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Food fraud is common in many supply chains. Apart from paper trails, the implementation of control measures is key to combat those fraudulent activities, also in the banana supply chains. A first step in this process is to bridge the knowledge gap between origin and bananas, between the geographical/production origin factors on the one hand and the chemical and physical signatures of bananas on the other hand. There is particularly a need for rapid, low-cost methodologies that can be used to control fraud. In this study, spectral features of Cavendish bananas of different geographical origins and production systems were deciphered using near infrared (NIR) spectroscopy. Bananas from six countries, i.e., Columbia, Costa Rica, Dominica Republic, Ecuador, Panama, and Peru, were assessed. The NIR spectral data were correlated with proximate compositional data to interpret the spectral differences observed. Bananas from Dominican Republic and Ecuadorian farms showed distinct NIR signatures in comparison to the bananas of other origins. These differences appeared to be correlated with their (higher) starch contents and other compositional characteristics. Organic bananas revealed more exceptional, differential proximate compositions than their conventional counterparts, but these differences were not clearly reflected in the NIR signatures. In conclusion, spectral and compositional signatures of bananas reflect certain origin aspects, and these findings can be used to develop authentication tools to assist in the control of the integrity of value chains.

Peanuts as raw materials are the cornerstone of the whole peanut industry. The quality traits of peanuts determine their market value and the characteristics of final products, such as peanut butters. However, the quality traits of peanuts vary extensively with variety, growing environment, storage condition, and maturity. Meanwhile, the quality traits of peanuts have profound influences on the characteristics of their derived peanut butters. In order to understand the impact of the varieties on the traits of peanuts and peanut butters and develop rapid determinations, the main aim of this thesis is to elucidate and comprehend distinct analytical signatures and relationships of various types of peanuts and derived peanut butters and develop rapid methods of evaluation and identification of peanuts by near-infrared spectroscopy (NIRS) combined with chemometrics and machine learning.In Chapter 2 and Chapter 3, the different analytical signatures of batch samples and single peanut kernel peanuts were measured by conventional methods (e.g. gas chromatography and high-performance anion-exchange chromatography). The results showed that the fatty acids (FAs) composition of high oleic acid peanuts (HOP) and regular peanuts differed significantly. The models established by portable NIRS had the same performance to identify HOP and quantitatively measure the major FAs in batch peanut samples compared with benchtop NIRS. Meanwhile, considering the internal (measured by laser confocal microscopy) and external characteristics (kernel size) of different single peanut varieties, a single peanut detection accessory was designed and equipped with portable NIRS to collect spectral data of single peanut kernels. Based on the established quantitative models, breeding experts could quickly analyse the fat, protein, sucrose, and amino acids contents in single peanut kernels.In Chapter 4, the relationships between peanuts and derived peanut butters were elucidated and the varieties were s

Recent food fraud incidents have highlighted the importance of fighting food fraud and thereby ensuring food integrity. Milk is reported as one of the most commonly adulterated foods in the world, hence there is a strong demand for the assurance of its integrity. Both technical and managerial approaches can help to combat food fraud and ensure the integrity of the milk supply chain. The Dutch and Chinese milk supply chains are different with regard to their structure, history of development, and historical evidence of fraud. Hence, this thesis aimed to elucidate and compare fraud vulnerabilities in the Dutch and Chinese milk supply chains, their underlying factors, and the relationship with fraud prevalence.Fraud vulnerabilities in the Dutch and Chinese supply chains were examined, and the similarities and differences between the tier groups were identified (Chapters 2 and 3). In general, both supply chains were rated as low to medium vulnerable to food fraud by its actors. The variation in fraud vulnerability among different tier groups, i.e. farmers, processors, and retailers, was relatively small in the Netherlands. When comparing Dutch farms of different management types, the organic farms appeared more vulnerable than their non-organic counterparts (Chapter 2). Unlike the Dutch milk supply chain, the difference in fraud vulnerability level between Chinese farmers and processors was larger. The farmers were the weaker link within the Chinese milk supply chain (Chapter 3). On average, Dutch and Chinese farmers reported a similar level of fraud vulnerability, but the Chinese farmers varied much more in their levels. The Dutch processors appeared slightly more vulnerable on average than their Chinese counterparts, but variation in both groups was similar.Following the profiling of fraud vulnerability of the milk supply chains, analytical methods for detection of milk adulteration were developed. Considering the diversity in milk composition, the authentication appr

