Similarity matching of food safety incidents in China: Aspects of rapid emergency response and food safety

The application of systematic accident analysis tools to investigate food safety incidents

Effective food safety (FS) management relies on the understanding of the factors that contribute to FS incidents (FSIs) and the means for their mitigation and control. This review aims to explore the application of systematic accident analysis tools to both design FS management systems (FSMSs) as well as to investigate FSI to identify contributive and causative factors associated with FSI and the means for their elimination or control. The study has compared and contrasted the diverse characteristics of linear, epidemiological, and systematic accident analysis tools and hazard analysis critical control point (HACCP) and the types and depth of qualitative and quantitative analysis they promote. Systematic accident analysis tools, such as the Accident Map Model, the Functional Resonance Accident Model, or the Systems Theoretical Accident Model and Processes, are flexible systematic approaches to analyzing FSI within a socio-technical food system which is complex and continually evolving. They can be applied at organizational, supply chain, or wider food system levels. As with the application of HACCP principles, the process is time-consuming and requires skilled users to achieve the level of systematic analysis required to ensure effective validation and verification of FSMS and revalidation and reverification following an FSI. Effective revalidation and reverification are essential to prevent recurrent FSI and to inform new practices and processes for emergent FS concerns and the means for their control.

Consumer brand and category switching behaviors after food safety incidents: Factors and mechanisms

The excessive mold found in Three Squirrels' nuts and the clenbuterol abuse of Shuanghui are two infamous food safety incidents in China. We adopted push-pull-mooring theory to conduct a model and examined the factors influencing consumer short-term or long-term brand-switching or category-switching behaviors following the two food safety incidents. We employed multinomial logistic regression and structural equation modeling as tools to analyze 1027 valid questionnaires. The results, for the first time, revealed that perceived risk, alternative selectivity, alternative attractiveness, controllability attribution, and habits were key push, pull and mooring factors influencing Chinese consumers' brand and category switching from food brands under food safety crisis, and most importantly, that their influential paths differed greatly under the two food safety incidents, suggesting a different influential mechanism across two product categories (i.e., utilitarian food and hedonic food). These findings throw light on the predictors and mechanisms that affect consumer brand and category switching from food brands under food safety crisis and help associated food businesses develop more targeted and powerful crisis management and public relations strategies.

Gold nanoparticles as colorimetric probes in food analysis: Progress and challenges

The rapid, sensitive and reliable food safety control is urgently needed due to the harmful effects of the food contaminants on human health. Colorimetric approach has exhibited promising potential for the detection of food contaminants due to their easy preparation, rapid detection, high sensitivity, and naked-eye sensing. In recent years, AuNPs-based colorimetric probes have been extensively explored for food analysis. The present article reviews the development of AuNPs-based colorimetric probes for colorimetric sensing and their applications in food analysis. It generally summarizes the properties of AuNPs and introduces the preparation and functionalization methods of AuNPs. An overview of the colorimetric sensing mechanisms of AuNPs-based probes and their applications in analysis of food contaminants are also provided. Although AuNPs-based colorimetric probes show many advantages in detection of food contaminants, challenges remain in terms of complexity of food matrices, multiple analytes detection in a single go, and testing conditions interference.

Curve Similarity Analysis for Reducing the Temperature Uncertainty of Optical Sensor for Oil-Tank Ground Settlement Monitoring

