Records 1 - 20 / 266
Impact of the COVID-19 pandemic on food fraud vulnerability in food supply networks
Ruth, Saskia M. van - \ 2020
Wageningen : Wageningen Food Safety Research (WFSR-report / Wageningen Food Safety Research 2020.017) - 25
The COVID-19 pandemic and related containment measures have placed food supply chains under great pressure. They have led to disruptions in supply and demand of food products but also led to shortfall in staff in various places affecting production, logistics, and adequacy of controls. Any disturbance in routine practices affects crime and criminal behaviour as has been conceptualised by the criminological Routine Activities Theory. Therefore, an effect of the pandemic on food fraud risk and prevalence may be expected. In the current study we examined the impact of the COVID-19 pandemic on food fraud vulnerabilities of European food businesses by conceptualising its effect on 50 food fraud risk factors identified previously using a theoretical framework analogue to the Routine Activities Theory. To identify the baseline vulnerabilities of industry segments, empirical fraud vulnerability assessment data from fish, meat, olive oil, spices, and various organic supply chains from previous studies were collated. Conventional and organic olive oil, meat, and spices appear industry segments with an intrinsically higher level of food fraud vulnerability. The impact of the COVID-19 pandemic on individual food fraud risk factors reveals primarily an enhancing effect on the economic and cultural/behavioural drivers as well as a reduction in adequacy of control measures. The pandemic has less impact on opportunities. When focusing on the individual industry segments, all are impacted in a negative sense. Even so, fish and meat industry segments see most widely spread effects in terms of production, logistics, and demand. These disruptions affect, in turn, in particular economic and cultural/behavioural drivers. Consequently, food fraud vulnerability of these animal production chain networks, which was already relatively high prior to the pandemic, appear to have further increased due to the COVID-19 pandemic.
Real or fake yellow in the vibrant colour craze : Rapid detection of lead chromate in turmeric
Erasmus, Sara W. ; Hasselt, Lisanne van; Ebbinge, Linda M. ; Ruth, Saskia M. van - \ 2020
Food Control (2020). - ISSN 0956-7135
Adulteration - FT-Raman spectroscopy - Spice fraud
For centuries, the colour of foods has played a significant role in the way products are perceived and valued. Generally, the more vibrant the product, the higher its quality and price. For modern-day consumers, various brightly coloured foods are known as superfoods and often consumed at higher concentrations than before. There is emerging attention for adulteration of turmeric with the vibrant yellow, toxic and carcinogenic compound lead chromate. Rapid detection of this hazardous lead chromate is important to protect consumers, therefore this study aimed to develop a spectroscopy-based method to detect lead chromate in turmeric powder. The potential of Fourier transform-Raman (FT-Raman) spectroscopy was investigated experimentally by measuring multiple turmeric powder samples adulterated with different concentrations of lead chromate (0.1%–10.0%, w/w). The acquired FT-Raman spectra were analysed by both univariate and multivariate statistics. Linear correlation of the intensity of the main lead chromate Raman peak at 840 cm−1 against the lead chromate concentration gave a limit of detection (LOD) of 0.6%. For the partial least squares regression (PLSR) model, based on the 1750-200 cm−1 range, a LOD of 0.5% was obtained. Lead chromate was successfully detected for samples adulterated from 0.5% or higher. Raman spectroscopy is a promising screening technique for the rapid detection of lead chromate in turmeric powder at concentrations over 0.5%. However, the LOD for this study is still above the maximum levels that have been found in practice and future studies should focus on increasing the sensitivity of the technique.
Study on the relations between hyperspectral images of bananas (Musa spp.) from different countries, their compositional traits and growing conditions
Wang, Zhijun ; Erasmus, Sara Wilhelmina ; Liu, Xiaotong ; Ruth, Saskia M. Van - \ 2020
Sensors 20 (2020)20. - ISSN 1424-8220 - p. 1 - 18.
Correlation analysis - Geographical origin - Organic - VIS-NIR hyperspectral fingerprints
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 productionmanagement (organic/conventional)were explored. Themain 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.
