An account of the occurrence of residues from veterinary drugs and contaminants in animal-derived products: a case study on Brazilian supply chains.

Brazil plays an important role in ensuring its position on the international market by assuring high food safety standards for its products, and all products should meet the requirements for residues from veterinary drugs and contaminants in animal products. Statutory monitoring provides insights into the compliance of the Brazilian industry regarding these legal requirements. The objective of this study was to provide insight into the safety of Brazilian animal products by reporting the occurrence of residues from veterinary drugs and contaminants according to an analysis of an 11-year report published by the Brazilian Ministry of Agriculture, Livestock and Food Supply (MAPA). Between 2010 and 2021, 166,647 samples from animal-derived products were analyzed in Brazil, and 624 of those samples were non-compliant (0.37%) exceeding maximum residue limits (>MRLs) or showed the presence of prohibited substances. The most common types of substances found in the non-compliant samples were heavy metals, parasiticides, and antimicrobials, accounting for 82% of all documents from the MAPA. Among Brazilian products, the challenge related to occurrence of substances varied across the food supply chain, with highest incidence rates observed in the fish chain, followed by eggs, milk, equids, sheep/goat, honey, bovine, swine, and broilers chains in decreasing order. Considering the type of substance, heavy metals were found to be more prevalent in fish products, mainly arsenic in wild fish. The prevalence of contaminants and heavy metals decreased, while that of veterinary drugs increased in Brazilian products from 2010 to 2021. From these results, it can be concluded that the number of accidental incidents including those associated with environmental contaminants decreased over the last decade, opposed to those involving human adversaries and deliberate illegal actions, such as the abuse of veterinary drugs, increased. Future monitoring plans need to take this paradigm shift into account.

Fluorescence lifetime imaging microscopy as a tool to characterize spice powder variations for quality and authenticity purposes: A ginger case study.

Spices are usually ground for applications and the resulting particle size of the powders is an important product attribute in view of the release of flavour. However, inhomogeneity of the original material may lead to variations in the physicochemical characteristics of the particles. This variation and its linkage to particle size may be examined by particular imaging techniques. This study aimed to explore the potential of Fluorescence Lifetime Imaging Microscopy (FLIM) to characterize spice powders according to particle size variations and correlation with their pigment contents to reveal the chemical information contained within the FLIM data. Ginger powder was used as a representative powder model. The FLIM profiles of the individual samples and populations revealed that FLIM coupled with the phasor approach has the capacity to characterize spice powder according to particle size. Meanwhile, Principal Component Analysis of pre-processed FLIM data revealed clustering of particle size groups. Further correlation analysis between the pigment compound contents and FLIM data of the ginger powders indicated that FLIM reflected chemical information of ginger powder and was able to visualize endogenous fluorophores. The current study revealed the potential of FLIM to characterize ginger powder particles. This approach may be extrapolated to other spice powder products. The new knowledge is a step further in paving the way for the application of innovative techniques, already prevalent in other domains, to food quality and authentication.

Interpreting the variation in particle size of ground spice by high-resolution visual and spectral imaging: A ginger case study.

High-resolution (HR) visual imaging and spectral imaging are common computer vision-based techniques used for food quality analysis and/or authentication based on the interaction of light and material surface and/or composition. The particle size of ground spices is an important morphological feature that affects the physico-chemical properties of food products containing such particles. This study aimed to interpret the impact of particle size of ground spice on its HR visual profile and spectral imaging profile using ginger powder as a representative spice powder model. The results revealed an increase in the light reflection with the decrease of particle size of ginger powder, which was manifested by the lighter colour (higher percentage of the colour code with lighter yellow colour) of the HR visual image and stronger reflection with spectral imaging. The study also revealed that, in spectral imaging, the influence of the particle size of ginger powder increased with rising wavelengths. Finally, the results indicated a relationship between spectral wavelengths, ginger particle size, and other natural variables of the products which might be generated from cultivation to processing. Ultimately, the impact of natural variables arising during the food production process on the physico-chemical properties of the product should be fully considered or even additionally evaluated prior to the application of specific food quality and/or authentication analytical techniques.

A sense of ginger fraud: prevalence and deconstruction of the China-European union supply chain.

