Food cold chain management improvement: A conjoint analysis on COVID-19 and food cold chain systems

Abstract

Cold chains are effective in maintaining food quality and reducing food losses, especially for long-distance international food commerce. Several recent reports have demonstrated that frozen foods are serving as carriers of SARS-CoV-2 and transmitting the virus from one place to another without any human-to-human contact. This finding highlights significant difficulties facing efforts to control the spread of COVID-19 and reveal a transmission mechanism that may have substantially worsened the global pandemic. Traditional food cold chain management practices do not include specific procedures related to SARS-CoV-2-related environmental control and information warnings; therefore, such procedures are urgently needed to allow food to be safely transported without transmitting SARS-CoV-2. In this study, a conjoint analysis of COVID-19 and food cold chain systems was performed, and the results of this analysis were used to develop an improved food cold chain management system utilizing internet of things (IoT) and blockchain technology. First, 45 COVID-19-related food cold chain incidents in China, primarily involving frozen meat and frozen aquatic products, were summarized. Critical food cold chain control points related to COVID-19 were analyzed, including temperature and cold chain requirements. A conceptual system structure to improve food cold chain management, including information sensing, chain linking and credible tracing, was proposed. Finally, a prototype system, which consisted of cold chain environment monitoring equipment, a cold chain blockchain platform, and a food chain management system, was developed. The system includes: 1) a defining characteristic of the newly developed food cold chain system presented here is the use of IoT technology to enhance real-time environmental information sensing capacity; 2) a hybrid data storage mechanism consisting of off-chain and on-chain systems was applied to enhance data security, and smart contracts were used to establish warning levels for food cold chain incidents; and 3) a hypothetical food cold chain failure scenario demonstration in which information collection, intelligent decision making, and cold chain tracing were integrated and automatically generated for decision-making. By integrating existing technologies and approaches, our study provides a novel solution to improve traditional food cold chain management and thus meet the challenges associated with the COVID-19 pandemic. Although our system has been shown to be effective, subsequent studies are still required to develop precise risk evaluation models for SARs-CoV-2 in food cold chains and more precisely control the entire process. By ensuring food safety and reliable traceability, our system could also contribute to the formulation of appropriate mechanisms for international cooperation and minimize the effect of the COVID-19 pandemic on international food commerce.