Rapid high-throughput determination of major components and amino acids in a single peanut kernel based on portable near-infrared spectroscopy combined with chemometrics
Yu, Hongwei ; Liu, Hongzhi ; Erasmus, Sara Wilhelmina ; Zhao, Simeng ; Wang, Qiang ; Ruth, S.M. van - \ 2020
Industrial Crops and Products 158 (2020)158. - ISSN 0926-6690
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.
Novel application of near-infrared spectroscopy and chemometrics approach for detection of lime juice adulteration
Jahani, Reza ; Yazdanpanah, Hassan ; Ruth, Saskia M. van; Kobarfard, Farzad ; Alewijn, Martin ; Mahboubi, Arash ; Faizi, Mehrdad ; Aliabadi, Mohammad Hossein Shojaee ; Salamzadeh, Jamshid - \ 2020
Iranian Journal of Pharmaceutical Research 19 (2020)2. - ISSN 1735-0328 - p. 34 - 44.
Chemometrics - Food fraud - K-NN - Lime juice - PLS-DA - Portable NIR
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.
Opportunities for fraudsters : When would profitable milk adulterations go unnoticed by common, standardized FTIR measurements?
Yang, Yuzheng ; Hettinga, Kasper A. ; Erasmus, Sara W. ; Pustjens, Annemieke M. ; Ruth, Saskia M. van - \ 2020
Food Research International 136 (2020). - ISSN 0963-9969
Ammonium chloride (PubChem CID: 25517) - Ammonium sulphate (PubChem CID: 6097028) - Dicyandiamide (PubChem CID: 10005) - Formaldehyde (PubChem CID: 712) - Fourier transform infrared - Fructose (PubChem CID: 5984) - Glucose (PubChem CID: 79025) - Hydrogen peroxide (PubChem CID: 784) - Lactose (PubChem CID: 104938) - Maltodextrin (PubChem CID: 68229136) - Melamine (PubChem CID: 7955) - Milk adulteration - Milk composition - Milkoscan measurements - One class classification - Profitability - Sodium bicarbonate (PubChem CID: 516892) - Sodium carbonate (PubChem CID: 10340) - Sodium citrate (PubChem CID: 23666341) - Sodium hydroxide (PubChem CID: 14798) - Starch (PubChem CID: 24836924) - Sucrose (PubChem CID: 5988) - Urea (PubChem CID: 1176)
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.
From Extra Virgin Olive Oil to Refined Products : Intensity and Balance Shifts of the Volatile Compounds versus Odor
Yan, Jing ; Alewijn, Martin ; Ruth, Saskia M. van - \ 2020
Molecules 25 (2020)11. - ISSN 1420-3049
extra virgin olive oil - odor quality - processing grades - quantitation - VOCs proportion
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.
Linking sensory and proton transfer reaction–mass spectrometry analyses for the assessment of melon fruit (Cucumis melo L.) quality traits
Bianchi, Tiago ; Guerrero, Luis ; Weesepoel, Yannick ; Argyris, Jason ; Koot, Alex ; Gratacós-Cubarsí, Marta ; Garcia-Mas, Jordi ; Ruth, Saskia van; Hortós, Maria - \ 2020
European Food Research and Technology 246 (2020). - ISSN 1438-2377 - p. 1439 - 1457.
Flavor - Melon fruit - Odor - PTR–MS - Sensory analysis - Volatile organic compounds
Sixty-seven samples of ten melon types (Cucumis melo L.) were evaluated to determine the relationship between their quality traits: sensory attributes, pH, soluble solids, and volatile organic compounds. Fruits from the cantalupensis, conomon, dudaim, inodorus, and momordica cultivar groups were analyzed. The sensory profiles were assessed using ten attributes covering odor, flavor, and taste characteristics, whereas the volatile profiles were derived by proton transfer reaction–mass spectrometry. Fruits from the cantalupensis and inodorus cultivars showed an opposite pattern for several quality traits. Fruits from the dudaim cultivar were more related to the cantalupensis, whereas conomon and momordica showed an intermediate behavior between inodorus and cantalupensis. The attributes of odor and flavor intensity, ripe fruit odor, fermentative odor, and fermentative flavor correlated positively to C3–C9 esters (r = 0.43–0.73; p ≤ 0.01). Positive correlations were also observed for several alcohols (r = 0.36–0.82; p ≤ 0.05), including methanol, ethanol, and diol alcohols, as well as for several aldehydes (r = 0.43–0.85; p ≤ 0.01), such as acetaldehyde, butanal, methyl butanal, heptanal, and decanal. The attributes mentioned above were negatively correlated with two C9 aldehydes, 2,6-nonadienal and nonenal (r = − 0.45 to − 0.62; p ≤ 0.01), whereas sweetness was negatively correlated with two C6 green leaf volatiles, hexenal and 3-hexenol (r = − 0.50; − 0.67; p ≤ 0.001). The melon fruits presented distinct differences in the quality traits evaluated. These results provide information for the development of new cultivars with characteristic taste combinations without compromising other desirable fruit quality traits.