As an important spice, ginger has been widely distributed in the Chinese and the European Union (EU) markets, the two largest trading areas, in various forms. The ginger supply chain between China and the EU is long and complex, providing opportunities for fraudsters to deceive consumers. However, limited attention has been given to food fraud in ginger, and there is a lack of research on this topic. In this review, ginger was used as an example for interpreting the fraud issues within low-priced and high-trade volume spice products. This review aims to summarize the open access information from food and food fraud databases, literature, and stakeholders about ginger fraud, and to map, deconstruct and analyse the food fraud vulnerability in the supply chain. In addition, potential testing strategies to detect ginger fraud were also discussed. The investigation of food fraud databases, a semi-structured literature review and online interviews with stakeholders revealed that adulteration is the major fraud type in ginger products. And the most vulnerable ginger products are ground ginger and finely processed ginger. The ginger supply chain from China to the EU comprises nine stages and is medium vulnerable to food fraud, both in regard to opportunities and motivational drivers. To ensure the integrity of the ginger supply chain, there is a need to apply fraud vulnerability tools in the companies of the industry. In addition, screening and confirmatory techniques based on the characteristics of ginger should be utilised for monitoring fraud issues in the supply chain.

Identification of milk from different animal and plant sources by desorption electrospray ionisation high-resolution mass spectrometry (DESI-MS).

This study used desorption electrospray ionisation mass spectrometry (DESI-MS) to analyse and detect and classify biomarkers in five different animal and plant sources of milk for the first time. A range of differences in terms of features was observed in the spectra of cow milk, goat milk, camel milk, soya milk, and oat milk. Chemometric modelling was then used to classify the mass spectra data, enabling unique or significant markers for each milk source to be identified. The classification of different milk sources was achieved with a cross-validation percentage rate of 100% through linear discriminate analysis (LDA) with high sensitivity to adulteration (0.1-5% v/v). The DESI-MS results from the milk samples analysed show the methodology to have high classification accuracy, and in the absence of complex sample clean-up which is often associated with authenticity testing, to be a rapid and efficient approach for milk fraud control.

Spatial-Temporal Event Analysis as a Prospective Approach for Signalling Emerging Food Fraud-Related Anomalies in Supply Chains.

One of the pillars on which food traceability systems are based is the unique identification and recording of products and batches along the supply chain. Patterns of these identification codes in time and place may provide useful information on emerging food frauds. The scanning of codes on food packaging by users results in interesting spatial-temporal datasets. The analysis of these data using artificial intelligence could advance current food fraud detection approaches. Spatial-temporal patterns of the scanned codes could reveal emerging anomalies in supply chains as a result of food fraud in the chain. These patterns have not been studied yet, but in other areas, such as biology, medicine, credit card fraud, etc., parallel approaches have been developed, and are discussed in this paper. This paper projects these approaches for transfer and implementation in food supply chains in view of future applications for early warning of emerging food frauds.

Handheld Devices for Food Authentication and Their Applications: A Review.

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.

Preliminary Study on Tracing the Origin and Exploring the Relations between Growing Conditions and Isotopic and Elemental Fingerprints of Organic and Conventional Cavendish Bananas (Musa spp.).

The stable isotopic ratios and elemental compositions of 120 banana samples, Musa spp. (AAA Group, Cavendish Subgroup) cultivar Williams, collected from six countries (Colombia, Costa Rica, Dominica Republic, Ecuador, Panama, Peru), were determined by isotope ratio mass spectrometry and inductively coupled plasma mass spectrometry. Growing conditions like altitude, temperature, rainfall and production system (organic or conventional cultivation) were obtained from the sampling farms. Principal component analysis (PCA) revealed separation of the farms based on geographical origin and production system. The results showed a significant difference in the stable isotopic ratios (δ13C, δ15N, δ18O) and elemental compositions (Al, Ba, Cu, Fe, Mn, Mo, Ni, Rb) of the pulp and peel samples. Furthermore, δ15N was found to be a good marker for organically produced bananas. A correlation analysis was conducted to show the linkage of growing conditions and compositional attributes. The δ13C of pulp and peel were mainly negatively correlated with the rainfall, while δ18O was moderately positively (R values ~0.5) correlated with altitude and temperature. A moderate correlation was also found between temperature and elements such as Ba, Fe, Mn, Ni and Sr in the pulp and peel samples. The PCA results and correlation analysis suggested that the differences of banana compositions were combined effects of geographical factors and production systems. Ultimately, the findings contribute towards understanding the compositional differences of bananas due to different growing conditions and production systems linked to a defined origin; thereby offering a tool to support the traceability of commercial fruits.

Which Company Characteristics Make a Food Business at Risk for Food Fraud?

