An Early Warning Support System for Food Safety Risks

2006 ◽  
pp. 446-457 ◽  
Author(s):  
Yasunobu Maeda ◽  
Norio Kurita ◽  
Saburo Ikeda
Keyword(s):  
Food Safety ◽  
Support System ◽  
Early Warning ◽  
Safety Risks

scholarly journals Automated food safety early warning system in the dairy supply chain using machine learning

2020 ◽  
Author(s):  
Ningjing Liu ◽  
Yamine Bouzembrak ◽  
Leonieke Bulk ◽  
Anand Gavai ◽  
Lucas Heuvel ◽  
...  
Keyword(s):  
Supply Chain ◽  
Food Safety ◽  
Early Warning ◽  
Food Supply ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Food Supply Chain ◽  
Safety Hazards ◽  
Safety Risks ◽  
Food Safety Risk

Abstract Traditionally, early warning systems for food safety are based on monitoring targeted food safety hazards. Therefore, food safety risks are generally detected only when the problems have developed too far to allow preventive measures. Successful early warning systems should identify signals that precede the development of a food safety risk. Moreover, such signals could be identified in factors from domains adjacent to the food supply chain, so-called drivers of change and other indicators. In this study, we show for the first time, using the dairy supply chain as an application case, that such drivers and indicators may indeed represent signals that precede the detection of a food safety risk. Using dynamic unsupervised anomaly detection models, anomalies were detected in indicator data expected by domain experts to impact the development of food safety risks in milk. Detrended cross-correlation analysis was used to demonstrate that anomalies in various indicators preceded reports of contaminated milk. Lag times of more than 12 months were observed. Similar results were observed for the 6 largest milk-producing countries in Europe (i.e., Germany, France, Italy, the Netherlands, Poland, and the United Kingdom). Additionally, a Bayesian network was used to identify the food safety hazards associated with an anomaly for the Netherlands. These results suggest that severe changes in domains adjacent to the food supply chain may trigger the development of food safety problems that become visible many months later. Awareness of such relationships will provide the opportunity for food producers or inspectors to take timely measures to prevent food safety problems. A fully automated system for data collection, processing, analysis and warning, such as that presented in this study, may further support the uptake of such an approach.

scholarly journals Comparison of whole genome sequences of three Bacillus cereus strains reveals the food safety risks of Apostichopus japonicus in China

2021 ◽  
Vol 20 ◽  
pp. 100649
Author(s):  
Xiaoran Zhao ◽  
Ruijun Li ◽  
Huifeng Dang ◽  
Luo Wang ◽  
Songzhe Fu ◽  
...  
Keyword(s):  
Food Safety ◽  
Bacillus Cereus ◽  
Apostichopus Japonicus ◽  
Whole Genome ◽  
Genome Sequences ◽  
Safety Risks

Deep Structured Learning for Natural Language Processing

2021 ◽  
Vol 20 (3) ◽  
pp. 1-14
Author(s):  
Yong Li ◽  
Xiaojun Yang ◽  
Min Zuo ◽  
Qingyu Jin ◽  
Haisheng Li ◽  
...  
Keyword(s):  
Public Opinion ◽  
Food Safety ◽  
Language Processing ◽  
Early Warning ◽  
Conditional Random Field ◽  
Semantic Features ◽  
Related Sequence ◽  
The Public ◽  
Network Public Opinion

The real-time and dissemination characteristics of network information make net-mediated public opinion become more and more important food safety early warning resources, but the data of petabyte (PB) scale growth also bring great difficulties to the research and judgment of network public opinion, especially how to extract the event role of network public opinion from these data and analyze the sentiment tendency of public opinion comment. First, this article takes the public opinion of food safety network as the research point, and a BLSTM-CRF model for automatically marking the role of event is proposed by combining BLSTM and conditional random field organically. Second, the Attention mechanism based on vocabulary in the field of food safety is introduced, the distance-related sequence semantic features are extracted by BLSTM, and the emotional classification of sequence semantic features is realized by using CNN. A kind of Att-BLSTM-CNN model for the analysis of public opinion and emotional tendency in the field of food safety is proposed. Finally, based on the time series, this article combines the role extraction of food safety events and the analysis of emotional tendency and constructs a net-mediated public opinion early warning model in the field of food safety according to the heat of the event and the emotional intensity of the public to food safety public opinion events.

