A real-time agro-food authentication and supervision system on a novel code for improving traceability credibility

Intelligent System/Equipment for Quality Deterioration Detection of Fresh Food: Recent Advances and Application

The quality of fresh foods tends to deteriorate rapidly during harvesting, storage, and transportation. Intelligent detection equipment is designed to monitor and ensure product quality in the supply chain, measure appropriate food quality parameters in real time, and thus minimize quality degradation and potential financial losses. Through various available tracking devices, consumers can obtain actionable information about fresh food products. This paper reviews the recent progress in intelligent detection equipment for sensing the quality deterioration of fresh foods, including computer vision equipment, electronic nose, smart colorimetric films, hyperspectral imaging (HSI), near-infrared spectroscopy (NIR), nuclear magnetic resonance (NMR), ultrasonic non-destructive testing, and intelligent tracing equipment. These devices offer the advantages of high speed, non-destructive operation, precision, and high sensitivity.

How can blockchain technology promote food safety in agricultural market?-an evolutionary game analysis

The governance of agricultural food safety issues is closely linked to social interests. To promote food safety supervision in the Chinese agricultural markets under the background of blockchain application, this paper develops a partnership comprising vendors, consumers, and the government. Using the theory of evolutionary game combined with the actual situation of China, the evolutionary process simulations of three participants prove that the tripartite subjects can realize a stable state under the specific relationship. Impact investigation results of typical influential factors indicate the following: (1) The behavior of vendors depends on the government's supervision and consumers' reporting attitude. Limiting the penalty amount for vendors to 66.7% of speculative gains can shorten the processing time for vendors to comply with the law. (2) Consumers play a vital role in food safety supervision of the agricultural market. The penalty for consumers should be limited to 1/3 of the reward amount. (3) The government's incentive-oriented and punishment-inhibited policies can promote blockchain technology in supervision. Punishment-inhibited and key influencing parameters can cooperate in obtaining the maximum regulatory benefits. The results of this study have certain reference values for promoting policy formulation and implementing blockchain technology in agricultural food safety supervision.

Green Agricultural Products Supply Chain Subsidy Scheme with Green Traceability and Data-Driven Marketing of the Platform

Government subsidies have played an important role in the development of green agriculture. In addition, the Internet platform is becoming a new channel to realize green traceability and promote the sale of agricultural products. In this context, we consider a two-level green agricultural products supply chain (GAPSC) consisting of one supplier and one Internet platform. The supplier makes green R&D investments to produce green agricultural products along with conventional agricultural products, and the platform implements green traceability and data-driven marketing. The differential game models are established under four government subsidy scenarios: no subsidy (NS), consumer subsidy (CS), supplier subsidy (SS), and supplier subsidy with green traceability cost-sharing (TSS). Then, the optimal feedback strategies under each subsidy scenario are derived using Bellman's continuous dynamic programming theory. The comparative static analyses of key parameters are given, and the comparisons among different subsidy scenarios are conducted. Numerical examples are employed to obtain more management insights. The results show that the CS strategy is effective only if the competition intensity between two types of products is below a certain threshold. Compared to the NS scenario, the SS strategy can always improve the supplier's green R&D level, the greenness level, market demand for green agricultural products, and the system's utility. The TSS strategy can build on the SS strategy to further enhance the green traceability level of the platform and the greenness level and demand for green agricultural products due to the advantage of the cost-sharing mechanism. Accordingly, a win-win situation for both parties can be realized under the TSS strategy. However, the positive effect of the cost-sharing mechanism will be weakened as the supplier subsidy increases. Moreover, compared to three other scenarios, the increase in the environmental concern of the platform has a more significant negative impact on the TSS strategy.

Impact of food safety supervision efficiency on preventing and controlling mass public crisis

Food safety has received unprecedented attention since the COVID-19 outbreak. Exploring food safety regulatory mechanisms in the context of cluster public crises is critical for COVID-19 prevention and control. As a result, using data from a food safety regulation survey in the Bei-jing-Tianjin-Hebei urban cluster, this paper investigates the impact of food safety regulation on the prevention and control of COVID-19. The study found that food safety regulation and cluster public crisis prevention and control have a significant positive relationship, with the ability to integrate regulatory resources acting as a mediator between the two. Second, industry groups argue that the relationship between regulatory efficiency and regulatory resource integration should be moderated in a positive manner. Finally, industry association support positively moderates the mediating role of regulatory re-source integration capacity between food safety regulatory efficiency and cluster public crises, and there is a mediating effect of being moderated. Our findings shed light on the mechanisms underlying the roles of regulatory efficiency, resource integration capacity, and industry association support in food safety, and they serve as a useful benchmark for further improving food safety regulations during the COVID-19 outbreak.

Traceability in food processing: problems, methods, and performance evaluations-a review

Processed food has become an indispensable part of the human food chain. It provides rich nutrition for human health and satisfies various other requirements for food consumption. However, establishing traceability systems for processed food faces a different set of challenges compared to primary agro-food, because of the variety of raw materials, batch mixing, and resource transformation. In this paper, progress in the traceability of processed food is reviewed. Based on an analysis of the food supply chain and processing stage, the problem of traceability in food processing results from the transformations that the resources go through. Methods to implement traceability in food processing, including physical separation in different lots, defining and associating batches, isotope analysis and DNA tracking, statistical data models, internal traceability system development, artificial intelligence (AI), and blockchain-based approaches are summarized. Traceability is evaluated based on recall effects, TRUs (traceable resource units), and comprehensive granularity. Different methods have different advantages and disadvantages. The combined application of different methods should consider the specific application scenarios in food processing to improve granularity. On the other hand, novel technologies, including batch mixing optimization with AI, quality forecasting with big data, and credible traceability with blockchain, are presented in the context of improving traceability performance in food processing.

Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing

In the last decade, the use of multivariate statistical techniques developed for analytical chemistry has been adopted widely in food science and technology. Usually, chemometrics is applied when there is a large and complex dataset, in terms of sample numbers, types, and responses. The results are used for authentication of geographical origin, farming systems, or even to trace adulteration of high value-added commodities. In this article, we provide an extensive practical and pragmatic overview on the use of the main chemometrics tools in food science studies, focusing on the effects of process variables on chemical composition and on the authentication of foods based on chemical markers. Pattern recognition methods, such as principal component analysis and cluster analysis, have been used to associate the level of bioactive components with in vitro functional properties, although supervised multivariate statistical methods have been used for authentication purposes. Overall, chemometrics is a useful aid when extensive, multiple, and complex real-life problems need to be addressed in a multifactorial and holistic context. Undoubtedly, chemometrics should be used by governmental bodies and industries that need to monitor the quality of foods, raw materials, and processes when high-dimensional data are available. We have focused on practical examples and listed the pros and cons of the most used chemometric tools to help the user choose the most appropriate statistical approach for analysis of complex and multivariate data.