Fraud can happen to any food business, but some sectors show more historical evidence of food fraud than others. This may be due to particular company characteristics that affect a company's level of vulnerability. In the current study, we examined the relevance of the industry segment, business size, and location of food businesses on their food fraud vulnerabilities. Over 8000 food fraud vulnerability self-assessments conducted by food businesses active in 20 industry segments located in five continents were collected and the data analyzed. Results revealed that a company's industry segment (chain and tier) affects its fraud vulnerability greatly and to a larger extent than the size of the business. The effect of industry segment on fraud vulnerability appears fairly similar across continents, whereas the effect of business size exhibits large geographical variation. The results demonstrate that those involved in animal product supply chains and end of chain nodes (catering, retail) are most vulnerable, and so are larger businesses, and businesses located in Africa and Asia. Current results imply that company characteristics are important determinants of the level of fraud vulnerability, and they may be used reversely in the future, i.e., as predictors of vulnerability.

Broadband acoustic resonance dissolution spectroscopy as a rapid tool for the compositional analysis of food powders: A case study of edible salts.

Broadband acoustic resonance dissolution spectroscopy (BARDS) is a novel method that can be used for the analysis of food-based powders, which are mainly characterized by their composition and particle morphology. This study aimed to evaluate BARDS for the compositional analysis of food powders. The changes in the BARDS spectra due to the changes in composition and particle morphology of fifteen salt mixtures (constituting of NaCl, KCl, and MgCl2) in five particle size ranges were comprehensively studied. Moreover, different regression methods were utilized to estimate each mixture component content. The results revealed that the average time-frequency spectra of each mixture in a certain particle size class were highly distinct and allowed discrimination from others. The unique spectra of each salt mixture originated from the specific dissolution rate and degassing effect of each constitutive compound. Finally, the accurate prediction of each mixture component content confirmed the consistency and efficiency of the method.

Novel Application of Near-infrared Spectroscopy and Chemometrics Approach for Detection of Lime Juice Adulteration.

The aim of this study is to investigate the novel application of a handheld near infra-red spectrophotometer coupled with classification methodologies as a screening approach in detection of adulterated lime juices. For this purpose, a miniaturized near infra-red spectrophotometer (Tellspec®) in the spectral range of 900-1700 nm was used. Three diffuse reflectance spectra of 31 pure lime juices were collected from Jahrom, Iran and 25 adulterated juices were acquired. Principal component analysis was almost able to generate two clusters. Partial least square discriminant analysis and k-nearest neighbors algorithms with different spectral preprocessing techniques were applied as predictive models. In the partial least squares discriminant analysis, the most accurate prediction was obtained with SNV transforming. The generated model was able to classify juices with an accuracy of 88% and the Matthew's correlation coefficient value of 0.75 in the external validation set. In the k-NN model, the highest accuracy and Matthew's correlation coefficient in the test set (88% and 0.76, respectively) was obtained with multiplicative signal correction followed by 2nd-order derivative and 5th nearest neighbor. The results of this preliminary study provided promising evidence of the potential of the handheld near infra-red spectrometer and machine learning methods for rapid detection of lime juice adulteration. Since a limited number of the samples were used in the current study, more lime juice samples from a wider range of variability need to be analyzed in order to increase the robustness of the generated models and to confirm the promising results achieved in this study.

Study on the Relations between Hyperspectral Images of Bananas (Musa spp.) from Different Countries, Their Compositional Traits and Growing Conditions.

Bananas are some of the most popular fruits around the world. However, there is limited research that explores hyperspectral imaging of bananas and its relationship with the chemical composition and growing conditions. In the study, the relations that exist between the visible near-infrared hyperspectral reflectance imaging data in the 400-1000 nm range of the bananas collected from different countries, the compositional traits and local growing conditions (altitude, temperature and rainfall) and production management (organic/conventional) were explored. The main compositional traits included moisture, starch, dietary fibre, protein, carotene content and the CIE L*a*b* colour values were also determined. The principal component analysis showed the preliminary separation of bananas from different geographical origins and production systems. The compositional and spectral data revealed positively and negatively moderate correlations (r around ±0.50, p < 0.05) between the carotene, starch content, and colour values (a*, b*) on the one hand and the wavelength ranges 405-525 nm, 615-645 nm, 885-985 nm on the other hand. Since the variation in composition and colour values were related to rainfall and temperature, the spectral information is likely also influenced by the growing conditions. The results could be useful to the industry for the improvement of banana quality and traceability.

Opportunities for fraudsters: When would profitable milk adulterations go unnoticed by common, standardized FTIR measurements?

