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Extra-virgin olive oil (EVOO) is subjected to different frauds. This work aimed at integrating the untargeted phenolic and sterol signatures with supervised multivariate discriminant analysis (OPLS-DA) and Artificial Neural Networks (ANN) for tracing the authenticity (as a function of variety, origin, and the blending) of Taggiasca Ligure, a renowned Italian EVOO. Overall, 408 samples from three consecutive growing seasons were used. Despite the cultivar, season, growth altitude, and geographical origin were all contributing to phytochemical profile, OPLS-DA models allowed identifying specific markers of authenticity. Cholesterol-derivatives and phenolics (tyrosols and oleuropeins, stilbenes, lignans, phenolic acids, and flavonoids) were the best markers, based on statistics. Thereafter, ANN was used to discriminate authentic Taggiasca, and the sensitivity was 100% (32/32) thus indicating an excellent classification. Our results strengthen the concept of "terroir" for EVOO and indicate that profiling sterols and phenolics can support EVOO integrity if adequate data treatments are adopted.

Given the need to prevent food fraud within the international food supply chain and the current lack of research on food integrity, in this paper, the relation between the organizational food integrity climate and employees’ food integrity behavior is examined to understand the role of the individual or psychological dimension in food integrity. The construct of food integrity behavior was introduced and defined, and the conceptual model of the food integrity climate in relation to food integrity behavior was elaborated along with study variables and hypotheses. In the proposed model, the potential moderating role of employees’ psychological well-being (i.e., burnout and job stress) was analyzed, and two mediating variables were also proposed (i.e., knowledge and motivation) which both could explain how the prevailing food integrity climate might influence employees’ food integrity behavior. Data was collected through convenience sampling in four Belgian food companies with a total of 118 participating employees through a self-assessment questionnaire. Based on the statistical analysis, it was concluded that a well-developed organizational food integrity climate promotes positive employees’ food integrity behavior. Specifically, results of this semi-quantitative study demonstrated that the companies’ food integrity climate is positively related to the employees’ food integrity behavior both directly and indirectly, and that food integrity knowledge is a partial mediator in the relation between food integrity climate and food integrity behavior, while food integrity motivation is a full mediator. Study limitations and implications are also discussed.

Current food safety technological solutions and management systems need to be complemented with more-comprehensive food integrity tools and strategies to address, control and prevent food fraud throughout the global supply chain. In this paper, the novel construct of food integrity culture is introduced. Its definition is presented and its operationalization was investigated and tested through method triangulation in a Belgian large-scale meat distribution company. The three tools applied in the proposed method triangulation are: (1) the food integrity climate (FIC) self-assessment tool which acknowledges a company's food integrity climate through employees' perceptions (human dimension), (2) a key performance indicators interview which verified objectively the employees' perceptions through an on-site observation (operational dimension), and (3) a food fraud vulnerability diagnostic tool (SSAFE) which evaluates the company's opportunities and motivations to commit fraud in opposition to the organizational control measures to counteract it (technical and managerial dimension). Since food integrity culture encompasses technical, managerial and operational aspects of a food organization as well as human factors, the three tools applied in the method triangulation highlight different complementary aspects of food integrity culture, such as subjective versus objective and individual versus organizational perspectives. Results confirmed the hypothesis that in a company with a high perceived food integrity climate and high food integrity performance, an overall low food fraud vulnerability is found. To achieve a consolidated food integrity culture, food companies should include within their current food safety management systems regular assessments of their food integrity climate, food integrity performance as well as of potential food fraud vulnerabilities, and managing such human, operational, technical and managerial aspects as strategies of an integrated system.

This review summarises miniaturised technologies, commercially available devices, and device applications for food authentication or measurement of features that could potentially be used for authentication. We first focus on the handheld technologies and their generic characteristics: (1) technology types available, (2) their design and mode of operation, and (3) data handling and output systems. Subsequently, applications are reviewed according to commodity type for products of animal and plant origin. The 150 applications of commercial, handheld devices involve a large variety of technologies, such as various types of spectroscopy, imaging, and sensor arrays. The majority of applications, ~60%, aim at food products of plant origin. The technologies are not specifically aimed at certain commodities or product features, and no single technology can be applied for authentication of all commodities. Nevertheless, many useful applications have been developed for many food commodities. However, the use of these applications in practice is still in its infancy. This is largely because for each single application, new spectral databases need to be built and maintained. Therefore, apart from developing applications, a focus on sharing and re-use of data and calibration transfers is pivotal to remove this bottleneck and to increase the implementation of these technologies in practice.

Current scientific research and industry guidelines focus on food safety, aiming to reduce unintentional food contaminations through technological and managerial measures. Due to the deceptive nature of food fraud, the fight to prevent intentional food adulteration and counterfeiting threats requires an approach that goes beyond the common food safety-based strategies and falls into the sphere of food integrity. With food integrity being an emerging discipline, a definition was proposed and the concept of food integrity climate was introduced. A food integrity climate (FIC) self-assessment tool in the form of a questionnaire, with twenty indicators and a five-point Likert rating scale was developed, expert-validated, and tested in practice in a large-scale meat distribution company. The questionnaire was designed to measure the performance level of food integrity in food businesses along the supply chain through managers’ and operators’ perceptions. Minor but interesting differences were found in the food integrity climate perceived between managers and operators as well as among the company’s affiliates. The tool helps food businesses to get a deeper insight on the human dimension behind food integrity through the assessment of five climate components in relation to four food integrity elements, identifying strengths and weaknesses regarding a company’s food integrity climate.

