Hierarchical network modeling with multidimensional information for aquatic safety management in the cold chain

Abstract

The cold‐chain information has characterized by the loss and dispersion according to the different collecting methods. The description for the quality decay factors of aquatic products can be defined as the multidimensional information. A series of nodes with multidimensional information are assembled to be hierarchies aiming at describing the environment conditions and locations in the supply chain. Each of the single hierarchy levels constitutes a sequence of node information in a network, which is applied as internal information analysis. The cross‐layer information structure is defined as “bridge” information which is able to record the information transmissions among every hierarchy from the point of view of the whole chain. The study has established a novel structured modeling to describe the cold chain of aquatic products based on a network‐hierarchy framework. An organized and sustainable transmission process can be built and recorded by the multidimensional attributes for the whole course of cold chain of aquatic products. In addition, seamless connections among every hierarchy are attainable by the environmental information records continuously to monitor the quality of aquatic products. The quality assessments and shelf life predictions are estimated properly as the risk control in order to monitor and trace the safety of aquatic products under the supply chain perspective.

Sustainable food cold chain logistics: From microenvironmental monitoring to global impact

“…The sustainable environmental control of cold storage can be achieved by predicting future temperature and power demand disturbances due to demand response (Hoang et al., 2021). In addition, by combining real‐time environmental monitoring IoT with an early risk warning decision support system, food loss can be controlled with high sustainability (Liu et al., 2018; Tsang, Choy, Wu, Ho, Lam, & Koo, 2018). By integrating IoT with notification systems, and by using forward propagation ANNs to classify the status of fresh products (e.g., good, unsatisfactory, alert), staff members can be notified to complete precontrol operations (Afreen & Bajwa, 2021).…”