Milk is regarded as one of the top food products susceptible to adulteration where its valuable components are specifically identified as high-risk indicators for milk fraud. The current study explores the impact of common milk adulterants on the apparent compositional parameters of milk from the Dutch market as measured by standardized Fourier transform infrared (FTIR) spectroscopy. More precisely, it examines the detectability of these adulterants at various concentration levels using the compositional parameters individually, in a univariate manner, and together in a multivariate approach. In this study we used measured boundaries but also more practical variance-adjusted boundaries to set thresholds for detection of adulteration. The potential economic impact of these adulterations under a milk payment scheme is also evaluated. Twenty-four substances were used to produce various categories of milk adulterations, each at four concentration levels. These substances comprised five protein-rich adulterants, five nitrogen-based adulterants, seven carbohydrate-based adulterants, six preservatives and water, resulting in a set of 360 samples to be analysed. The results showed that the addition of protein-rich adulterants, as well as dicyandiamide and melamine, increased the apparent protein content, while the addition of carbohydrate-based adulterants, whey protein isolate, and skimmed milk powder, increased the apparent lactose content. When considering the compositional parameters univariately, especially protein- and nitrogen-based adulterants did not raise a flag of unusual apparent concentrations at lower concentration levels. Addition of preservatives also went unnoticed. The multivariate approach did not improve the level of detection. Regarding the potential profit of milk adulteration, whey protein and corn starch seem particularly interesting. Combining the artificial inflation of valuable components, the resulting potential profit, and the gaps in detection, it appears that the whey protein isolates deserve particular attention when thinking like a criminal.

Prevalence of Milk Fraud in the Chinese Market and its Relationship with Fraud Vulnerabilities in the Chain.

This study aimed to assess the prevalence of ultra-high-temperature (UHT) processed milk samples suspected of being adulterated on the Chinese market and, subsequently, relate their geographical origin to the earlier determined fraud vulnerability. A total of 52 UHT milk samples purchased from the Chinese market were measured to detect possible anomalies. The milk compositional features were determined by standardized Fourier transform-infrared spectroscopy, and the detection limits for common milk adulterations were investigated. The results showed that twelve of the analysed milk samples (23%) were suspected of having quality or fraud-related issues, while one sample of these was highly suspected of being adulterated (diluted with water). Proportionally, more suspected samples were determined among milks produced in the Central-Northern and Eastern areas of China than in those from the North-Western and North-Eastern areas, while those from the South were in between. Combining the earlier collected results on fraud vulnerability in the Chinese milk chains, it appears that increased fraud prevalence relates to poorer business relationships and lack of adequate managerial controls. Since very few opportunities and motivations differ consistently across high and low-prevalence areas, primarily the improvement of control measures can help to mitigate food fraud in the Chinese milk supply chains.

From Extra Virgin Olive Oil to Refined Products: Intensity and Balance Shifts of the Volatile Compounds versus Odor.

To explore relationships between the volatile organic compounds (VOCs) of different grades of olive oils (OOs) (extra virgin olive oil (EVOO), refined olive oil (ROO), and pomace olive oil (POO)) and odor quality, VOCs were measured in the headspace of the oils by proton transfer reaction quadrupole ion guide time-of-flight mass spectrometry. The concentrations of most VOCs differed significantly between the grades (EVOO>ROO>POO), whereas the abundance of m/z 47.012 (formic acid), m/z 49.016 (fragments), m/z 49.027 (fragments), and m/z 115.111 (heptanal/heptanone) increased in that order. Although the refined oils had considerably lower VOC abundance, the extent of the decline varied with the VOCs. This results in differences in VOCs proportions. The high VOC abundance in the EVOO headspace in comparison to ROO and POO results in a richer and more complex odor. The identified C5-C6 compounds are expected to contribute mainly to the green odor notes, while the identified C1-C4 and C7-C15 are mainly responsible for odor defects of OOs. Current results reveal that processing strongly affects both the quantitative and relative abundance of the VOCs and, therefore, the odor quality of the various grades of OOs.

Feeding fiction: Fraud vulnerability in the food service industry.

This study examines fraud vulnerability in the food service industry; identifies underlying fraud vulnerability factors; and studies the differences in fraud vulnerability between casual dining restaurants, fine dining restaurants and mass caterers for four product groups. Vulnerability was assessed by an adapted SSAFE food fraud vulnerability assessment, tailored to the food service sector situation. The 15 food service operators rated high vulnerability for 40% of the fraud indicators. This is considerably more than food manufacturers, wholesalers and retailers did previously. In particular, more opportunities and fewer controls were noted. Overall fraud vulnerability was more determined by the type of food service operator than by the type of food product. Casual dining restaurants appeared most vulnerable, followed by fine dining restaurants. Mass caterers seemed the least vulnerable operators, because they had more adequate food fraud controls in place. Considering its high vulnerability, reinforcement of mitigation measures in the food service industry is urgently recommended.

Linking growing conditions to stable isotope ratios and elemental compositions of Costa Rican bananas (Musa spp.).