Prevalence of milk fraud in the Chinese market and its relationship with fraud vulnerabilities in the chain
Yang, Yuzheng ; Zhang, Liebing ; Hettinga, Kasper A. ; Erasmus, Sara W. ; Ruth, Saskia M. Van - \ 2020
Foods 9 (2020)6. - ISSN 2304-8158
China - Fourier transform-infrared spectroscopy - Fraud vulnerability - Milk adulteration - Milk composition - One-class classifications
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.
Evaluation of portable and benchtop NIR for classification of high oleic acid peanuts and fatty acid quantitation
Yu, Hongwei ; Liu, Hongzhi ; Wang, Qiang ; Ruth, Saskia van - \ 2020
Food Science and Technology = Lebensmittel-Wissenschaft und Technologie 128 (2020). - ISSN 0023-6438
High oleic acid - Peanut - PLS - PLS-DA - Portable NIR
Portable near-infrared (NIR) analyzer for classifying the high oleic acid peanuts (HOP) and quantitation of its major fatty acids was assessed for the first time in comparison with the benchtop NIR. Reference chemical values of fatty acids were calculated by the gas chromatographic method. The processed datasets were explored by principal component analysis and classification models were built by using partial least square discriminant analysis. The results showed that the accuracy of distinction of the HOP from others was 100%. Partial least square was used to build quantitative models for quantifying the peanuts’ major fatty acids. The R of the calibration model noted for the portable NIR was 0.90, 0.88 and 0.88 for oleic acid, linoleic acid and palmitic acid of the HOP with a SEC of 0.97, 0.12 and 0.12, respectively. The similar results could be found in the benchtop NIR. The RPD of all models were over 2 which showed good performance of the models. This study indicated that the portable NIR performance was comparable with the performance of the benchtop NIR for distinction of the HOP from others, as well as for the prediction of the contents of its main fatty acids.
Sniffing out cocoa bean traits that persist in chocolates by PTR-MS, ICP-MS and IR-MS
Acierno, Valentina ; Jonge, Leon de; Ruth, Saskia van - \ 2020
Food Research International 133 (2020). - ISSN 0963-9969
Chocolate - Cocoa beans - Fingerprint - High sensitivity-proton transfer reaction-mass spectrometry - Inductively coupled plasma-mass spectrometry - Isotope ratio-mass spectrometry
The cocoa botanical and geographical origin and the primary processing steps applied by cocoa farmers at the beginning of the supply chain influence the chemical compositional traits of the cocoa beans. These features are carried along the supply chain as intrinsic markers up to the final products. These intrinsic markers could be used for tracking and tracing purposes. In this study, we examined the retention and loss of compositional signatures from cocoa beans to chocolates. Volatile, elemental and stable isotope signatures of cocoa beans of 10 different origins and 11 corresponding chocolates were determined by high sensitivity-proton transfer reaction-mass spectrometry (HS-PTR-MS), inductively coupled plasma-MS (ICP-MS) and isotope ratio-MS (IR-MS), respectively. The volatile fingerprints provided mostly information on the origin and primary processing traits of the raw cocoa beans in the chocolates. Volatile compounds that are relevant markers include: acetic acid (m/z 61), benzene (m/z 79), pyridine (m/z 80), 2-phenylethanol (m/z 123), and maltol (m/z 127). On the other hand, the elemental and stable isotope characteristics are more indicative of the cocoa content and added ingredients. Possible elemental markers for cocoa origin include Fe, Cr, and Cd. VOCs appear to be the most robust markers carried from cocoa beans to chocolates of the groups examined. This provides the potential for track and trace of cocoa beans from farm to chocolates.
