Traceability in a food supply chain: Safety and quality perspectives

Food Fraud Conceptualization: An Exploratory Study with Portuguese Consumers

Food fraud refers to deceptive practices conducted for economic gain, and incidents of such fraud are often reported in the media and scientific literature. However, little is known about how European consumers perceive food fraud. To address this gap, a study explored Portuguese consumers' knowledge and perceptions of food fraud using qualitative methods such as free word association and semi-structured interviews. For this research, 340 participants were recruited, providing 911 valid words, classified into categories, major categories, and dimensions. Differences between consumers' previous exposure to food fraud and sociodemographic characteristics were explored. Additionally, other thirty-six participants were selected and interviewed, following a semi-structured guide. Interviews were transcribed, coded, and analyzed using a thematic analysis procedure. The results suggest that Portuguese consumers view food fraud as a morally reprehensible deception and are aware of its causes and impacts. However, not all consumers know the different forms of food fraud or the types of products vulnerable to fraud. Among the most repeated words were "deception", "expiration date", and "falsification". Despite this food fraud awareness, most consumers believed they were not exposed to food fraud and stated that they do not conduct daily practices to reduce exposure to it. Following the chi-square and Mann-Whitney tests, significant differences (p ≤ 0.05) were identified between participants exposed and not exposed to food fraud. The study also found that consumers with higher education and self-reported exposure to food fraud had a better understanding of the issue. This study provides insights for quantitative research on consumer perceptions and beliefs about food fraud to explore further vulnerable food categories and types of food fraud in real-world scenarios.

The influence of traceability label trust on consumers' traceability pork purchasing behavior: Based on the moderating effect of food safety identification

Based on 908 consumer questionnaire data from 15 urban areas in Shanghai, we use the binary logit model to empirically analyze the impact of traceability label trust on consumers' traceable pork purchase behavior and the moderating effect of food safety identification. After constructing the theoretical analysis framework, this paper verifies it from the two aspects of statistical analysis and econometric analysis and tests the robustness of the final results. The results show that: first, traceability label trust has a significant positive impact on consumers' traceability pork behavior. Second, food safety identification can significantly strengthen and promote this process. Third, consumers' purchasing behavior is significantly positively affected by traceable pork consumption scenarios and price labels, but the permanent elderly in the composition of family members significantly negative impact on it. Therefore, we put forward relevant policy suggestions, such as strengthening the knowledge popularization and publicity based on the advantageous commodity attributes of traceable pork, carrying out food safety knowledge popularization education, and enhancing consumers' risk perception and food safety identification ability.

The complexities of decision-making in food waste valorization: A critical review

The efficient utilization of food waste (FW) resources through Food Waste Valorization (FWV) has received increasing attention in recent years. Various decision-making studies have been undertaken to facilitate FWV implementation, such as the studies on decision-making framework and FWV technology assessment. Food waste hierarchy is a widely discussed framework in FW management, but it was found too simplified and does not always contribute positively to environmental sustainability. Moreover, decision-making studies in FWV often focus on specific aspects of the food system and employ distinctive decision-making approaches, making it difficult to compare the results from different studies. Therefore, our literature review is conducted to provide a comprehensive understanding of FWV decision-making. This study identifies what decisions are needed, and three levels of decisions are revealed: system-level, FW stream-level, and FWV option-level. The assessment approaches and criteria used to support decision-making in FWV are also collected and analyzed. Building upon these findings, an hourglass model is synthesized to provide a holistic illustration of decision-making in FWV. This study untangles the complexities of FWV decision-making and sheds light on the limitations of current studies. We anticipate this study will make more people realize that FWV is a multidisciplinary issue and requires the collective participation of researchers, practitioners, policymakers, and consumers. Such collective engagement is essential to effectively address practical challenges and propel the transition of the current food system toward a more resource-efficient paradigm.

Kinetic models applied to quality change and shelf-life prediction of fresh-cut pineapple in food cold chain

This study developed a predictive model of the remaining shelf-life of fresh-cut pineapple by considering microbial, chemical, and sensory indicators under storage temperatures.The effect of temperature on quality indices (Ea)was29.57-96.8 kJ/mol. The acceptable limits for vitamin C loss and weight loss for fresh-cut pineapple were 27.71 mg/100 g fresh weight and 4.32 %, respectively, in accordance with cutoffs determined on the basis of sensory changes. Key quality indicators that could predict the remaining shelf-life between 5 °C and 25 °C were the TVC and WL. Vitamin C loss was only suitable when storage temperature was above 10 °C. The remaining shelf-life in a real supply chain in terms of the TVC, vitamin C loss, and WL were 9.9, 3.5, and 4 days, respectively. Overall, the shelf-life prediction model developed using selected key indicators may help in managing temperature in the fresh-cut fruit supply chain and improving storage shelf-life.

Enhancing seafood traceability: tracking the origin of seabass and seabream from the tuscan coast area by the analysis of the gill bacterial communities

BACKGROUND

The seafood consumption and trade have increased over the years, and along its expected expansion pose major challenges to the seafood industry and government institutions. In particular, the global trade in fish products and the consequent consumption are linked to reliable authentication, necessary to guarantee lawful trade and healthy consumption. Alterations or errors in this process can lead to commercial fraud and/or health threats. Consequently, the development of new investigative tools became crucial in ensuring unwanted scenarios. Here we used NGS techniques through targeted metagenomics approach on the V3-V4 region of the 16S rRNA genes to characterize the gill bacterial communities in wild-caught seabream (Sparus aurata) and seabass (Dicentrarchus labrax) within different fisheries areas of the "Costa degli Etruschi'' area in the Tuscan coast. Our challenge involved the possibility of discriminating between the microbiota of both fish species collected from three different fishing sites very close to each other (all within 100 km) in important areas from a commercial and tourist point of view.

RESULTS

Our results showed a significant difference in the assembly of gill bacterial communities in terms of diversity (alpha and beta diversity) of both seabass and seabream in accordance with the three fishing areas. These differences were represented by a unique site -related bacterial signature, more evident in seabream compared to the seabass. Accordingly, the core membership of seabream specimens within the three different sites was minimal compared to the seabass which showed a greater number of sequence variants shared among the different fishing sites. Therefore, the LRT analysis highlighted the possibility of obtaining specific fish bacterial signatures associated with each site; it is noteworthy that specific taxa showed a unique association with the fishing site regardless of the fish species. This study demonstrates the effectiveness of target-metagenomic sequencing of gills in discriminating bacterial signatures of specimens collected from fishing areas located at a limited distance to each other.