A nonuniform temperature field can deteriorate the performance of sensors, especially those working in the field, such as an optical sensor for oil-tank ground settlement (GS) monitoring. In this case, the GS monitoring employs hydraulic-level-based sensors (HLBS), which are uniformly installed along with the oil-tank basement perimeter and are all connected by hydraulic tubes. Then, the cylinder structure of the oil tank itself can create a strong temperature difference between the sensors installed in the sunlit front and those in the shadow. Practically, this sunlight-dependent difference can be over 30 °C, by which the thermal expansion of the measuring liquid inside the connecting hydraulic tubes keeps on driving a movement and, thereby, leads to fluctuations in the final result of the oil-tank GS monitoring system. Now, this system can work well at night when the temperature difference becomes negligible. However, temperature uncertainty is generated in the GS sensors due to the large temperature difference between the sensors in the daytime. In this paper, we measured the temperature where the sensor was located. Then, we compared the results of the GS sensors with their corresponding temperatures and fitted them with two separate curves, respectively. After observing the similarity in the tendency of the two curves, we found that there was a qualitative correlative relationship between the change in temperature and the uncertainty in the sensor results. Then, a curve similarity analysis (CSA) principle based on the minimum mean square error (MMSE) criteria was employed to establish an algorithm, by which the temperature uncertainty in the GS sensors was reduced. A practical test proved that the standard deviation was improved by 73.4% by the algorithm. This work could be an example for reducing the temperature uncertainty from in-field sensors through the CSA method.

Easily operated COF-based monolithic sponges as matrix clean-up materials for non-targeted analysis of chemical hazards in oil-rich foods

Non-targeted analysis of chemical hazards in foods plays a crucial role in controlling food safety. However, because it brings forward high demand for sample pretreatment, materials suitable for the pretreatment of foods, especially animal foods, are rare. Herein, covalent organic frameworks (COF)-based monolithic materials were constructed by three successive steps: preparation of polydimethylsiloxane (PDMS) sponge using sugar cube as a sacrificial template, loading of a heteroporous COF on PDMS sponge via ultrasonic or in-situ growth method, coating of the obtained PDMS@COF by polydopamine (PDA) network. As-prepared PDMS@COF@PDA sponges were demonstrated to work well in sample pretreatment of animal foods for non-targeted analysis of chemical hazards. After a simple vortex treatment for about 2 min, more than 98% triglycerides, the main interfering matrix components in animal foods, could be removed from lard and pork samples, accompanied by "full recovery" (recovery efficiencies: ≥63%) of 44 chemical hazards with different physicochemical properties. Besides providing promising sample pretreatment materials for non-targeted food safety analysis, this work also paves a feasible way to improve COF-based monolithic materials and thus promote their practical applications, because we found that the introduction of PDA network on COF-based monolithic material surface could play a role in "killing three birds with one stone": enhancing the stability of the materials by overcoming the detachment of COF during operations; controllably adjusting hydrophobic and hydrogen-bonding interactions on the material surface to promote the removal of triglycerides; weakening the hydrophobic and π-π interactions between COF and chemical hazards to increase the recoveries of chemical hazards.

Crisis Management Experience from Social Media: Public Response to the Safety Crisis of Imported Aquatic Products in China during the Pandemic

China's outbreak related to cold-chain aquatic product quality and safety in 2020 caused public panic and further led to a crisis in China's aquatic industry. This paper uses topic clustering and emotion analysis methods to text-mine the comments of netizens on Sina Weibo to study the main features of the public's views on the administration's crisis management measures and to provide experience for future imported food safety management. The findings show that for the imported food safety incident and the risk of virus infection, the public response had four types of characteristics: a higher proportion of negative emotion; a wider range of information demand; attention paid to the whole imported food industry chain; and a differentiated attitude towards control policies. Based on the online public response, countermeasures to further improve the management ability of imported food safety crises are proposed as follows: the government should pay active attention to the development trend of online public opinion; work more on exploring the content of public concern and emotion; strengthen the risk assessment of imported food and establish the classification and management measures of imported food safety events; construct the imported food safety traceability system; build a special recall mechanism for imported food safety; and improve the cooperation between government and media, enhancing the public's trust in policies.