Traceability of agricultural produce is getting increasingly important for numerous reasons including marketing, certification, and food safety. Globally, banana (Musa spp.) with its high nutritional value and easy accessibility, is a popular fruit among consumers. Bananas are produced throughout the (sub-)tropics under a wide range of environmental conditions. Environmental conditions could influence the composition of bananas. Understanding the effect of these conditions on fruit composition provides a way of increasing the fruit's traceability and linking it to its origin - a crucial aspect for the increasing global supply chain. In this study, we examined the influence of growing conditions on the isotopic and elemental composition of bananas produced in 15 Costa Rican farms. A total of 88 bananas (peel and pulp) were collected from the farms and analysed for isotopic signatures (δ13C, δ15N, and δ18O) and elemental compositions. The growing conditions were characterized in terms of climate, topography and soil conditions. The isotopic ratios differed significantly between groups of farms. The δ13C and δ15N values were mainly influenced by soil types, while rainfall and temperatures related more to the δ18O values. The elemental compositions of the bananas were primarily influenced by the local rainfall and soil types, while the geographical origin could be distinguished using principal component analysis. The overall results link the growing conditions to the isotopic and elemental compositions of bananas, thereby also providing a way to trace its origin.

Integrity of Organic Foods and Their Suppliers: Fraud Vulnerability Across Chains.

Organic foods are frequently targeted by fraudsters. Examination of underlying factors helps to reduce fraud vulnerability and to prevent fraud. In this study, the fraud vulnerability of five actors from each of four chains were examined using the SSAFE food fraud vulnerability assessment tool: the organic banana, egg, olive oil and pork supply chains. The organic chains appeared slightly less vulnerable than conventional chains due to fewer opportunities for fraud and the more adequate controls being present. On the other hand, organic chains were associated with enhanced vulnerability resulting from cultural and behavioral drivers. Generally, actors in the organic olive oil and pork chains were more vulnerable than those from the banana and egg chains. However, high risk actors were not limited to particular chains. Across the whole group of actors in organic chains, three groups in terms of cultural/behavioral drivers were distinguished: a low vulnerability group, a group facing more external threats and a group presenting fraud vulnerability in general and in particular from within their own company. Ethical business culture and criminal history scores of businesses correlated significantly. This implies that the climate in a company is an important factor to consider when estimating the exposure of businesses to food fraud.

Dairy farming system markers: The correlation of forage and milk fatty acid profiles from organic, pasture and conventional systems in the Netherlands.

The relationships between the fatty acid (FA) composition in forage and milk (F&M) from different dairy systems were investigated. Eighty milk samples and 91 forage samples were collected from 40 farms (19 organic, 11 pasture and 10 conventional) in the Netherlands, during winter and summer. The FA profiles of F&M samples were measured with gas chromatography. The results showed that the F&M of organic farms were significantly differentiated from the F&M of other farms, both in summer and winter. The differences are likely due to the different grazing strategies in summer and different forage composition in winter. The Pearson's correlation results showed the specific relationship between individual FAs in forages and related milk. A PLS-DA model was applied to classify all milks samples, resulting in 87.5% and 83.3% correct classifications of training set and validation set.

A sound approach: Exploring a rapid and non-destructive ultrasonic pulse echo system for vegetable oils characterization.

A rapid and non-destructive ultrasonic pulse echo system was developed for vegetable oils characterization. To understand the differences in the ultrasonic properties of the oils, physical traits, such as their viscosity and density, were related to the ultrasonic data. In turn, these physical traits were correlated with the fatty acid compositions of the oils. Eighty oil samples, including 30 extra virgin olive oil (EVOO), 15 refined olive oil, 15 pomace olive oil, 10 rapeseed oil, 5 sunflower oil and 5 peanut oil samples, were analysed for their sound properties, viscosities, densities and fatty acid compositions. It was observed that the ultrasonic velocity of EVOO decreased linearly with increase in temperature, the temperature coefficient of ultrasonic velocity in EVOO was -2.92 m·s-1·°C-1. The ultrasonic velocity of EVOO (1453 ±â€¯2 m/s) differed significantly from those of pomace olive oil and the oils of other botanical origin, but not from the velocity of refined olive oil. Ultrasonic velocity was positively correlated with the density and negatively correlated with the viscosity of the oils. The higher density and lower viscosity of the oils were in turn related to a higher unsaturation degree of the oils. Hence, oils with a higher proportion of unsaturated fat present higher densities and lower viscosities, which resulted in higher ultrasonic velocity values. Ultrasonic measurements allow rapid, non-destructive analysis, and this first application for characterization of these oils is promising.