Integrity of organic foods and their suppliers : Fraud vulnerability across chains
Ruth, Saskia M. van; Pagter-de Witte, Leontien de - \ 2020
Foods 9 (2020)2. - ISSN 2304-8158
Banana - Egg - Fraud - Mitigation - Olive oil - Organic - Pork - Vulnerability
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.
The Chinese milk supply chain: A fraud perspective
Yang, Yuzheng ; Huisman, Wim ; Hettinga, Kasper A. ; Zhang, Liebing ; Ruth, Saskia M. van - \ 2020
Food Control 113 (2020). - ISSN 0956-7135
China - Dairy farmer - Economically motivated adulteration - Fraud vulnerability assessment - Milk processor - Milk supply chain
Food fraud has become a serious concern all over the world and especially in China. The melamine contaminated infant formula in 2008 has brought food fraud in the spotlights. This incident had grave consequences for the Chinese citizens as well as the Chinese milk industry. Fraud vulnerability assessments are the first step towards food fraud prevention and mitigation. To combat food fraud, one has to think like a criminal. In the current study, we determined the most vulnerable points in the Chinese milk supply chain, and examined the underlying causes. The fraud vulnerability perceived by 90 Chinese dairy farmers and 14 milk processors was evaluated with the SSAFE food fraud vulnerability assessment tool. Overall, actors perceived the milk supply chain as low to medium vulnerable to food fraud. Farmers appeared significantly more vulnerable than processors due to enhanced opportunities and motivations, and less adequate controls. Both geographical location of the farms and their size affected their perceived fraud vulnerability significantly.
Feeding fiction: Fraud vulnerability in the food service industry
Ruth, Saskia M. van; Veeken, Joris van der; Dekker, Pieter ; Luning, Pieternel A. ; Huisman, Wim - \ 2020
Food Research International 133 (2020). - ISSN 0963-9969
Dining - Food fraud - Fraud prevention - Hospitality - Integrity - Mass caterer - Restaurant
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.
Food fraud: Assessing fraud vulnerability in the extra virgin olive oil supply chain
Yan, Jing ; Erasmus, Sara W. ; Aguilera Toro, Miguel ; Huang, Haixin ; Ruth, Saskia M. van - \ 2020
Food Control 111 (2020). - ISSN 0956-7135
B2B company - FFVA tool - Food fraud - Food manufacturer - Olive oil producer - Retailer
As a high value commodity on the market, extra virgin olive oil (EVOO) is a suitable target for fraudsters. To understand differences in perceived fraud vulnerability between tier groups across the EVOO supply chain and to disclose underlying factors, the perceived fraud vulnerability of 28 companies was examined using the SSAFE food fraud vulnerability assessment tool. Amongst these companies were seven olive oil producers, seven business-to-business (B2B) companies, seven food manufacturers and seven retailers. The similarities and differences in perceived fraud vulnerabilities according to group characteristics (the role, the scale and the location of the company) were evaluated. Non-parametric tests and multiple correspondence analysis were applied for data exploration. An in-depth fraud vulnerability assessment of the EVOO supply chain was provided. Eight fraud factors related to opportunities and motivations scored high in the supply chain indicating their importance as fraud drivers and enablers. Four factors related to control measures are perceived as greatest vulnerability in the EVOO supply chain. Then, the vulnerability to fraud in the EVOO supply chain across all actors is perceived as high level on average. In decreasing contribution to the overall perceived fraud vulnerability, the fraud factor categories were ranked as follow: technical opportunities, a lack of managerial controls, a lack of technical controls, economic drivers, cultural and behavioural drivers, and opportunities in time and place. Among the tier groups, the retailers and B2B companies experienced higher levels of perceived vulnerability than olive oil producers and food manufacturers due to the additional vulnerability related to the opportunities in time and place, and greatest lack of control measures. Furthermore, the perceived fraud vulnerability of the company was not only determined by the tier group, but also impacted by the scale and location of the company.
