Anticipation of food safety and fraud issues: ISAR - A new screening tool to monitor food prices and commodity flows

[The One Health approach in the context of global commodity chains, crises, and food and feed safety]

The holistic view of food and feed safety, including animal health and environmental conditions, is an important pillar of the One Health approach. The terminology thus clearly goes beyond the prevention of spreading microbiological diseases, in which context it is often understood, and highlights that humans, animals, and the environment as well as their interaction should be considered in a transdisciplinary context.In terms of One Health, this discussion paper focuses less on microbiological risks, but rather on the connection to chemical risks in the food chain. This is illustrated by concrete examples of chemical contaminants (metals, persistent organic contaminants, natural toxins). The mechanisms of input and transfer along the food chain are presented.Minimizing the presence of contaminants and thus exposure requires international and interdisciplinary cooperation in the spirit of the One Health approach. Climate change, pandemics, shortages of raw materials, energy deficiencies, political crises, and environmental disasters can affect the entire food chain from primary production of plant and animal foods to further processing and provision of products to consumers. In addition to changing availability, this can also have an impact on the composition, quality, and safety of food and feed. Based on the effect on global commodity chains, vulnerable and resilient areas along the food chain become visible. In terms of the One Health approach, the aim is to increase safety and resilience along the food chain and to minimize its vulnerability.

Analysis of Cross-Regional Transfer of Food Safety Risks and Its Influencing Factors-An Empirical Study of Five Provinces in East China

The cross-regional transfer of food safety risks has become more prominent, bringing new challenges to food safety regulation. This study used a social network analysis to delve into the nuanced features and determinants of the cross-regional transfer of food safety risks based on the food safety inspection data of five provinces in East China from 2016 to 2020, thus contributing to the establishment of effective cross-regional cooperation in food safety regulation. The main findings are as follows: First, the cross-regional transfer of unqualified products accounts for 36.09% of all unqualified products. Second, the food safety risk transfer network presents a typical complex network-a relatively low but increasing network density, heterogeneous nodes, numerous subgroups, and a dynamic structure-bringing more difficulties to food safety cross-regional cooperation. Third, territorial regulation and intelligent supervision both contribute to restricting cross-regional transfers. However, the advantages of intelligent supervision have not yet been brought into play due to low data utilization. Fourth, the development of the food industry helps to mitigate the cross-regional transfer of food safety risks. To achieve effective cross-regional cooperation in food safety risks, it is essential to use food safety big data as a guide and to maintain synchronization between the development of the food industry and the improvement of regulations.

Fraud vulnerability quantitative assessment of Wuchang rice industrial chain in China based on AHP-EWM and ANN methods

Vulnerability assessment has been used in the food fraud mitigation based on the subjective judgement of industry participants and simple calculation. To have a more objective result, an improved vulnerability quantitative assessment method was proposed. The overall fraud vulnerability was described by the vulnerability of fraud factors and the health and economic impact of fraud incidents. The fraud factors were related to opportunity, motivation and control measure. Analytic hierarchy process combined with entropy weighting method (AHP-EWM) and artificial neural networking (ANN) to improve judgment accuracy. In the application in Wuchang rice industrial chain, 51 fraud factors were used in the assessment and 10 experts, 36 farmers, 15 suppliers and 15 supervisors were interviewed. Results showed that Wuchang rice industrial chain was highly vulnerable to fraud. The opportunity for fraud was high, the motivation to commit it was moderate, and controls to prevent it needed reinforcing. Fraud vulnerability differed between farmers and suppliers. To reduce the fraud vulnerability, improved regulations and policies and stiffer penalties were strongly recommended.

Tools to combat food fraud - A gap analysis

A complex legal and institutional framework exists in the EU to ensure the safety of the feed-food chain, while such an integrated system for combating food fraud is under development. The European Commission (EC) Knowledge Centre for Food Fraud and Quality is charged with the provision of scientific insight for the policy making of EC services dealing with food fraud, and the creation of expert networks with the competent authorities of the EU Member States. To flag gaps in the existing infrastructure needed for effectively and efficiently fighting food fraud, the Centre together with the competent authorities and several EC services undertook a stocktaking exercise of what works well and which areas will need improvement. Out of several focus areas, (i) the development of early warning systems, (ii) the availability of compositional databases of vulnerable foods, and (iii) the creation of centres of competence were prioritised for further action.

