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Digital twins to map the key quality attributes in fresh-produce supply chains.

Des jumeaux numériques pour cartographier les principaux critères de qualité dans les chaînes d'approvisionnement de produits frais.

Numéro : 292336



The supply chains of several heat-sensitive biological products, such as vaccines and fresh horticultural produce, require refrigerated storage and transport of the product. Low temperatures reduce the rate of several temperature-driven biochemical degradation reactions, thereby preserving the quality of these perishable products. However, every single refrigerated shipment is unique and encounters a distinct cooling history, including suboptimal temperature deviations, which manifest themselves as a unique quality evolution. This introduces a large variability in end-product quality for the consumer, which complicates logistics and can increase product losses. Digital twins can map this currently uncharted quality evolution. A digital twin is a virtual model of a heat-sensitive biological product in a cold chain, in which all relevant biophysical transport processes are simulated. The twin is linked to the real fruit by monitored environmental parameters in the real cold chain (such as cooling air temperature and humidity). The present study employs the citrus cold chain as a case study for digital twinning, to demonstrate in-silico the variability in quality evolution between different citrus shipments from South Africa to the Netherlands. We also identify trade-offs between a comprehensive set of quality attributes such as biochemical degradation reactions, mass loss, low temperature-induced chilling injury, and phytosanitary mortality of pests. Our results provide essential insights into the variability in the remaining shelf life days for the different shipments, which varied between 8 and 10 days. Furthermore, the risk of chilling injury and condensation was predicted for these shipments. This information is indispensable for multiple stakeholders in the refrigerated supply chain. They can use this information for better decision-making in planning logistics and dynamically adjusting pricing. Additionally, these findings can help prolong the shelf life and minimize variability in end-product quality, thereby reducing product losses and the associated loss of embodied energy in these cold chains.

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Pages : 9


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Version PowerPoint

Pages : 22




  • Titre original : Digital twins to map the key quality attributes in fresh-produce supply chains.
  • Identifiant de la fiche : 30027567
  • Langues : Anglais
  • Sujet : Technologie
  • Source : 6th IIR International Conference on Sustainability and the Cold Chain. Proceedings: Nantes, France, August 26-28 2020
  • Date d'édition : 26/08/2020
  • DOI : http://dx.doi.org/10.18462/iir.iccc.2020.292336
  • Disponible à la bibliothèque de l'IIF


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