CONCLUSIONS

This study provides new information relating the structure of the gill microbiota of seabass and seabream in a fishing area with a crucial commercial and tourist interest, namely "Costa degli Etruschi". This study demonstrated that microbiome-based approaches can represent an important tool for validating the seafood origins with a central applicative perspective in the seafood traceability system.

Research on safety risk control of prepared foods from the perspective of supply chain

Prepared foods bring great convenience to people's lives, but they also entail safety risks in all aspects, from production to sales. The cooperation of the supply chain and the supervision of the government are key to promoting the safety management of prepared foods. This paper considers the government's regulation, focuses on the interaction relationship between the producer and the retailer of prepared foods, and builds an evolutionary game model to analyze the influence of collaborative decision-making between prepared food producers and retailers in preventing and controlling food safety risks under the government's regulatory strategy. The research finds that: (1) Under certain conditions, there are three stable equilibrium strategies within the prepared foods supply chain: bilateral low-safety inputs, unilateral high-safety inputs, and bilateral high-safety inputs. (2) Government regulators can influence the safety input behaviors of prepared food supply chain enterprises by adjusting investigation probabilities and punishment severity. (3) The safety input behaviors of these enterprises are influenced by various factors, including costs, revenues, brand image, reputation, and the consequences associated with contractual violations. This paper represents the first systematic analysis of prepared food safety from a supply chain perspective. It fills a gap in the existing literature in this area, offering guidance and suggestions for prepared food supply chain enterprises, as well as references and recommendations for government regulators.

The improvement of block chain technology simulation in supply chain management (case study: pesticide company)

This research was conducted on industrial agriculture in Indonesia. Risk analysis was carried out based on previous research. One source of risk was obtained, namely raw materials that did not meet specifications, which was then proposed to be mitigated by evaluating supplier performance. This activity involves a lot of data, requiring efficient and effective data storage and access. The level in the simulation layout includes analysing system needs, using problem diagrams, compiling activity diagrams, deciding subprocesses, and filtering information. The analysis is carried out by comparing the use of supply chains with Blockchain and without Blockchain, which is then obtained to determine whether there is an increase. A sequentially stored data scenario describes a situation when the transaction process is in progress and is stored sequentially according to the process that occurs. Storing data in groups explains a problem when a transaction has been completed and stored in groups with similar data, making it easier to track specific data. In this regard, a simulation will be carried out using a website, namely a blockchain demo. The design stage starts with identifying system requirements, creating use case diagrams, compiling activity diagrams, determining subprocesses, and selecting information. The simulation results obtained will be analysed to determine the feasibility of Blockchain as a means of supporting risk mitigation related to data using aspects, including security, trust, traceability, sustainability, and costs.

Selective ionization of marker molecules in fuels by laser-based ion mobility spectrometry (LIMS)

Careful quality control of complex matrices such as fuels and food is necessary due to the prevalence of counterfeit and pirated goods in global trade. The addition of taggants (indicator substances) to products or their packaging helps to ensure traceability. In order to prevent the mixing of different liquid products, such as different taxed fuels, invisible labelling (marker) can be used to detect illegal activities. This study investigates the qualitative and quantitative analysis of markers in complex fuel matrices using Resonance-Enhanced Multiphoton Ionisation (REMPI) Ion Mobility Spectrometry (IMS). The potential of REMPI as a selective ionisation technique for the detection of markers is highlighted, particularly with respect to minimizing matrix background and the possibility of detection without chromatographic pre-separation. Finding a suitable marker-wavelength combination that provides a suitable marker-to-matrix ratio allows selective ionization of markers while minimising matrix background. Matrix analysis shows that higher excitation wavelengths result in reduced matrix signals, with the low intensities observed at 355 nm for diesel and petrol matrices. Several candidate markers are evaluated based on the criteria of intense signal at 355 nm and non-leachability for the low tax labelling. The analytical performance of selected markers is evaluated, with a focus on the charge transfer reaction (CTR) between markers and matrix components. Our findings demonstrate the potential of REMPI-IMS for marker analysis in fuels without the need for chromatographic pre-separation, providing a promising approach for detecting illegal or fraudulent activities in the supply chain.

A data-driven approach for prioritising microbial and chemical hazards associated with dairy products using open-source databases

This study presents a data-driven approach for classifying food safety alerts related to chemical and microbial contaminants in dairy products using the Rapid Alert System for Food and Feed (RASFF) and the World Health Organization (WHO)'s Global Environmental Monitoring System (GEMS) food contaminants databases. This research aimed to prioritise microbial and chemical hazards based on their presence and severity through exploratory data analysis and to classify the severity of chemical hazards using machine learning (ML) approaches. It identified Listeria monocytogenes, Escherichia coli, Salmonella, Pseudomonas spp., Staphylococcus spp., Bacillus cereus, Clostridium spp., and Cronobacter sakazakii as the microbial hazards of priority in dairy products. The study also prioritised the top ten chemical hazards based on their presence and severity. These hazards include nitrate, nitrite, ergocornine, 3-MCPD ester, lead, arsenic, ochratoxin A, cadmium, mercury, and aflatoxin (G1, B1, G2, B2, G5 and M1). Using ML techniques, the accuracy rate of classifying food safety alerts as either 'serious' or 'non-serious' was up to 98 %. Additionally, the study identified Reference dose (RfD), substance amount, notification type, product, and substance as the most important features affecting the ML models' performance. These ML models (decision trees, random forests, k-nearest neighbors, linear discriminant analysis, and support vector machines) were also validated on an external dataset of RASFF alerts related to chemical contaminants in dairy products. They achieved an accuracy of up to 95.1 %. The study's findings demonstrate the models' robustness and ability to classify food safety alerts related to chemical contaminants in dairy products, even on new data. These results can enhance the development of more effective machine-learning models for classifying food safety alerts related to chemical contaminants in dairy products, highlighting the importance of developing accurate and efficient classification models for timely intervention.

Geographical origin identification of mandarin fruits by analyzing fingerprint signatures based on multielemental composition

Given rising traders and consumers concerns, the global food industry is increasingly demanding authentic and traceable products. Consequently, there is a heightened focus on verifying geographical authenticity as food quality assurance. In this work, we assessed pattern recognition approaches based on elemental predictors to discern the provenance of mandarin juices from three distinct citrus-producing zones located in the Northeast region of Argentina. A total of 202 samples originating from two cultivars were prepared through microwave-assisted acid digestion and analyzed by microwave plasma atomic emission spectroscopy (MP-AES). Later, we applied linear discriminant analysis (LDA), k-nearest neighbor (k-NN), support vector machine (SVM), and random forest (RF) to the element data obtained. SVM accomplished the best classification performance with a 95.1% success rate, for which it was selected for citrus samples authentication. The proposed method highlights the capability of mineral profiles in accurately identifying the genuine origin of mandarin juices. By implementing this model in the food supply chain, it can prevent mislabeling fraud, thereby contributing to consumer protection.