Improving the quality and safety of dairy products by implementing a management system

2021 ◽  
pp. 28-31
Author(s):  
Natalia A. Jurk ◽  
Keyword(s):  
Food Safety ◽  
Management System ◽  
Safety Management ◽  
Quality Management System ◽  
Raw Materials ◽  
Developed Countries ◽  
Control Points ◽  
Quality And Safety ◽  
Critical Control Points ◽  
Safety Risks

In order to achieve a certain level of food production, it is necessary to manage its quality and safety. Currently, the quality management system based on the principles of HACCP is widely recognized and is the only method for ensuring food security in all developed countries. The ultimate goal of this system is to eliminate or reduce any food safety risks by preventing them. During the research, the main, auxiliary raw materials and the finished product were identified; flowcharts for the production of an enriched whey drink were developed. On the basis of the developed block diagrams, an analysis of microbiological, chemical, physical and qualitative hazards was carried out, it was determined which of the hazardous factors are the most critical, can harm health and must be eliminated or reduced to acceptable levels. Based on the analysis of significant hazards using the Decision Tree algorithm, two critical control points (pasteurization and cooling) were established. Measures for the management of critical control points are established in the HACCP plan, which reflects all CCPs of the production process of the research object and actions for monitoring and managing them. The introduction of elements of a food safety management system into practice contributes to the production of safe products of appropriate quality in compliance with applicable requirements and standards.

scholarly journals Food Safety and Employee Health Implications of COVID-19

2021 ◽  
Author(s):  
Aljosa Trmcic ◽  
Elizabeth Demmings ◽  
Kalmia Kniel ◽  
Martin Wiedmann ◽  
Samuel David Alcaine
Keyword(s):  
Food Safety ◽  
Food Supply ◽  
Food Industry ◽  
Food Packaging ◽  
Control Strategies ◽  
Epidemiological Data ◽  
Control Culture ◽  
Safety Risks ◽  
The Face ◽  
Effective Program

The COVID-19 pandemic has greatly impacted the US food supply and consumer behavior. Food production and processing are being disrupted as illnesses, proactive quarantines, and government-mandated movement restrictions cause labor shortages. In this environment, the food industry has been required to adopt new, additional practices to minimize the risk of COVID-19 cases and outbreaks among its workforce. Successfully overcoming these challenges requires a comprehensive approach that addresses COVID-19 transmission both within and outside the facility; possible interventions include strategies to (i) vaccinate employees, (ii) assure that employees practice social distancing, (iii) assure that employees wear face coverings, (iv) screen employees for COVID-19 (v) assure that employees practice frequent handwashing and avoid touching their faces, (vi) clean frequently touched surfaces, and (vii) assure proper ventilation. Compliance with these control strategies needs to be verified and an overall “COVID-19 control culture” needs to be established to facilitate an effective program. Despite some public misperceptions about SARS-CoV-2 presence on foods or food packaging representing a public health risk, it is important to note that both the virus’ biology and epidemiological data clearly support a negligible risk of COVID-19 transmission through food and food packing. However, COVID-19 pandemic related supply chain and workforce disruptions, as well as the shift in resources to protect food industry employees from COVID-19 may increase the actual food safety risks. The goal of this paper is to review the COVID-19 mitigation practices adopted by the food industry, and the potential impact of these practices and COVID-19 related disruptions on the industry’s food safety mission. A review of these impacts is necessary to ensure that the food industry is prepared to maintain a safe and nutritious food supply in the face of future global disruptions.

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