representations of products, batches, and cold chains, supporting decisions on stock rotation, routing, and discounting. Realizing this vision will require progress on sensor reliability and cost, validation under commercial conditions, evaluation of explanations and uncertainty, data governance, and regulatory acceptance. Through interdisciplinary collaboration, dynamic shelf life could make poultry supply chains safer, less wasteful, and more transparent while keeping human decision-makers at the center.