The Application of Artificial Intelligence and Big Data in the Food Industry

Over the past few decades, the food industry has undergone revolutionary changes due to the impacts of globalization, technological advancements, and ever-evolving consumer demands. Artificial intelligence (AI) and big data have become pivotal in strengthening food safety, production, and marketing. With the continuous evolution of AI technology and big data analytics, the food industry is poised to embrace further changes and developmental opportunities. An increasing number of food enterprises will leverage AI and big data to enhance product quality, meet consumer needs, and propel the industry toward a more intelligent and sustainable future. This review delves into the applications of AI and big data in the food sector, examining their impacts on production, quality, safety, risk management, and consumer insights. Furthermore, the advent of Industry 4.0 applied to the food industry has brought to the fore technologies such as smart agriculture, robotic farming, drones, 3D printing, and digital twins; the food industry also faces challenges in smart production and sustainable development going forward. This review articulates the current state of AI and big data applications in the food industry, analyses the challenges encountered, and discusses viable solutions. Lastly, it outlines the future development trends in the food industry.

Agri-Food Value Chain Traceability Using Blockchain Technology: Portuguese Hams' Production Scenario

The globalization of food markets has led companies to buy products not only locally, but also from other corners of the world. This has introduced complexity into supply chains, as products have to move longer distances and pass through more companies before reaching the end consumer. The meat industry has been no different. Events such as animal disease outbreaks have diminished consumer confidence in the industry and the supply chain. Coupled with this, consumers started demanding "more transparent" meat products. This has led companies to think about new traceability systems, which continue to enforce food safety and health rules, but at the same time enhance and make transparent to the consumer the origin and constitution of their products. This article proposes a traceability system in the agri-food (meat industry) with a multi-chain architecture, among them, blockchain. The use of blockchain in the traceability system helped to mitigate the omission of relevant data for the traceability process, allowing us to guarantee the immutability, reliability, and transparency of the data along the value chain. At the same time, the system was able to reduce the time of the traceability process by giving the user the possibility to access the traced information via a unique product identifier.

A review of supply chain quality management practices in sustainable food networks

Supply chain quality management practices are necessary to improve processes, meet consumer quality needs, and enhance supply chain quality management performance in sustainable food networks. Food supply chain quality management and associated practices are considerably studied in global food systems, less so for alternative food networks. There are salient differences between global food systems and alternative food networks, which may reflect on the applicable supply chain quality management practices in the food systems and networks. This paper reviews the literature on supply chain quality management practices, with a focus on alternative food networks. A systematic literature review methodology is adopted, resulting in the analysis of seventy-eight papers, identifying a total of one hundred and three supply chain quality management practices. The identified supply chain quality management practices were analysed in relation to their link to a) place, production, and producer and b) link to (bio)processes. Emerging themes from the analysis are discussed, and some areas of future research were put forward.

Ambient temperature, refrigerator food load, and door openings effect on a preservation performance indicator based on chicken temperature data and predictive microbiology

Home preservation depends on the food matrix, refrigerator design/technology, consumer actions, and ambient temperature. Storing different food matrices in product-relevant refrigerator locations generating different temperature histories can be used to develop an indicator of how refrigerator technology, consumer habits, and environment conditions impact the refrigerator food preservation performance. In this study, poultry, particularly prone to spoilage reflecting its pH, nutrient availability, and high aw, was used to evaluate refrigerator preservation performance as affected by compressor technology (single [SS] and variable speed [VS]), ambient temperature (21.1°C [LT] and 32.2°C [HT]), and refrigerator load (22.5 kg [RL] and 39 kg [HL]). Time-temperature values collected for chicken breast stored in a drawer independently controlled at 0°C in a refrigerator set 5°C, and a Pseudomonas predictive microbiology model, were used to estimate a normalized refrigerator performance indicator (RPI). Values <1, ∼1, and >1 described excellent, good, or poor performance, respectively. A first analysis revealed that up to 54% of chicken breast temperatures were above its recommended refrigerated storage value. When ignoring variability sources, SS technology yielded RPI values ranging 0.61-0.70, whereas the more energy efficient VS compressor yielded values ranging 0.86-1.14. The higher and wider VS RPI range reflects a compressor control logic optimized for energy efficiency compliance while disregarding effects on food preservation. When considering the variability of model parameters and temperature measurements through one-sided 95% confidence intervals yielded RPI reaching 1.16. Although the independently controlled drawer preservation performance was near optimal, it can improve by considering energy use and preservation impact when optimizing the compressor speed control protocol. PRACTICAL APPLICATION: Worldwide poultry meat consumption has reached 15 kg per person. Refrigeration is widely used for its safety and quality preservation. Efficiency regulations decreased the energy use of residential refrigerators by nearly tenfold even though their size increased by 50% in the last half century. In this study, we provide quantitative evidence that their preservation performance must be improved. This is particularly true for upper end units typically equipped with quieter and more energy-efficient variable speed compressors. The same methodology can be used to evaluate the preservation performance of the storage units, trucks, and display cases used for refrigerated products.

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.

"Blockchain technology in food safety and traceability concern to livestock products"

Livestock products share more than fifteen percent of total agri-foods traded worldwide. A global increase in food demand has increased the risk to food safety. Improvements in food quality, cold chain transit, and preservation are required for safe livestock products. Though, the food safety and regulation authorities demand complete food traceability from farm to fork, but in traditional supply chain it is ignored by fiddling with the transit paperwork and bill invoices. The process of supply chain reformation and activities linked to food recalls during food safety issues are insanely expensive and challenging. Traceability-driven food supply chain management is likely to implement novel technologies like the Internet of Things (IoT). The capability of the Blockchain era within the food sector is emerging with use cases across different regions, as shown via the growing number of studies. Credibility, efficiency, and safety are all improved when food products can be instantly traced from their point of origin through all points of contact on their way to the consumer. Blockchain assures a tamper-proof and transparent system that allows an innovative business solution, together with smart contracts. However, there are significant difficulties with the implementation of blockchain technology for food traceability. It necessitates more and more training platforms as well as trainers, who can make understanding and operability of this technology easy among ground-level participants and food entities. For the tactical application of this technology, it is essential to comprehend the legal and regulatory framework.

