Improving continuous traceability of food stuff by using barcode-RFID bidirectional transformation equipment: Two field experiments

Design of agricultural product traceability system based on blockchain and RFID

Ensuring the traceability of agricultural products is essential for quality control and food safety. Recent technological advances have provided new ways to enhance traceability systems. This study aims to use blockchain technology, centralized database and RFID tags to develop a secure agricultural product traceability system, retain the detailed information of agricultural products traceability, ensure that the summary information of agricultural products on the chain cannot be modified, and optimize the SM3 algorithm to effectively summarize the traceability data and improve the efficiency of the system. The aggregated data is time-stamped, recorded on the blockchain, and written into an RFID tag. The optimization of the SM3 algorithm improved the efficiency by 30% and reduced the execution time of 192-byte messages to 210µs. The system ensures accurate linking of traceability data through secure data retention and unalterable summaries on the blockchain. The integrated use of blockchain, centralized database and RFID technology, as well as the enhanced SM3 algorithm, allows the system to meet the standards for data accuracy and performance requirements in agricultural traceability applications.

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.

Investigating the characteristics of fluorescence features on sweet peppers using UV light excitation

Sweet peppers are popular worldwide due to their nutrition and taste. Conventional vegetable tracing methods have been trialed, but the application of such labels or tags can be laborious and expensive, making their commercial application impractical. What is needed is a label-free method that can identify features unique to each individual fruit. Our research team has noted that sweet peppers have unique textural fluorescence features when observed under UV light that could potentially be used as a label-free signature for identification of individual fruit as it travels through the postharvest supply chain. The objective of this research was to assess the feature of these sweet pepper features for identification purposes. The macroscopic and microscopic images were taken to characterize the fluorescence. The results indicate that all sweet peppers possess dot-like fluorescence features on their surface. Furthermore, it was observed that 93.60% of these features exhibited changes in fluorescence intensity within the cuticle layer during the growth of a pepper. These features on the macro-image are visible under 365 nm UV light, but challenging to be seen under white LEDs and to be classified from the fluorescence spectrum under 365 nm light. This research reported the fluorescence feature on the sweet pepper, which is invisible under white light. The results show that the uniqueness of fluorescent features on the surface of sweet peppers has the potential to become a traceability technology due to the presence of its unique physical modality.

Towards circular economy in the textiles and clothing value chain through blockchain technology and IoT: A review

The textile and clothing industry sector has today a big environmental impact, not only due to the consumption of water and the use of toxic chemicals but also due to the increasing levels of textile waste. One way to reduce the problem is to circularise the, currently linear, textile and clothing value chain, by using discarded clothes as raw material for the production of new clothes, transforming it into a model of circular economy. This way, while reducing the need to produce new raw materials (e.g. cotton), the problem of textile waste produced is also reduced, thus contributing to a more sustainable industry. In this article, we review the current approaches for traceability in the textile and clothing value chain, and study a set of technologies we deem essential for promoting the circular economy in this value chain - namely, the blockchain technology - for registering activities on traceable items through the value chain, and the Internet of Things (IoT) technology, for easily identifying the traceable items' digital twins.

A Hybrid Traceability Technology Selection Approach for Sustainable Food Supply Chains

Traceability technologies have great potential to improve sustainable performance in cold food supply chains by reducing food loss. In existing approaches, traceability technologies are selected either intuitively or through a random approach, that neither considers the trade-off between multiple cost–benefit technology criteria nor systematically translates user requirements for traceability systems into the selection process. This paper presents a hybrid approach combining the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with integer linear programming to select the optimum traceability technologies for improving sustainable performance in cold food supply chains. The proposed methodology is applied in four case studies utilising data collected from literature and expert interviews. The proposed approach can assist decision-makers, e.g., food business operators and technology companies, to identify what combination of technologies best suits a given food supply chain scenario and reduces food loss at minimum cost.