The assessment of cocoa’s natural characteristics can be used to link cocoa beans and chocolate. Establishing a link between the raw material and the finished product is complicated not only because of complex characteristics of the supply chain but also because of the technology involved in the production and the composition of the ingredients. One may wonder why a link between raw material and the finished product is relevant. Nowadays, more and more attention is given to sustainability, pushing the cocoa manufacturers to take into account social, economic and environmental issues while producing. As a consequence, the demand in cocoa-importing countries for certified sustainable cocoa has increased considerably and is expected to show continuous growth over the next years. Moreover, more consumers have become increasingly aware of the existence of different cocoa varieties and their origins, and the market of specialty chocolates such as chocolates with single-origin bean, organic and fair-trade chocolate has largely grown in the last decades. The aforementioned trends in the chocolate sector and the growing concerns regarding food quality and safety led to a growing effort in the implementation of traceability systems. This trend has facilitated the need to verify and guarantee the origin of the cocoa beans along with the cocoa-chocolate supply chain and to establish a link between raw material and the finished product.For these reasons, the main objective of this thesis is to discover cocoa beans’ traits in terms of the botanical and geographical origin carried along the cocoa–chocolate supply chain. Compositional characteristics of botanical and geographical origin of cocoa beans after fermentation and drying, after manufacturing chocolate and during chocolate consumption were analysed. This information can be used to derive a link between raw material and the finished product, which in turn can be used to support traceability systems.To investigate the cocoa

Bij de productie van en handel in levensmiddelen is er regelmatig sprake van fraude. Dit is in strijd met de wet, resulteert in economische schade, en kan leiden tot voedselveiligheidsrisico’s. Er is daarom steeds meer aandacht voor het beheersen van fraude. Een van de manieren om beter met fraude om te gaan is door informatie over incidenten en risico-indicaties rond frauduleuze productie te delen. Als fraude-informatie per product of productcategorie beschikbaar is, kunnen afnemers gericht maatregelen nemen. Dit onderzoek richt zich op de mogelijke behoefte aan een voedselintegriteitsnetwerk in Nederland, een platform voor het delen van informatie over voedselfraudegevallen. We hebben daarvoor gekeken naar bestaande oplossingen in het buitenland en naar draagvlak in Nederland. In eerste instantie zijn drie grote retailorganisaties gepeild. Meer informatie over mogelijke fraudeincidenten kan helpen bij het maken van betere interne risicoanalyses voor verschillende voedselproducten en productgroepen. Retailers zijn geïnteresseerd als het platform iets toevoegt aan de bestaande informele onderlinge communicatie. Verder stelt men als voorwaarde dat er brede deelname is vanuit de keten, dat die deelname anoniem is en dat alleen bedrijven meedoen. CBL heeft al eerder belangstelling getoond en FNLI bespreekt het voorstel met haar deelnemers. Het Britse initiatief FIIN kan dienen als voorbeeld voor NL-FINE. Zij stellen echter geen data ter beschikking, alleen trendanalyses. Verder neemt FIIN alleen fraude op basis van lab testresultaten op. Beide aannames zijn waarschijnlijk niet van toepassing voor NL-FINE. In dit rapport hebben we verdere een eenvoudig datamodel voor het potentiële netwerk voorgesteld op basis van een aantal bestaande databases en een eerder opgesteld uniform model. Voor het vervolg zouden in 2021 de volgende activiteiten uitgevoerd kunnen worden. - Andere partijen in de keten polsen - Een stuurgroep inrichten om de belangen van de verschillende parti

With the globalisation of the food supply system, food fraud can have international impacts, sometimes with far-reaching and lethal consequences. Extra virgin olive oil (EVOO) is considered one of the most frequently reported commodities, suffering from fraud. Knowledge about risk factors and precise laboratory and broad on-site screening methods will help to combat fraud in the EVOO supply chain network. The main objectives of this thesis are to develop strategies to combat fraud in the EVOO supply chains through knowledge about weak spots and underlying risk factors and the development of novel detection methods.To achieve these goals, firstly, the EVOO supply chain was assessed for their vulnerability using the SSAFE food fraud vulnerability assessment tool. These assessments indicate that the EVOO supply chain is fairly vulnerable. B2B companies and retailers in the EVOO supply chain are more vulnerable to fraud than olive oil producers and food manufacturers due to the additional vulnerability related to opportunities in time and place and a lack of control measures. Fraud vulnerability across the EVOO supply chain was not only determined by the place of the actor in the chain (node), but also by the scale and location of the companies.Four novel methods were developed in this thesis for EVOO authentication. Monochloropropanediol (MCPD) esters and glycidyl esters (GEs) analysis by gas chromatography-tandem mass spectrometry (GC-MS/MS) was applied to defect EVOO adulteration with lower grade oils. The limit of fraud detection of lower grade olive oils in EVOO was 2% when using 3-MCPD esters, 5% for 2-MCPD esters and 13–14% for GEs. These results imply that the method is fairly useful for confirmatory analysis. However, 3-MCPD analysis by GC-MS/MS is currently a tedious and time-consuming method, it is not recommended to use this method to analyse a large number of suspect samples when a quick response is required. In addition, three rapid and non-destructive tec