Current Technologies and Uses for Fruit and Vegetable Wastes in a Sustainable System: A Review

The fruit and vegetable industry produces millions of tons of residues, which can cause large economic losses. Fruit and vegetable wastes and by-products contain a large number of bioactive substances with functional ingredients that have antioxidant, antibacterial, and other properties. Current technologies can utilize fruit and vegetable waste and by-products as ingredients, food bioactive compounds, and biofuels. Traditional and commercial utilization in the food industry includes such technologies as microwave-assisted extraction (MAE), supercritical fluid extraction (SFE), ultrasonic-assisted extraction (UAE), and high hydrostatic pressure technique (HHP). Biorefinery methods for converting fruit and vegetable wastes into biofuels, such as anaerobic digestion (AD), fermentation, incineration, pyrolysis and gasification, and hydrothermal carbonization, are described. This study provides strategies for the processing of fruit and vegetable wastes using eco-friendly technologies and lays a foundation for the utilization of fruit and vegetable loss/waste and by-products in a sustainable system.

Supply chain traceability using blockchain

In the current global marketplace supply chains can span a huge number of countries, cross many borders and require interoperation of a multitude of organizations. This vastness of supply chains impacts business competitiveness since it adds complexity and can difficult securing traceability, chain of custody and transparency. We propose that assuring chain of custody and traceability via Blockchain (BC) allows organizations to demonstrate product provenance, integrity and compliance. This work proposes that to effect true traceability the more complete approach is to connect both the Supply Chain Actors (SCAs) and products identifications using digital certificates. A Blockchain is used to manage the traceability of products and validation of the identities. Importing, verifying and storing the certificates uses an off-chain data storage solution for products certificates, IDs and data (i.e., WalliD) . To create, validate the certificates and setup the chain of trust a Public Key Infrastructure (PKI) was designed as part of the proposal. Our study follows a Design Science research approach aimed to analyse the requirements and propose a solution to a more complete traceability in supply chains. The results were architectural artifacts, including an Ethereum Smart Contract and a PKI based certificate authentication system. The implementation of these deliverables allow for a supply chain system that can provide decentralized and trustful assurance of the provenance, chain of custody and traceability functionalities for all the Organizations and also for the final consumers.

To exemplify the problem and demonstrate the applicability of the solution, its potential and benefits we applied it to a real food supply chain use case that already uses provenance certificates and stored them in the blockchain using the before mentioned SmartContract to assure and demonstrate the chain of custody and traceability of the food produce.

Application of blockchain technology in shaping the future of food industry based on transparency and consumer trust

Food Industries, at this moment, are moving towards a new phase, and this phase will be governed by consumers and not by the industry leaders. The report shows that claims on sustainability, health, wellness, and transparency would govern the future trends in the food industry. Currently, there are several cases of misleading and false claims which hamper consumer trust. So, to uphold consumer trust, authentication of claims through transparency in the food supply chain is required, and blockchain technology can bring transparency at relatively low transaction costs. Once in a blockchain network, data is very difficult to manipulate, with no single point of authority to mess and collapse the system. Though we see mostly the financial systems using blockchain's decentralized functionality, there is a growing trend of innovative applications being built in the supply chain area for contracts and operations. With effort in the right direction and over time, blockchain will recast how operations and processes are done across the industry, including public sectors. The paper reviews the opportunity for the blockchain in enabling food industries for future-readiness, empowering the consumers in verifying the product claims and thus prevent themselves from food fraud. In doing so, the paper considers the future trends in the food industry, identifies current food fraud cases, and outlines the various applications in the agri-food chain and challenges associated with it.

Graphical abstract

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.

Appraisal of Kenya's excisable goods management system using interrupted time series analysis: A case of cigarettes and cigars excise tax revenue

The government of Kenya introduced the Excisable Goods Management System (EGMS) in November 2013, which is a form of Track and Trace Systems (TTSs) for excisable goods, including cigarettes and cigars. This study appraised the EGMS with a focus on its impact on cigarette and cigars excise tax revenue and possibly control of related illicit trade in Kenya. Illicit trade in cigarettes and cigars pose significant health risks owing to increased access to tobacco products, besides contributing to loss of government revenues. The study utilised an Interrupted Time Series Analysis (ITSA) to assess impacts of the EGMS on monthly cigarette and cigars real excise tax revenue over the period April 2013 to March 2017. The results show that the difference between the pre-intervention and post-intervention slopes of the real excise tax revenue was positive and statistically significant, suggesting a change in excise tax revenue trends. The hypothesis of an immediate level change in excise tax revenue was however not supported, possibly due to the initial implementation challenges that dampened a 'jump' in real excise tax revenue. These findings suggest that TTSs need to be complemented by sustained efforts to achieve maximum compliance levels and impact in both the short term and the long term.

Determinants of the willingness to buy products certified by omics technology: differences between regular and occasional consumers of organic food

Consumers' demand for organic food has increased in the last years, together with a growing request for food authentication and safety. Omics technologies represent a viable analytical strategy to respond to such needs, strengthen food safety information transmission between consumers and industry, and differentiate between organic and conventional products. However, little is known about consumers' perception of such a novel certification approach. The present research ought to provide insights into the perspectives of consumers, exploring the antecedents of their intention to purchase organic vegetables certified through omics technologies and differentiating between regular and occasional consumers of organic foods. Data were collected from a representative sample of 807 Italian respondents who completed a self-report questionnaire, and Structural Equation Modeling was performed to analyze the data. Results show that several factors influence consumers' approach to omics technology, among which trust in actors in the food industry, attitudes towards the technology and environmental food concerns. In addition, the study drew attention to the differential path impacting consumers with distinct eating habits. Indeed, the degree of importance attributed to food in one's life and the interest towards innovative food are significant predictors of the intention to adopt omics technology only for people consuming organic products with higher frequency. Also, trust in industry actors follows a different path for regular and occasional organic food consumers. The present study sheds light on consumers' perspective on omics technologies, a relatively unexplored topic. Moreover, it allowed to differentiate consumers based on their organic consumption habits, which has been rarely done in previous research. The evidence collected suggests the need for tailored communication programs to stimulate the adoption of omics technologies and foster consumers' confidence in novel food technologies.