Food Supply without Risk: Multicriteria Analysis of Institutional Conditions of Exporters

International trade in food knows no borders, hence the need for prevention systems to avoid the consumption of products that are harmful to health. This paper proposes the use of multicriteria risk prevention tools that consider the socioeconomic and institutional conditions of food exporters. We propose the use of three decision-making methods—Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), Elimination et Choix Traduisant la Realité (ELECTRE), and Cross-Efficiency (CE)—to establish a ranking of countries that export cereals to the European Union, based on structural criteria related to the detection of potential associated risks (notifications, food quality, corruption, environmental sustainability in agriculture, and logistics). In addition, the analysis examines whether the wealth and institutional capacity of supplier countries influence their position in the ranking. The research was carried out biannually over the period from 2012–2016, allowing an assessment to be made of the possible stability of the markets. The results reveal that suppliers’ rankings based exclusively on aspects related to food risk differ from importers’ actual choices determined by micro/macroeconomic features (price, production volume, and economic growth). The rankings obtained by the three proposed methods are not the same, but present certain similarities, with the ability to discern countries according to their level of food risk. The proposed methodology can be applied to support sourcing strategies. In the future, food safety considerations could have increased influence in importing decisions, which would involve further difficulties for low-income countries.

An automated alarm system for food safety by using electronic invoices

Background

Invoices had been used in food product traceability, however, none have addressed the automated alarm system for food safety by utilizing electronic invoice big data. In this paper, we present an alarm system for edible oil manufacture that can prevent a food safety crisis rather than trace problematic sources post-crisis.

Materials and methods

Using nearly 100 million labeled e-invoices from the 2013‒2014 of 595 edible oil manufacturers provided by Ministry of Finance, we applied text-mining, statistical and machine learning techniques to “train” the system for two functions: (1) to sieve edible oil-related e-invoices of manufacturers who may also produce other merchandise and (2) to identify suspicious edible oil manufacture based on irrational transactions from the e-invoices sieved.

Results

The system was able to (1) accurately sieve the correct invoices with sensitivity >95% and specificity >98% via text classification and (2) identify problematic manufacturers with 100% accuracy via Random Forest machine learning method, as well as with sensitivity >70% and specificity >99% through simple decision-tree method.

Conclusion

E-invoice has bright future on the application of food safety. It can not only be used for product traceability, but also prevention of adverse events by flag suspicious manufacturers. Compulsory usage of e-invoice for food producing can increase the accuracy of this alarm system.

The use of trade data to predict the source and spread of food safety outbreaks: An innovative mathematical modelling approach

Food is traded across the global markets to satisfy consumer demands, mainly from developed countries, for year-round access to a wide range of foods. This has resulted in an increasingly complex network of food trade and has made importing countries vulnerable to the spread of foodborne disease outbreaks originating from "foreign" food networks. Analysis of these networks can provide information on potential food safety risks and also on the potential spread of these risks through the food network in question. In this study, network theory has been used to analyse global trade. A mathematical model was developed enabling a simulation of the distribution of food products based on the publicly available data on international imports, exports and production provided by the Food and Agriculture Organization of the United Nations. Through numerical simulations we demonstrate, for the first time, the impact that the network structure has on the distribution of food products in terms of food safety risks. As a case study, a recent trans-national food safety incident was analysed, illustrating the potential application of the model in a foodborne pathogen outbreak. Using only the type of contaminated food and the countries where the outbreak was reported, the model was used to identify the most likely origin of the contaminated eggs, narrowing down the options to three countries (including the actual origin). Furthermore, it is used to identify those countries with significant food safety risks, due to imports of food produced in these three countries. The approach can help regulatory agencies and the food industry to design improved surveillance and risk mitigation actions against transnational food safety risks.

Quadratic Frequency Modulation Signals Parameter Estimation Based on Product High Order Ambiguity Function-Modified Integrated Cubic Phase Function

In inverse synthetic aperture radar (ISAR) imaging system for targets with complex motion, such as ships fluctuating with oceanic waves and high maneuvering airplanes, the multi-component quadratic frequency modulation (QFM) signals are more suitable model for azimuth echo signals. The quadratic chirp rate (QCR) and chirp rate (CR) cause the ISAR imaging defocus. Thus, it is important to estimate QCR and CR of multi-component QFM signals in ISAR imaging system. The conventional QFM signal parameter estimation algorithms suffer from the cross-term problem. To solve this problem, this paper proposes the product high order ambiguity function-modified integrated cubic phase function (PHAF-MICPF). The PHAF-MICPF employs phase differentiation operation with multi-scale factors and modified coherently integrated cubic phase function (MICPF) to transform the multi-component QFM signals into the time-quadratic chirp rate (T-QCR) domains. The cross-term suppression ability of the PHAF-MICPF is improved by multiplying different T-QCR domains that are related to different scale factors. Besides, the multiplication operation can improve the anti-noise performance and solve the identifiability problem. Compared with high order ambiguity function-integrated cubic phase function (HAF-ICPF), the simulation results verify that the PHAF-MICPF acquires better cross-term suppression ability, better anti-noise performance and solves the identifiability problem.