Organic milk has been receiving more and more attention in recent years. However, it is also susceptible to fraud considering its high retail price and the strict requirements of organic production. Since the quality of milk is affected by many factors, such as seasons, environment, lactation stage, feed, cow breed, etc., it is challenging to distinguish organic milk from conventional milk. To ensure fair competition and consumer confidence, there is a strong need to confirm the identity of organic products including milk. Therefore, this study was carried out to elucidate the differences in characteristics, in terms of fatty acid (FA) and volatile organic compound (VOC) profiles, of organic milk and other milks, and to study their underlying causes.In Chapter 2 and Chapter 4, the FA profiles of different farm (raw) milks and retail milks were investigated by gas chromatography (GC). Both the types of silages and grazing management strategies in different dairy production systems impacted on the FA profiles of milks, where the impact of the latter one was more significant. Corresponding to this result for farm (raw) milks, the differences of the FA profiles of different milks have also been observed among retail milks. Hence, industrial processing and milk pooling did not erase all the characteristics of organic milks. However, due to the relatively flexible regulations of pasture milk, the differences between pasture retail milk and conventional retail milk were less significant than the differences between pasture raw milk and conventional raw milk.Similarly, the VOC profiles of raw milks and retail milks were analysed in Chapter 3 and Chapter 6. By using proton transfer reaction quadrupole mass spectrometry (PTR-(Quad)MS) and proton transfer reaction time of flight mass spectrometry (PTR-(ToF)MS), the characteristics of different milks in winter and summer were investigated. Similar to the results of FA analysis, the grazing management had a greater impact on VOC

The quality traits of peanuts (Arachis hypogaea L.) are fundamental to the whole peanut industry. However, many common analyses require the sample to be brought to the laboratory. Therefore, this research explores the feasibility of portable near-infrared spectroscopy combined with a single detection accessory to analyse the composition of peanuts in a single seed level quantitatively. The single detection accessory was specifically designed for spectral data collection considering the internal and external characteristics of single peanuts. Confocal laser scanning microscopy revealed that the oil body and protein body were randomly distributed at cell of single peanuts. The external characteristics of single peanuts were also determined and considered length (11.32–24.25 mm) and width (7.49–12.25 mm). The chemical compositional data (i.e. fat, sucrose, protein, and 16 amino acids) were determined by conventional wet-chemical methods and showed large variation. Principal component analysis on the compositional data showed that peanuts with higher fat contents usually have higher hydrophobic amino acids contents, lower sucrose contents, and lower protein contents. The composition prediction models of single peanuts were estimated using partial least squares regression models that were integrated with different spectral pre-treatments and validated by external sets. The results showed that the prediction models have good performance with a correlation coefficient above 0.88 (calibration) and 0.83 (prediction) and a residual prediction deviation above 1.5 except for a few indicators. Overall, the portable near-infrared spectroscopy offered reliable methods to assess the major components and amino acids quantitatively in a single peanut, which will improve the raw material quality in the peanut industry through the simultaneous and short-term determination of multiple indicators.

Aroma properties of spices are related to the volatile organic compounds (VOCs) present, which can provide distinct analytical signatures. The aim of the study was to examine similarity and diversity of VOC profiles of six common market spices (black/white pepper, chili paprika, cinnamon, nutmeg and saffron). The key volatiles were identified by PTR-TOFMS. Twelve samples per spice were subjected to PTR-Quadrupole MS (PTR-QMS) and Principal Component Analysis to compare the groups and examine diversity. With PTR-TOFMS, 101 volatile compounds were identified as total sum across all samples by mass and comparing them with literature data. Some spices comprised key character aroma compounds, e.g. cinnamaldehyde in cinnamon. For others, VOC groups, such as terpenes, acids and aldehydes topped the list. The PTR-QMS in combination with variables selection resulted in distinct PCA patterns for each spice. Variation within the spice groups was observed, but varied with the kind of spice. The results are valuable for future authentication studies.

