Analysing the effects of using a digital environment in official food safety control and understanding its benefits is crucial for competent authorities. The aim of this paper was to assess the ...effectiveness of official control carried out by the Barcelona Public Health Agency between 2015 and 2022 in Barcelona city (Spain) at retail outlets following the transition from a traditional to a digital inspection. Effectiveness is defined as the ability to detect non-compliance during inspections. This study assessed 2,188 inspection reports of risk-based planned inspections from 2015 to 2019 (traditional inspection) and 2022 (digital inspection) to compare the detection of non-compliances. The results show a significant increase in the detection of non-compliance when using the digital inspection. Compared to all inspection areas studied, the highest prevalence difference in the detection of non-compliance using a digital environment was found for the areas of food processing and handling procedures (34.0%) and own controls (16.7%). On the other hand, the areas of food labelling and general cleanliness of premises and equipment showed the lowest difference, 11.1% and 7.9%, respectively. The present case study shows that the use of a digital environment during inspections positively supports the control officers in structuring the compliance judgement and being more sensible to detect non-compliance. This fact results in a greater effectiveness of food control.
•This research investigated the impact of using digital technologies on the effectiveness of food control.•The mean number of non-compliant inspection areas significantly increased with digital inspection.•The inspection area with the highest prevalence difference was food processing and handling procedures (34.0%).•The use of a digital environment increased the effectiveness of official control in Barcelona city.
Food safety continues to be a challenge worldwide despite scientific advances, continuous improvement in food safety management systems and increasing academic debate on food safety. This paper aims ...to validate a new model of food safety cultural compliance to identify the challenges that organisations face in their pursuit of a positive food safety culture. A mixed-method approach was adopted via the quantitative analysis of a stage one ‘Enlighten Questionnaire’ involving 202 respondents using parametric statistics (ANOVA with appropriate Post-Hoc tests and t-tests). Hochberg's GT2 was used for the Post-Hoc tests due to different group sizes and appropriate non-parametric tests were also run to confirm these results. Qualitative analysis of stage two semi-structured interviews totalling 40 participants and stage three focus groups each consisting of 3 groups of 9 employees equating to 27 participants was utilised. Thematic analysis was adopted to synthesise and cluster key themes. Our findings identify the misalignment of management and employees in the pursuit of establishing and embedding a positive food safety culture. Four key themes of the Enlighten Food Safety Culture Model (EFSCM) namely; Control, Co-operation, Communication and Competence were core cultural factors that could be used to realign management and employee behaviours to help stimulate a positive food safety culture.
•Quality assurance systems do not guarantee food safety compliance.•Food Safety Culture relies on both management and employee commitment.•Control, Co-operation, Communication and Competence are food safety benchmarks.
Organizational culture is defined by dimensions and characteristics that can be used to measure food safety culture in food manufacturing through a food safety maturity model. Maturity models from ...quality, health care, and information technology have been used since early 1970 and this work presents a novel food safety culture maturity model with five capability areas and food safety pinpointed behaviours specific to functions and levels in a food manufacturing company. A survey tool linked to the model is used to measure a company's position within the maturity model framework. The method was tested with a Canadian food manufacturer and proved valuable to measure food safety culture across the five capability areas, which provides the manufacturer with a map for prioritizing future efforts to strengthen food safety culture.
•Theory of organizational culture was applied to measure food safety culture characteristics.•Food safety culture was measured using a self-assessment survey with pinpointed food safety behaviours.•A maturity model was developed to measure food safety culture in food manufacturing.•The tool was tested with a Canadian food manufacturer resulting in a measure of the organization's food safety culture across six capability areas.
Sustainable food supply is a primary concern for food industries, governments, and international agencies worldwide. Food industries are under continuous pressure to develop processing technologies ...that simultaneously preserve the nutritional value of foods, improve the bio-accessibility of nutrients, environment friendly and meet consumers' demands of sensory attributes. Furthermore, increasing population and inadequate cultivable land also demand transformations in the existing food processing techniques. Therefore, minimizing food wastages, sustainable developments in preservation, nutrient security, and food safety are essential elements for future requirements.
This study refers to the roles of the pulsed electric field (PEF) in sustainable food processing systems. It also discusses the effects of this emerging technology on achieving the critical industrial goals of enhanced food quality, decreased water usage, reduced emissions, increased energy efficiency, and the ability to utilize by-products from waste food. The current study also emphasizes the need to understand factors that may limit this emerging technology's industrial uptake.
A combined multi-dimensional methodology through the entire food supply is essential to meet the worldwide food processing challenges. A limited worldwide food resource must have a balanced methodology for raw material, water, energy, and nutrient content. PEF technology fulfils significant needs for sustainable food processing as requires fewer resources to produce quantities of existing foods that are nutritionally suitable for advancing health and wellbeing, long shelf lives, and transportable.
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•PEF contributes to food security & safety, nutritional security, energy & water resources.•PEF reduced cost & energy reduction along with healthier recovery of food components.•Minimizing industrial waste and & toxicity as compared to conventional technologies.•The optimization of PEF protocols leads to sustainable environment and economy.
The development of techniques and methods for rapidly and reliably detecting and analysing food quality and safety products is of significance for the food industry. Traditional machine learning ...algorithms based on handcrafted features normally have poor performance due to their limited representation capacity for complex food characteristics. Recently, the convolutional neural network (CNN) emerges as an effective and potential tool for feature extraction, which is considered the most popular architecture of deep learning and has been increasingly applied for the detection and analysis of complex food matrices.
In the current review, the structure of CNN, the method of feature extraction based on 1-D, 2-D and 3-D CNN models, and multi-feature aggregation methods are introduced. Applications of CNN as a depth feature extractor for detecting and analyzing complex food matrices are discussed, including meat and aquatic products, cereals and cereal products, fruits and vegetables, and others. In addition, data sources, model architecture and overall performance of CNN with other existing methods are compared, and trends of future studies on applying CNN for food detection and analysis are also highlighted.
CNN combined with nondestructive detection techniques and computer vision system show great potential for effectively and efficiently detecting and analysing complex food matrices, and the features based on CNN show better performance and outperform the features handcrafted or those extracted by machine learning algorithms. Although there still remains some challenges in using CNN, it is expected that CNN models will be deployed on mobile devices for real-time detection and analysis of food matrices in future.
•The principle and architectures of convolutional neural network are presented.•Feature extraction methods based on convolutional neural network are investigated.•Recent applications of convolutional neural network in food are summarized.•Challenges and future work of convolutional neural network are discussed.
•Current advances and perspectives of smartphone-assisted biosensors towards foodborne pathogens are proposed.•Role of nanotechnology in smartphone-assisted biosensors is elucidated.•The recognition ...modes for targeting foodborne pathogens are described.•The smartphone POC platforms in foodborne pathogens detection are discussed.
Pathogens are one of the supreme threats for the public health around the world in food supply chain. The on-site monitoring is an emerging trend for screening pathogens during the food processing and preserving. Traditional analytical tools have been unable to satisfy the current demands. Smartphones have enormous potentials for achieving on-site detection of foodborne pathogens, with intrinsic advantages such as small size, high accessibility, fast processing speed, and powerful imaging capacity. This review aims to synthesize the current advances in smartphone-assisted biosensors (SABs) for sensing foodborne pathogens, and briefly put forward the problem that consist in the research. We present the role of nanotechnology and recognition modes targeting foodborne pathogens in SABs, and discuss the signal conversion platforms coupling with smartphone. The challenges and perspectives in SABs are also proposed. The smartphone analytics area is moving forward, and it much be subject to careful quality standards and validation.
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