Building blocks for a digital twin of large cool store complexes

Digital twins are virtual representations that serve as real-time digital counterparts of physical objects spanning their full lifecycle. In the context of postharvest horticulture, these represent infrastructure (storage plants including refrigeration and controlled atmosphere systems) and the produce being handled (fruit and vegetables). The aim of the digital twin is to be used in real-time to support decision-making throughout the logistic handling chain, considering targets for, among others, product quality, food losses, energy use, emissions, and costs. Working with biological produce involves accounting for the inevitable biological variance, but also uncertainty exists in terms of unforeseen temporal and spatial variations within cold rooms. This contribution will present a review of the state of the art of models that can be used for the digital twin for large cool store complexes, including fully resolved as well as reduced order models of heat and mass transfer, as well as kinetics models while addressing issues with uncertainty propagation at both the theoretical and applied levels. Challenges and solutions for sensor-digital twin integration are discussed.