Personal Glucose Meters Coupled with Signal Amplification Technologies for Quantitative Detection of Non-Glucose Targets: Recent Progress and Challenges in Food Safety Hazards Analysis

Ensuring food safety is paramount worldwide. Developing effective detection methods to ensure food safety can be challenging owing to trace hazards, long detection time, and resource-poor sites, in addition to the matrix effects of food. Personal glucose meter (PGM), a classic point-of-care testing device, possesses unique application advantages, demonstrating promise in food safety. Currently, many studies have used PGM-based biosensors and signal amplification technologies to achieve sensitive and specific detection of food hazards. Signal amplification technologies have the potential to greatly improve the analytical performance and integration of PGMs with biosensors, which is crucial for solving the challenges associated with the use of PGMs for food safety analysis. This review introduces the basic detection principle of a PGM-based sensing strategy, which consists of three key factors: target recognition, signal transduction, and signal output. Representative studies of existing PGM-based sensing strategies combined with various signal amplification technologies (nanomaterial-loaded multienzyme labeling, nucleic acid reaction, DNAzyme catalysis, responsive nanomaterial encapsulation, and others) in the field of food safety detection are reviewed. Future perspectives and potential opportunities and challenges associated with PGMs in the field of food safety are discussed. Despite the need for complex sample preparation and the lack of standardization in the field, using PGMs in combination with signal amplification technology shows promise as a rapid and cost-effective method for food safety hazard analysis.

Blockchain, Quo Vadis? Recent Changes in Perspectives on the Application of Technology in Agribusiness

Information technologies such as blockchain are developing fast, overcoming bottlenecks, and quickly taking advantage of their application. The present study analyzes recent changes concerning the benefits, disadvantages, challenges, and opportunities of blockchain applications in agribusiness. Interviews were conducted with and a questionnaire was applied to professionals working in the development and application of blockchain technology in agribusiness, to compare their perception of the recent advances. The results showed that the importance of blockchain technology to improve governance and information flow along supply chains has increased, and this is the main perceived benefit. The main disadvantages were removing intermediaries and the high cost of implementing the technology. The absence of a widely accepted platform in blockchain operations is the leading and growing challenge, while patterns for blockchain technology seem to be being overcome. The integration of blockchain with new technologies, and the competitiveness provided by the technology, are seen as the main and growing opportunities. Despite the study limitations, we conclude that the benefits and opportunities associated with blockchain application in agribusiness outweigh the challenges and disadvantages in number and importance, and are becoming more relevant.

Antecedents and consequences of blockchain adoption in supply chains: a systematic literature review

Purpose

Despite the availability of several published reviews on the adoption of blockchain (BC) in supply chain (SC), at present, the literature lacks a comprehensive review incorporating the antecedents and consequences of BC adoption. Moreover, the complex adoption of BC in SC, explained with the mediating and moderating relationships, is not fully consolidated. Thus, the aim of this study was to conduct a systematic literature review (SLR) on BC technology adoption (BCTA) in SC by integrating its antecedents and consequences.

Design/methodology/approach

Keyword searches were performed in multiple databases resulting 382 articles for evaluation and verification. After careful screening with respect to the purpose of the study and systematic processing of the retrieved articles, a total of 211 peer-reviewed articles were included in this study for review.

Findings

Various technological, organisational, individual, social, environmental, operational and economic factors were found as the antecedents of BCTA in SC. In addition, numerous applications of BC Technology (BCT) were identified, including asset management, identity management, transaction management, data management and operations management. Finally, the consequences of BCTA were categorised as operational, risk management, economic and sustainability outcomes.

Practical implications

This study can assist relevant decision-makers in managing the factors influencing BCTA and the potential uses of the technology to enhance SC performance.

Originality/value

By integrating the antecedents, applications and consequences of BCTA in SC, including the mediators and moderators, an integrated framework was developed that can potentially assist researchers to develop theoretical models. Further, the results of this SLR provide future directions for studying BCTA in supply chain management (SCM).

Biotechnological advancements towards water, food and medical healthcare: A review

The global health status is highly affected by the growing pace of urbanization, new lifestyles, climate changes, and resource exploitation. Modern technologies pave a promising way to deal with severe concerns toward sustainable development. Herein, we provided a comprehensive review of some popular biotechnological advancements regarding the progress achieved in water, food, and medicine, as the most substantial fields related to public health. The emergence of novel organic/inorganic materials has brought about significant improvement in conventional water treatment techniques, anti-fouling approaches, anti-microbial agents, food processing, biosensors, drug delivery systems, and implants. Particularly, a growing interest has been devoted to nanomaterials and their application for developing novel structures or improving the characteristics of standard components. Also, bioinspired materials have been widely used to improve the performance, efficiency, accuracy, stability, safety, and cost-effectiveness of traditional systems. On the other side, the fabrication of innovative devices for precisely monitoring and managing various ecosystem and human health issues is of great importance. Above all, exceptional advancements in designing ion-selective electrodes (ISEs), microelectromechanical systems (MEMs), and implantable medical devices have altered the future landscape of environmental and biomedical research. This review paper aimed to shed light on the wide-ranging materials and devices that have been developed for health applications and mainly focused on the impact of nanotechnology in this field.

Experimental investigation of different-shaped microwave-heated potatoes: thermal and quality characteristics analysis for food preservation

Food materials are consumed for nutritional purposes in the form of fruits, vegetables, plants, and meat. These contain proteins, carbohydrates, and other useful nutritional compounds and these processed foods are a rich source of nutrition. The demand and supply of hygienic food for a particular population is possible only by food preservation. It can be done by various methods such as drying, freezing, chilling, chemical preservation, and pasteurization. Drying is a method of food preservation and it can be done by solar drying, microwave heating, vacuum drying, and some other methods. Microwave heating is a fast-drying method. It utilizes electrical energy to generate heat energy. The domestic microwave oven is not harmful but a commercial-level oven may be little bit harmful, when operated on high frequency. Potato is used as a sample material with different shapes such as slab, cylindrical, and spherical. The microwave oven has been operated at four different microwave powers such as 100 W, 300 W, 600 W, and 800 W. Slab-shaped (30 °C), cylindrical-shaped (31.5 °C), and spherical-shaped (30.5 °C) food materials achieved maximum temperatures of 83.9 °C, 110.6 °C, and 146.1 °C respectively. The temperature variations and drying characteristics of the food samples have been monitored. An oven has achieved maximum drying efficiency of 25.65% with a slab-shaped sample. For the detection of the cracks and chemical compositions in the food samples, SEM with EDS analysis has been performed. Economic analysis of microwave oven has also been done and payback period has been found as 3.27 years.

Assessing retailer readiness to use blockchain technology to improve supply chain performance

Purpose

This paper aims to assess the readiness of retail workers to use blockchain technology (BCT) to improve supply chain performance. The assessment was made via a quantitative approach taken using a theoretical framework based on Keller’s motivation model and self-determination theory in the BCT context.