Parmigiano Reggiano is a hard cheese with a Protected Designation of Origin (PDO) certification that also applies to the grated product. The percentage of rind in grated Parmigiano Reggiano is regulated by the PDO production Specification and must not exceed the limit of 18% (w/w). The present study evaluates the potential of an untargeted foodomics approach to detect anomalous inclusions of rind in grated Parmigiano Reggiano cheese. In particular, a combined metabolomics and peptidomics approach was used to detect potential markers of counterfeits (rind > 18%). In the framework of realistic food integrity purposes, non-Parmigiano Reggiano grated samples and different ripening times were also considered. Untargeted metabolomics allowed detecting 347 compounds, with a prevalence of amino acids and peptide derivatives, followed by fatty acyls and other compounds (such as lactones, ketones, and aldehydes) typically related to proteolysis and lipolysis events. Overall, the unsupervised multivariate statistics showed that the ripening time plays a hierarchically higher impact than rind inclusion in determining the main differences in the chemical profiles detected. Interestingly, supervised statistics highlighted distinctive markers for ripening time and rind inclusion, with only 16 common discriminant compounds being shared between the two conditions. The best markers of rind inclusion > 18% were 2-hydroxyadenine (VIP score = 1.937; AUC value = 0.83) and the amino acid derivatives argininic acid (VIP score = 1.462; AUC value = 0.75) and 5-hydroxyindole acetaldehyde (VIP score = 1.710; AUC value = 0.86). Interestingly, the medium-chain aldehyde 4-hydroperoxy-2-nonenal was a common marker of both ripening time and anomalous rind inclusion (>18%), likely arising from the lipid oxidation processes. Finally, among potential marker peptides of rind inclusion, the alpha-S1 casein proteolytic product (F)FVAPFPEVFGK(E) could be identified.

One of the biggest challenges facing the food industry is assuring food integrity. Dealing with complex food integrity issues requires a multi-dimensional approach. Preventive actions and early reactive responses are key for the food supply chain. Information sharing could facilitate the detection and prevention of food integrity issues. This study investigates attitudes towards a food integrity information sharing system (FI-ISS) among stakeholders in the European food supply chain. Insights into stakeholders&rsquo, interest in participating and their conditions for joining an FI-ISS are assessed. The stakeholder consultation consisted of three rounds. During the first round, a total of 143 food industry stakeholders&mdash, covering all major food sectors susceptible to food integrity issues&mdash, participated in an online quantitative survey between November 2017 and February 2018. The second round, an online qualitative feedback survey in which the findings were presented, received feedback from 61 stakeholders from the food industry, food safety authorities and the science community. Finally, 37 stakeholders discussed the results in further detail during an interactive workshop in May 2018. Three distinct groups of industry stakeholders were identified based on reported frequency of occurrence and likelihood of detecting food integrity issues. Food industry stakeholders strongly support the concept of an FI-ISS, with an attitude score of 4.49 (standard deviation (S.D.) = 0.57) on a 5-point scale, and their willingness to participate is accordingly high (81%). Consensus exists regarding the advantages an FI-ISS can yield towards detection and prevention. A stakeholder&rsquo, s perception of the advantages was identified as a predictor of their intention to join an FI-ISS, while their perception of the disadvantages and the perceived risk of food integrity issues were not. Medium-sized companies perceive the current detection of food integrity issues as less likely compared to smaller and large companies. Interestingly, medium-sized companies also have lower intentions to join an FI-ISS. Four key success factors for an FI-ISS are defined, more specifically with regards to (1) the actors to be involved in a system, (2) the information to be shared, (3) the third party to manage the FI-ISS and (4) the role of food safety authorities. Reactions diverged concerning the required level of transparency, the type of data that stakeholders might be willing to share in an FI-ISS and the role authorities can have within an FI-ISS.

Saffron is a high-quality and expensive spice being widely subjected to adulteration. An UHPLC-ESI/QTOF-MS metabolomic-based approach was therefore used to investigate the discrimination potential between adulterated (added with different percentage of other parts of the flower) and authentic saffron, as well as to trace its geographical origin. Both unsupervised (hierarchical clustering) and supervised OPLS-DA multivariate statistics allowed discriminating authentic saffron from styles added of other floral components, as well as PDO (Protected Designation of Origin) vs non PDO saffron samples according to their chemical fingerprints. The proposed markers were then validated through ROC curves. Anthocyanins and glycosidic flavonols were the best markers of the styles' adulteration. However, other flavonoids (mainly free flavonols and flavones), together with protocatechuic aldehyde and isomeric forms of hydroxybenzoic acid, were also validated as markers for the discrimination of PDO vs non PDO saffron samples. This work outlines the potential of untargeted metabolomics based on UHPLC-ESI/QTOF mass spectrometry for saffron authenticity and traceability.

Background Food chains have changed dramatically due to technical and demographic changes over the last decades. Although efforts are made to ensure high quality and integrity, food-borne outbreaks and food scandals still happen to an undesired extent. Scope and approach This commentary paper aims to give insight in the current approach in the European food control and audit system, the underestimation of complexity and the role of trust in food control and auditing. Furthermore, the need for complex systems thinking in risk-based auditing is discussed and a framework to structure complex system risk-based auditing is proposed. Key findings and conclusions The current food control system seems to cause a reactive vicious cycle, which leads to more and stricter regulations and standards on every level. A new paradigm in risk-based auditing is needed that acknowledges the behaviour of complex systems to ensure trust along the food chain. The proposed framework for complex system risk-based auditing may enable a systematic analysis of audit triggers, audit goals and context characteristics suggesting multiple methods for risk analysis, as basis for the questions on when, how, what, and whom to audit.