Developing an analytical framework for estimating food security indicators in the United Arab Emirates: A review

Rapid population growth, climate change, limited natural resources, and the COVID-19 pandemic contribute to increased global hunger, necessitating intensive efforts to ensure food security and nutrition (FSN). Previous FSN approaches covered some dimensions, but not all, resulting in significant gaps in food security indicators. The Gulf Cooperation Council (GCC) and the Middle East and North Africa (MENA) regions have received less attention in food security studies, thus far necessitating considerable effort to develop an appropriate analytical framework. This study reviewed articles and international reports of FSN indicators, drivers and policies, methods, and models and extracted the challenges and gaps from the global and UAE contexts. The UAE and the world have gaps in FSN drivers, indicators, and methods, necessitating potential solutions to meet future challenges such as rapid population growth, pandemics, and limited natural resources. As a result, we created a newly developed analytical framework that addresses the shortcomings of previous approaches such as sustainable food systems developed by FAO and the Global Food Security Index (GFSI) and covers all aspects of food security. Gaps in knowledge in FSN drivers and policies, indicators, big data, methods, and models were considered in the developed framework, which has specific advantages. The novel developed framework addresses all food security dimensions (access, availability, stability, and utilization), ensuring poverty reduction, food security, and nutrition security while outperforming previous approaches (i.e., FAO and GFSI). The developed framework could be used successfully not only in the UAE and MENA, but also, globally, helping to solve food insecurity and malnutrition for future generations. The scientific community and policymakers should disseminate such solutions to address global food insecurity and ensure nutrition for future generations in the face of rapid population growth, limited natural resources, climate change, and spreading pandemics.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10668-023-03032-3.

The Perception of the National Traceability Platform among Small-Scale Tea Farmers in Typical Agricultural Areas in Central China

As one of the key technologies to ensure the safety of agricultural products, the national traceability platform is being widely promoted in China. However, it has not yet been widely adopted among farmers, especially small-scale farmers. Farmers are both producers and direct participants in the traceability of agricultural products. Their perception directly affects the effectiveness of the promotion of the national traceability platform. This study explores the perception of the national traceability platform among small-scale tea farmers in typical agricultural areas in central China. This research employed Q methodology, an approach that integrates both qualitative and quantitative data allowing individuals' subjective understandings of a specific topic to be studied. The Q-sort procedure was performed in the field with 16 small-scale tea farmers. Next, Q-factor analyses were conducted using the Ken-Q analysis. The results show that small-scale tea farmers have different perceptions of the national traceability platform. Their main characteristics are active participation, resistant participation, risk aversion, and being driven by pressure. These four categories covered 52% of the perceived variance. Meanwhile, there is also a degree of internal consistency in the perception of small-scale tea farmers. Specifically, they are all concerned that participating in the national traceability platform may increase the cost and risk of cultivation and that it is difficult to obtain support from agricultural technicians. Therefore, understanding the perceptions of tea farmers of the national traceability platform is the premise for formulating effective promotion policies. Our research sheds light on the decision-making mechanisms for small-scale tea farmers to participate in national traceability platforms, further expanding the scope of current research on farmer behavior. This research has reference significance for promoting national traceability platforms in China and other countries around the world.

Community public health safety emergency management and nursing insurance service optimization for digital healthy urban environment construction

The purpose of this paper is to promote the construction of digital healthy cities and improve the living standards of urban residents. Based on this, this paper analyzes the development of healthy cities, and studies community public health safety emergency management and nursing insurance service optimization methods for healthy urban environment construction. First, the concept of digital healthy urban environment construction is discussed. Then, the role of environmental health is discussed. Finally, two methods are designed to study the emergency management of public health safety and nursing insurance services in urban communities under the condition of environmental health. The results show that in the environmental health score of the city, the scores of X1 (the urban air quality excellent rate) and X6 (citizens' satisfaction with the environmental quality) were relatively low between 2016 and 2018, below 0.5 points. The scores for the remaining 3 years were relatively high, above 0.5. The scores of X2 (green coverage rate of built-up area), X3 (average grade sound effect of environmental noise in urban area), X4 (harmless treatment rate of domestic waste) and X5 (centralized treatment rate of domestic sewage) were relatively high from 2016 to 2018, above 0.5 points, and relatively low in the remaining 3 years, below 0.5 points. Meanwhile, residents are very satisfied with information collection and information management in public health and safety emergency management, and the number of very satisfied people is basically more than 40%. Satisfaction with resource allocation and privacy management is high, and the number of very satisfied people is basically above 30%. However, the satisfaction with risk perception and management measures is very low, and the number of very satisfied people is basically below 20%. It shows that the current construction of the community's public health and safety emergency management system is relatively poor in terms of X2-X5, while the development of X1 and X6 is relatively mature. The research not only provides a reference for the construction and improvement of a digital healthy city, but also contributes to the improvement of the healthy life of urban residents.