Food products are often composed of multiple ingredients that are in addition generally heavily processed, this makes it very challenging to determine the ingredient composition. Traditional molecular biological techniques, such as, specific PCR followed by Sanger sequencing or TaqMan PCR are most frequently applied to identify species/varieties in food/feed products. In the last decade, next generation sequencing (NGS) technologies have been developed and have been widely applied in medical science and other areas, such as agricultural and environmental sciences. The aim of this thesis was to use detailed genetic differences to identify species/varieties in feed/food products based on advanced analytical NGS based strategies. The study focused on the identification of two target groups: (a) endangered species and (b) GMOs. Elucidating genetic composition was subdivided in three main topics: enrichment, NGS based strategy and identification. For both applications novel molecular assays were developed and coupled to an apt NGS technology, data analysis was performed with a dedicated bioinformatics pipelines that were developed for the specific needs per application. With respect to endangered species identification, in chapter 2 it was shown that no dedicated method was available to identify endangered plant and animal species in real-life samples. To address this issue, in chapter 3, a multi-locus DNA metabarcoding approach was developed comparing 12 plant and animal barcode and mini-barcode markers, and the method was validated across 16 laboratories. The results showed that the approach was sensitive enough to identify species present at 1% and consistent and reproducible results were observed across the laboratories for all the analysed experimental mixtures and real-life samples. The combination of multiple barcodes enabled the identification of all the species used in the experimental mixtures, and additionally increased the quality assurance for detection. Fur

Authentication of food products is of ongoing interest to consumers in developed countries. Recently, a general interest in the sustainability of food productions, from both societal and environmental perspectives, developed and added a new dimension. Fish and fish products are common targets for food adulteration. The most important issue is fish management, e.g., the environmental impact of overfishing. Analytical means would be helpful for verification. The aim of the present study was to evaluate various marker groups for the distinction of European plaice from the North Sea from European plaice from other geographical origins: volatile organic compounds (VOCs), fatty acids(FA), and isotope ratios. VOCs were analyzed using proton transfer reaction mass spectrometry (PTR-MS); the FA composition was analyzed using gas chromatography with a flame ionization detector, and carbon, hydrogen, nitrogen; and sulfur isotope ratios were analyzed using isotope ratio mass spectrometry. In a principal component analysis, FA profiling appeared the best option to distinguish European plaice from the North Sea from those originating from other seas.

Background: DNA metabarcoding, which involves Next-Generation Sequencing (NGS) of DNA barcodes, holds great promise for species identification in complex samples such as food supplements and Traditional Medicines (TMs). Such method would aid CITES (the Convention on International Trade in Endangered Species of Wild Fauna and Flora) enforcement officers to combat wildlife crime by preventing illegal trade of endangered plant and animal species. The objective of this research was to develop a multi-locus DNA metabarcoding method for wildlife forensic species identification and to evaluate the applicability and reproducibility of the this approach across different laboratories. Results: The DNA metabarcoding method developed in this study makes use of 12 DNA barcode markers that have demonstrated universal applicability across a wide range of plant and animal taxa, and that facilitate the identification of plant and animal species in highly processed samples containing degraded DNA. The DNA metabarcoding method was developed on the basis of NGS data generated for 15 well-defined experimental mixtures using Illumina MiSeq technology, for which a bioinformatics pipeline with user-friendly web interface was developed. The performance of the DNA metabarcoding method was assessed in an international validation trial by 16 laboratories, in which the method was found to be highly reproducible and sensitive enough to identify species present in a mixture at 1% dry weight content. Conclusion: The advanced, multi-locus DNA metabarcoding method assessed in this study provides reliable and detailed data on the composition of complex food products, including information on the presence of CITES species. The method provides improved resolution for species identification, while verifying species with multiple DNA barcodes contributes to enhanced quality assurance., Background: DNA metabarcoding, which involves Next-Generation Sequencing (NGS) of DNA barcodes, holds great promise for species identification in complex samples such as food supplements and Traditional Medicines (TMs). Such method would aid CITES (the Convention on International Trade in Endangered Species of Wild Fauna and Flora) enforcement officers to combat wildlife crime by preventing illegal trade of endangered plant and animal species. The objective of this research was to develop a multi-locus DNA metabarcoding method for wildlife forensic species identification and to evaluate the applicability and reproducibility of the this approach across different laboratories. Results: The DNA metabarcoding method developed in this study makes use of 12 DNA barcode markers that have demonstrated universal applicability across a wide range of plant and animal taxa, and that facilitate the identification of plant and animal species in highly processed samples containing degraded DNA. The DNA metabarcoding method was developed on the basis of NGS data generated for 15 well-defined experimental mixtures using Illumina MiSeq technology, for which a bioinformatics pipeline with user-friendly web interface was developed. The performance of the DNA metabarcoding method was assessed in an international validation trial by 16 laboratories, in which the method was found to be highly reproducible and sensitive enough to identify species present in a mixture at 1% dry weight content. Conclusion: The advanced, multi-locus DNA metabarcoding method assessed in this study provides reliable and detailed data on the composition of complex food products, including information on the presence of CITES species. The method provides improved resolution for species identification, while verifying species with multiple DNA barcodes contributes to enhanced quality assurance.