Informative and corrective responsive packaging: Advances in farm-to-fork monitoring and remediation of food quality and safety

Microbial growth and fluctuations in environmental conditions have been shown to cause microbial contamination and deterioration of food. Thus, it is paramount to develop reliable strategies to effectively prevent the sale and consumption of contaminated or spoiled food. Responsive packaging systems are designed to react to specific stimuli in the food or environment, such as microorganisms or temperature, then implement an informational or corrective response. Informative responsive packaging is aimed at continuously monitoring the changes in food or environmental conditions and conveys this information to the users in real time. Meanwhile, packaging systems with the capacity to control contamination or deterioration are also of great interest. Encouragingly, corrective responsive packaging attempting to mitigate the adverse effects of condition fluctuations on food has been investigated. This packaging exerts its effects through the triggered release of active agents by environmental stimuli. In this review, informative and corrective responsive packaging is conceptualized clearly and concisely. The mechanism and characteristics of each type of packaging are discussed in depth. This review also summarized the latest research progress of responsive packaging and objectively appraised their advantages. Evidently, the mechanism through which packaging systems respond to microbial contamination and associated environmental factors was also highlighted. Moreover, risk concerns, related legislation, and consumer perspective in the application of responsive packaging are discussed as well. Broadly, this comprehensive review covering the latest information on responsive packaging aims to provide a timely reference for scientific research and offer guidance for presenting their applications in food industry.

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.

Radio Frequency IDentification for Meat Supply-Chain Digitalisation

Digitalised supply-chain traceability systems can offer wide prospects both for improving safety as well as enhancing perceived quality. However, the coupling between physical goods and information is often difficult for agri-food items. A solution could be the use of RFID (Radio Frequency IDentification) systems. Due to its wide reading range, Ultra-High Frequency (UHF) technology is already widely used in logistics and warehousing, mostly for the identification of batches of items. A growing interest is also emerging in Near Field Communication (NFC), as several smartphones embed an integrated NFC antenna. This paper deals with the automatic identification of meat products at item level, proposing and evaluating the adoption of different RFID technologies. Different UHF and NFC solutions are proposed, which benchmark tag performances in different configurations, including four meat types (fatty beef, lean beef, chicken and pork), by using a specifically designed test bench. As avoiding the application of two different tags could be advantageous, dual frequency devices (UHF and NFC) are also considered. Significant differences in tag performances, which also depend on meat type and packaging, are highlighted. The paper highlights that tag positioning should consider the geometry of the packaging and the relative positioning of tag, meat and reader antenna.

IoT Platform for Seafood Farmers and Consumers

There has been a strong growth in aquatic products supported by the global seafood industry. Consumers demand information transparency to support informed decisions and to verify nutrition, food safety, and sustainable operations. Supporting these needs rests on the existence of interoperable Internet of Things (IoT) platforms for traceability that goes beyond the minimum "one up, one down" scheme required by regulators. Seafood farmers, being the source of both food and food-information, are critical to achieving the needed transparency. Traditionally, seafood farmers carry the costs of providing information, while downstream actors reap the benefits, causing limited provision of information. Now, global standards for labelling, data from IoT devices, and the reciprocity of utility from collecting data while sharing them represent great potential for farmers to generate value from traceability systems. To enable this, farmers need an IoT platform integrated with other IoT platforms in the value network. This paper presents a case study of an enterprise-level IoT platform for seafood farmers that satisfies consumers' end-to-end traceability needs while extracting data from requests for information from downstream actors.

A Novel Visual Analysis Method of Food Safety Risk Traceability Based on Blockchain

Current food traceability systems have a number of problems, such as data being easily tampered with and a lack of effective methods to intuitively analyze the causes of risks. Therefore, a novel method has been proposed that combines blockchain technology with visualization technology, which uses Hyperledger to build an information storage platform. Features such as distribution and tamper-resistance can guarantee the authenticity and validity of data. A data structure model is designed to implement the data storage of the blockchain. The food safety risks of unqualified detection data can be quantitatively analyzed, and a food safety risk assessment model is established according to failure rate and qualification deviation. Risk analysis used visual techniques, such as heat maps, to show the areas where unqualified products appeared, with a migration map and a force-directed graph used to trace these products. Moreover, the food sampling data were used as the experimental data set to test the validity of the method. Instead of difficult-to-understand and highly specialized food data sets, such as elements in food, food sampling data for the entire year of 2016 was used to analyze the risks of food incidents. A case study using aquatic products as an example was explored, where the results showed the risks intuitively. Furthermore, by analyzing the reasons and traceability processes effectively, it can be proven that the proposed method provides a basis to formulate a regulatory strategy for regions with risks.