Design/methodology/approach

The authors collected data from 567 retail workers from an emerging country through a structured survey questionnaire. The authors tested the hypotheses of the proposed model using Warp PLS 7.0 and controlled firm age, industry type and technological intensity.

Findings

Our findings may help firms in making the process of digital transformation inclusive. The authors found that supplier-based attention and motivation through BCT lead to supply chain performance, and that supplier-based satisfaction and trust achieved through BCT positively impact supply chain performance. Further, supplier-based relevance on raw material selection with the higher trust and motivation levels achieved through BCT was found to have a positive impact on supply chain performance.

Research limitations/implications

IT supply chain applications are referred to as “lean” rather than “rich” because they still rely mainly on written and numerical means to present data. When the environment is less ambiguous, then less rich media can be used to facilitate communication. IT supply chain applications allow suppliers to spend time building relationships with other suppliers instead of focusing on administrative tasks, thus enhancing such relationships.

Originality/value

This study can be considered the first to assess retailer readiness to use BCT to improve supply chain performance through the theoretical lens of Keller’s motivation model and self-determination theory.

Assessing the role of organic food supply chain traceability on food safety and consumer wellbeing: A mediated-moderation investigation

INTRODUCTION/PURPOSE

Drawing on dynamic capabilities theory, this study offers a comprehensive framework for examining the relationships between organic food supply chain traceability, consumer wellbeing, and food safety trust based in organic food sector. The study also explores how consumer awareness of organic food influences the relationship between consumer wellbeing and food safety. We also look at a mediated moderation mechanism in the relationships stated earlier.

METHODS

Using a survey as the primary data collecting method, a total of 221 usable responses were collected. To test the hypothesized relationships between all variables, SPSS PROCESS Macro 3.3 is utilized.

RESULTS

The findings show that the organic food traceability OFSC affect food safety trust and food safety and consumer wellbeing are positively associated, while consumer awareness of organic food acts as a moderator on the relationship between food safety trust and consumer wellbeing. Also consumer awareness conditionally influences the strength of the indirect relationship between OFST and consumer wellbeing via food safety, thereby indicates a mediated moderation mechanism among the study variables.

DISCUSSION/IMPLICATIONS

This study clarifies how consumer food safety trust and organic food traceability can enhance their wellbeing. It contributes to the theory of dynamic capabilities as well as organic traceable product marketing strategies.

A Blockchain-Based Product Traceability System with Off-Chain EPCIS and IoT Device Authentication

Blockchain-based traceability systems are a promising approach because they are decentralized, transparent, and tamper proof; however, if all traceability data are uploaded to a blockchain platform, it may affect the efficiency or even lead to data explosion. Additionally, it is difficult to guarantee the reliability of the original data source of massive Internet of Things (IoT) devices. Furthermore, when different enterprise nodes adopt different data storage structures, the costs that are associated with data sharing will increase. In this paper, we have proposed a trustworthy product traceability system that is based on hyperledger fabric and Electronic Product Code Information Service (EPCIS), which is not only capable of making products traceable, but it can also authenticate and authorize the IoT devices that are used for data collection. First, we adopted the on-chain and off-chain collaborative management mechanism in order to alleviate data explosion on the chain. Second, we proposed a scheme to authenticate and authorize devices based on blockchain. Third, we complied with EPCIS and Core Business Vocabulary (CBV) standards and provided the EPCIS location discovery service in order to improve the interactivity. Finally, we implemented and tested the proposed traceability system and compared it with the existing research. The proposed solution provides product information traceability, data tamper proofing, data confidentiality, and data source reliability.

Corporate social responsibility as a catalyst of circular economy? A case study perspective in Agri-food

Purpose

This study aims to analyze how, under the stakeholder theory, corporate social responsibility (CSR) might favor the emergence of circular economy (CE) in the Agri-food sector, which is a relevant context, as it is technologically dynamic and requires paying attention to all the stakeholders.

Design/methodology/approach

An exploratory, qualitative research design has been adopted to study the phenomenon in detail, as it facilitates the understanding of complex phenomena such those under investigation and helps enrich existing theory with new insights from real-world cases to add theoretical generalizations to the existing body of research in the field.

Findings

The results of this study highlight that companies adopting CSR models are oriented toward circularity.

Practical implications

This study provides useful indications to managers and policymakers as to how to favor the two approaches (CSR and CE) and benefit all the stakeholders.

Originality/value

While there is wide scholarly and managerial interest toward CSR and CE, previous research has mainly analyzed CE and CSR as two independent phenomena. Therefore, there is a lack of understanding about how the two areas are linked. Following previous studies that have started to theoretically argue an interconnection between CSR and CE, in this research, it has been empirically investigated, and further explored theoretically, whether CSR can implicitly encourage the emergence of CE approaches.

A sense of ginger fraud: prevalence and deconstruction of the China-European union supply chain

As an important spice, ginger has been widely distributed in the Chinese and the European Union (EU) markets, the two largest trading areas, in various forms. The ginger supply chain between China and the EU is long and complex, providing opportunities for fraudsters to deceive consumers. However, limited attention has been given to food fraud in ginger, and there is a lack of research on this topic. In this review, ginger was used as an example for interpreting the fraud issues within low-priced and high-trade volume spice products. This review aims to summarize the open access information from food and food fraud databases, literature, and stakeholders about ginger fraud, and to map, deconstruct and analyse the food fraud vulnerability in the supply chain. In addition, potential testing strategies to detect ginger fraud were also discussed. The investigation of food fraud databases, a semi-structured literature review and online interviews with stakeholders revealed that adulteration is the major fraud type in ginger products. And the most vulnerable ginger products are ground ginger and finely processed ginger. The ginger supply chain from China to the EU comprises nine stages and is medium vulnerable to food fraud, both in regard to opportunities and motivational drivers. To ensure the integrity of the ginger supply chain, there is a need to apply fraud vulnerability tools in the companies of the industry. In addition, screening and confirmatory techniques based on the characteristics of ginger should be utilised for monitoring fraud issues in the supply chain.