Agricultural big data and methods and models for food security analysis-a mini-review

Background

Big data and data analysis methods and models are important tools in food security (FS) studies for gap analysis and preparation of appropriate analytical frameworks. These innovations necessitate the development of novel methods for collecting, storing, processing, and extracting data.

Methodology

The primary goal of this study was to conduct a critical review of agricultural big data and methods and models used for FS studies published in peer-reviewed journals since 2010. Approximately 130 articles were selected for full content review after the pre-screening process.

Results

There are different sources of data collection, including but not limited to online databases, the internet, omics, Internet of Things, social media, survey rounds, remote sensing, and the Food and Agriculture Organization Corporate Statistical Database. The collected data require analysis (i.e., mining, neural networks, Bayesian networks, and other ML algorithms) before data visualization using Python, R, Circos, Gephi, Tableau, or Cytoscape. Approximately 122 models, all of which were used in FS studies worldwide, were selected from 130 articles. However, most of these models addressed only one or two dimensions of FS (i.e., availability and access) and ignored the other dimensions (i.e., stability and utilization), creating a gap in the global context.

Conclusions

There are certain FS gaps both worldwide and in the United Arab Emirates that need to be addressed by scientists and policymakers. Following the identification of the drivers, policies, and indicators, the findings of this review could be used to develop an appropriate analytical framework for FS and nutrition.

The impact of COVID-19 on the small and medium dairy farms and comparative analysis of customers' behavior in Armenia

The restrictions caused by the pandemic of COVID-19 have affected almost all economic sectors of different countries, including agriculture. At the global level of quarantine and lockdowns, the whole humanity has been faced with various problems, food insecurity being one of them. The current research aims to study the effect of the restraints imposed in Armenia upon COVID-19, in 2020 on the activities of small and medium dairy farms and to compare the retrieved data with those of pre-pandemic period. The study period covered March-August, 2020, when the most severe restrictions were working in Armenia, while the indicators were compared with the data of 2019 for the same period. Meanwhile, the changes of the customer behavior from the prospect of milk and dairy product purchase throughout the restriction period have been disclosed and their incentives have been enhanced. The investigations testify that in Armenia the milk production and sale prices haven't undergone any significant changes within the restriction period, which is mainly accounted for internal market sale and short run of severe restrictions. Considerable change has been recorded in the customer behavior, particularly in the first month after declaring state of emergency. An increase in the purchase rate of milk and dairy product per one-time buy, as well as a decrease in the visit frequency to the shops and supermarkets have been recorded.

Covid-19 pandemic effects on food safety - Multi-country survey study

This study provides an important insight into the response of food safety systems during the first months of the pandemic, elevating the perspective of preventing Covid-19 within conventional food safety management systems. A multi-country survey was conducted in 16 countries involving 825 food companies. Based on the results of the survey, it is obvious that the level of maturity of a food safety system in place is the main trigger in classifying companies and their responses to the pandemic challenge. Staff awareness and hygiene are the two most important attributes in combating Covid-19, opposed to temperature checking of workers in food establishment and health protocols from the World Health Organization, recognized as attributes with limited salience and importance. Companies confirmed implementation of more restrictive hygiene procedures during the pandemic and the need for purchasing more additional personal protective equipment. Retailers were identified as the food supply chain link mostly affected by the pandemic opposed to food storage facilities ranked as least affected. During this challenging period, all companies declared that food safety has not been compromised at any moment. It is important to note that less than a half of the food companies had documented any emergency plans associated with pandemics and health issues in place.