Toward Better Food Security Using Concepts from Industry 5.0

The rapid growth of the world population has increased the food demand as well as the need for assurance of food quality, safety, and sustainability. However, food security can easily be compromised by not only natural hazards but also changes in food preferences, political conflicts, and food frauds. In order to contribute to building a more sustainable food system-digitally visible and processes measurable-within this review, we summarized currently available evidence for various information and communication technologies (ICTs) that can be utilized to support collaborative actions, prevent fraudulent activities, and remotely perform real-time monitoring, which has become essential, especially during the COVID-19 pandemic. The Internet of Everything, 6G, blockchain, artificial intelligence, and digital twin are gaining significant attention in recent years in anticipation of leveraging the creativity of human experts in collaboration with efficient, intelligent, and accurate machines, but with limited consideration in the food supply chain. Therefore, this paper provided a thorough review of the food system by showing how various ICT tools can help sense and quantify the food system and highlighting the key enhancements that Industry 5.0 technologies can bring. The vulnerability of the food system can be effectively mitigated with the utilization of various ICTs depending on not only the nature and severity of crisis but also the specificity of the food supply chain. There are numerous ways of implementing these technologies, and they are continuously evolving.

Research on traceability strategy of food supply chain considering delay effect

The traceability system has significantly contributed to ensure food safety and quality. However, the biggest difficulty in food traceability is the numerous links from field to table, and there is no stable strategic partnership between supply chain members and the lack of social responsibility of some practitioners. Thus, this study aims to seek the best traceability strategy for companies in centralized model and decentralized model, respectively. Therefore, we have constructed a differential game model based on the delay effect to determine the optimal traceability level and traceable goodwill and compare the profits of the food supply chain (FSC). The results show that the delay time is positively related to the level of traceability effort and has a high impact on the traceable goodwill. Companies in the FSC can formulate optimal traceability strategies based on delay time and foster improvement in food safety and quality.

Carbon nanomaterials for the detection of pesticide residues in food: A review

In agricultural fields, pesticides are widely used, but their residual presence in the environment poses a threat to humans, animals, insects, and ecosystems. The overuse of pesticides for pest control, enhancement of crop yield, etc. leaves behind a significant residual amount in the environment. Various robust, reliable, and reusable methods using a wide class of composites have been developed for the monitoring and controlling of pesticides. Researchers have discovered that carbon nanomaterials have a wide range of characteristics such as high porosity, conductivity and easy electron transfer that can be successfully used to detect pesticide residues from food. This review emphasizes the role of carbon nanomaterials in the field of pesticide residue analysis in different food matrices. The carbon nanomaterials including carbon nanotubes, carbon dots, carbon nanofibers, graphene/graphene oxides, and activated carbon fibres are discussed in the review. In addition, the review examines future prospects in this research area to help improve detection techniques for pesticides analysis.

Does a Traceability System Help to Regulate Pig Farm Households' Veterinary Drug Use Behavior? Evidence from Pig Farms in China

In China, there is a renewed interest in traceability systems as an efficient tool to guarantee pork safety. One of the pathways through which a traceability system can benefit consumers is by easing information asymmetry. However, past literature on the traceability system in China pays more attention to theoretical analysis and less to empirical analysis. Using a large-scale survey of pig farms in China, we investigate the effects influencing farmers' participation in the traceability system. Findings show that a traceability system can influence the safety of pork indirectly through its impacts on farmers' production behaviors. Another important finding is that unsafe pork is a result of non-standard use of veterinary drugs, and the traceability system works well for farmers by pushing them to take stricter safety measurements.

Advances in Machine Learning and Hyperspectral Imaging in the Food Supply Chain

Food quality and safety are the essential hot issues of social concern. In recent years, there has been a growing demand for real-time food information, and non-destructive testing is gradually replacing traditional manual sensory testing and chemical analysis methods with lagging and destructive effects and has strong potential for application in the food supply chain. With the maturity and development of computer science and spectroscopic techniques, machine learning and hyperspectral imaging (HSI) have been widely demonstrated as efficient detection techniques that can be applied to rapidly evaluate sensory characteristics and quality attributes of food products nondestructively and efficiently. This paper first briefly described the basic concepts of hyperspectral imaging and machine learning, including the imaging process of HSI, the type of algorithms contained in machine learning, and the data processing flow. Secondly, this paper provided an objective and comprehensive overview of the current applications of machine learning and HSI in the food supply chain for sorting, packaging, transportation, storage, and sales, based on the state-of-art literature from 2017 to 2022. Finally, the potential of the technology is further discussed to provide optimized ideas for practical application.

Rapid identification of the geographical origin of Eucommia ulmoides by using excitation-emission matrix fluorescence combined with chemometric methods

Eucommia ulmoides is an important and valuable traditional Chinese medicine with various medical functions, and has been widely used as health food in China, Japan, South Korea and other Asian countries for many years. The efficacy and quality of E. ulmoides are closely associated with the geographical origin. In this work, the potential of excitation-emission matrix (EEMs) fluorescence coupled with chemometric methods was investigated for simple, rapid and accurate for identification E. ulmoides from different geographical origins. Parallel factor analysis (PARAFAC) was applied for characterizing the fluorescence fingerprints of E. ulmoides samples. Moreover, k-nearest neighbor (kNN), principal component analysis-linear discriminant analysis (PCA-LDA) and partial least squares discriminant analysis (PLS-DA) models were used for the classification of E. ulmoides samples according to their geographical origins. The results showed that kNN model was more suitable for identification of E. ulmoides samples from different provinces. The kNN model could identify E. ulmoides samples from eight different geographical origins with 100% accuracy on the training and test sets. Therefore, the proposed method was available for conveniently and accurately determining the geographical origin of E. ulmoides, which can expect to be an attractive alternative method for identifying the geographic origin of other traditional Chinese medicines.

Relationship between the state of the country's logistics and perishable goods' output: dairy industry

Purpose

This paper seeks to assess the capabilities and maturity of supply chain planning and product quality management systems implemented by the dairy industries in three different countries: Russia, Kazakhstan, and Lithuania.

Design/methodology/approach

Through a systematic analysis of statistical information, the descriptors of the logistics supply chain efficiency were identified. Directions for dairy supply chain management improvement were also highlighted. The study uses secondary statistics from open sources as a basis for the comparative analysis across a range of indicators, including the Logistics Performance Index (LPI), the dairy products quantity, the production volume of milk and dairy products, and other indicators characterizing the dairy industry.

Findings

The results of this study suggest the inconsistency and narrowness of single indexes and ranking, which are traditionally used to evaluate the logistics system. LPI values confirmed that the internal efficiency of the Lithuanian logistics system exceeds similar systems in Russia and Kazakhstan.

Social implications

In this paper, ways to improve supply chain management of dairy products in the context of globalization have been determined, the prerequisites for the formation of the perishable goods market according to the balance of supply and demand and the institutional mechanism of this process, which represents important information for all interested economic agents, have been analyzed.

Originality/value

The proposed approach points to the importance of having detailed information on the supply chain infrastructure and the need to introduce a single information space based on modern information and communication technologies.

Assessing Risks in Dairy Supply Chain Systems: A System Dynamics Approach

Due to the dynamic nature of the food supply chain system, food supply management could suffer because of, and be interrupted by, unforeseen events. Considering the perishable nature of fresh food products and their short life cycle, fresh food companies feel immense pressure to adopt an efficient and proactive risk management system. The risk management aspects within the food supply chains have been addressed in several studies. However, only a few studies focus on the complex interactions between the various types of risks impacting food supply chain functionality and dynamic feedback effects, which can generate a reliable risk management system. This paper strives to contribute to this evident research gap by adopting a system dynamics modelling approach to generate a systemic risk management model. The system dynamics model serves as the basis for the simulation of risk index values and can be explored in future work to further analyse the dynamic risk’s effect on the food supply chain system’s behaviour. According to a literature review of published research from 2017 to 2021, nine different risks across the food supply chain were identified as a subsection of the major risk categories: macro-level and operational risks. Following this stage, two of the risk groups identified first were integrated with a developed system dynamics model to conduct this research and to evaluate the interaction between the risks and the functionality of the three main dairy supply chain processes: production, logistics, and retailing. The key findings drawn from this paper can be beneficial for enhancing managerial discernment regarding the critical role of system dynamics models for analysing various types of risks across the food supply chain process and improving its efficiency.

Traceability Information Model for Sustainability of Black Soybean Supply Chain: A Systematic Literature Review

Traceability information as a solution option becomes an important task for the industry in providing products, preparing sustainable raw materials, and ensuring adequate safety quality. The emergence of these demands makes the industry perform tracking in order to prepare product inventories ranging from raw materials to products that have been produced. Based on these reasons, the scope of this paper is to provide a systematic review of the literature on various aspects of implementing information traceability models and sustainability of supply chain on economic, social, environmental, technological, institutional, and infrastructural dimensions. For this purpose, we use the Scopus, Science Direct, EBSCO Host, and ProQuest databases. We used the PRISMA model to identify, filter, and test for the eligibility of articles to be included. We selected 52 articles contributed by this search engine. We found was that between 2018 to 2021 there was increasing interest in this research. The dominant traceability information model in the article uses blockchain, the rest use operations research (OR), Google Earth Engine (GEE), website-based, Unified Modeling Language (UML), Extensible Markup Language (XML), physical markup language (PML), logit, enterprise resource planning (ERP), soft independent modelling of class analogies (SIMCA), and Spatially Explicit Information on Production to Consumption Systems (SEI-PCS).

Blockchain technology-based sustainable management research: the status quo and a general framework for future application

The problems of data leakage and unreliable information transfer in the management process make sustainability management an inevitable need for future development. Globally, there is increasing attention paid to blockchain technology and particularly its application in addressing sustainable management issues, both from academia and industry. Aiming to deepen the understanding of how blockchain technology could deal with sustainable management issues across different disciplines, this paper investigates the latest research on the application of blockchain technology in sustainable management published from 2017 to 2021. It is found that there is a drastic surge of publications in the recent 2 years. The analysis focuses on authors' origins, the collaboration network of the keywords, countries, and research topics covered. The application of blockchain technology in five key sectors of sustainable management, encompassing energy management, construction management, supply chain management, environmental management, and e-government management, is selected for further analysis detail. Also, a general framework for applying blockchain technology is proposed for broadening its use and dealing with sustainable management issues. The findings show that the identified 108 publications are distributed in 75 different journals, and scholars from China, the UK, and the USA have been working closely in BT-based sustainable management research. Blockchain technology is just emerging in sustainable management, and there is a great potential for applying blockchain technology to improve sustainable management performance and, more importantly, to provide solutions to quite a few long-lasting problems in these sectors. Opportunities for future research are also presented and discussed.

Recent advances in the application of Raman spectroscopy for fish quality and safety analysis

Fish is one of the highly demanded aquatic products, and its quality and safety play a pivotal role in daily diet. However, the possible hazardous substance in perishable fish both in pre- and postharvest periods may decrease their values and pose a threat to public health. Laborious and expensive traditional methods drive the need of developing effective tools for detecting fish quality and safety properties in a rapid, nondestructive, and effective manner. Recent advances in Raman spectroscopy (RS) and surface-enhanced Raman scattering (SERS) have shown enormous potential in various aspects, which largely boost their applications in fish quality and safety evaluation. They have incomparable merits such as providing molecule fingerprint information and allowing for rapid, sensitive, and noninvasive detection with simple sample preparation. This review provides a comprehensive overview focusing on the applications of RS and SERS for fish quality assessment and safety inspection, highlighting the hazardous substance and illegal behavior both in preharvest (veterinary drug residues and environmental pollutants) and postharvest (freshness and illegal behavior) particularly. Moreover, challenges and prospects are also proposed to facilitate the vigorous development of RS and SERS. This review is aimed to emphasize potential opportunities for applying RS and SERS as promising techniques for routine food quality and safety detection. PRACTICAL APPLICATION: With these applications, it can be clearly indicated that RS and SERS are promising and powerful in fish quality and safety surveillance, thereby reducing the occurrence of commercial fraud and food safety issues. More efforts still should be concentrated on exploiting the high-performance Raman instruments, establishing a universal Raman database, developing reproducible SERS substrates and combing RS with other versatile spectral techniques to promote these technologies from laboratory to practice. It is hoped that this review should arouse more research interests in RS and SERS technologies for fish quality and safety surveillance, as well as provide more insights to make a breakthrough.

Application of Electrolyzed Water in the Food Industry: A Review

Electrolyzed water is a novel disinfectant and cleaner that has been widely utilized in the food sector for several years to ensure that surfaces are sterilized, and that food is safe. It is produced by the electrolysis of a dilute salt solution, and the reaction products include sodium hydroxide (NaOH) and hypochlorous acid. In comparison to conventional cleaning agents, electrolyzed water is economical and eco-friendly, easy to use, and strongly effective. Electrolyzed water is also used in its acidic form, but it is non-corrosive to the human epithelium and other organic matter. The electrolyzed water can be utilized in a diverse range of foods; thus, it is an appropriate choice for synergistic microbial control in the food industry to ensure food safety and quality without damaging the organoleptic parameters of the food. The present review article highlights the latest information on the factors responsible for food spoilage and the antimicrobial potential of electrolyzed water in fresh or processed plant and animal products.