Dairy farming system markers: The correlation of forage and milk fatty acid profiles from organic, pasture and conventional systems in the Netherlands
Liu, Ningjing ; Pustjens, Annemieke M. ; Erasmus, Sara W. ; Yang, Yuzheng ; Hettinga, Kasper ; Ruth, Saskia M. van - \ 2020
Food Chemistry 314 (2020). - ISSN 0308-8146
Classification - Correlation analysis - Fatty acids - Forage - Milk - Organic
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.
Linking growing conditions to stable isotope ratios and elemental compositions of Costa Rican bananas (Musa spp.)
Wang, Zhijun ; Erasmus, Sara W. ; Dekker, Pieter ; Guo, Boli ; Stoorvogel, Jetse J. ; Ruth, Saskia M. van - \ 2020
Food Research International 129 (2020). - ISSN 0963-9969
Banana - Elemental profiling - Geographical attribute - Stable isotopic fingerprinting
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.
|Think like a criminal: who is vulnerable to fraud?
Ruth, Saskia van - \ 2019
Food fraud and vulnerability assessments
Ruth, Saskia M. van - \ 2019
In: Encyclopedia of Food Chemistry Elsevier - ISBN 9780128140260 - p. 663 - 669.
Controls - Drivers - Enablers - Food adulteration - Food authenticity - Food fraud - Food safety - Mitigation - Motivations - Offenders - Opportunities - Quality management
Food fraud is the intentional, deceptive misrepresentation of foods for economic gain. It is the outcome of the convergence in time and place of a motivated offender and a suitable target in the absence of capable guardians. Fraud vulnerability of businesses depend on openings for undesirable events resulting from weaknesses or flaws in the system. The mapping of a company’s or chain’s fraud vulnerabilities is a first step towards fraud management. In this chapter the food fraud concept based on the criminological routine activity theory is described. Furthermore, key elements and individual fraud factors are discussed, as well as differences in fraud vulnerability across supply chains and their tiers.
Evaluation of food-grade vegetable oils using ultrasonic velocity measurement and fatty acid composition
Yan, Jing ; Wright, William M.D. ; Roos, Yrjo ; Ruth, Saskia M. Van - \ 2019
In: 2019 IEEE International Ultrasonics Symposium, IUS 2019. - IEEE computer society (IEEE International Ultrasonics Symposium, IUS ) - ISBN 9781728145969 - p. 2435 - 2438.
density - extra virgin olive oil - fatty acid methyl ester (FAME) test - oil viscosity - ultrasonic velocity
Extra virgin olive oil (EVOO) is a high-value food commodity and is often a target for food fraud, in which the EVOO is adulterated with lower grade oils such as refined olive oil (ROO), pomace olive oil (POO) and other vegetable oils of nut or seed origin such as rapeseed or canola oil (RSO), peanut oil (PNO) and sunflower oil (SFO). The objective of this study is to investigate ultrasonic techniques to distinguish between different food-grade oils based on their fatty acid (FA) composition. An ultrasonic pulse-echo system was used to measure the propagation delay and hence the velocity of ultrasonic waves at 5 MHz in three different types of olive oil (EVOO, POO and ROO) and three other vegetable oils of nut or seed origin (PNO, RSO and SFO). The ultrasonic system was temperature controlled in a heated water bath at 23.5°C±0.05°C. The ultrasonic velocity was determined using the differential propagation delay from four 2.00 mm increments in the propagation path, determined using a micrometer to ±0.005 mm to eliminate any uncertainty in the initial propagation path. The FA content of each oil was determined using an ISO 12966-2 (2017) automatic BF3 transmethylation procedure followed by gas chromatography according to ISO 12966-4 (2015) using an Agilent HP7890A Gas Chromatograph. 80 different samples were tested, using extra virgin olive oil (n=30), refined olive oil (n=15), pomace olive oil (n=15), rapeseed/canola oil (n=10), sunflower oil (n=5), and peanut oil (n=5). The FA composition and ultrasonic velocity of each sample were measured. A statistically significant correlation between polyunsaturated fatty acid (PUFA) content and ultrasonic velocity, and a statistically significant negative correlation between monounsaturated and saturated fatty acid (MUFA and SFA) content and ultrasonic velocity, were noted. The ultrasonic velocity may thus be used to help distinguish between different food-grade vegetable oils that have a high PUFA content, such as sunflower oil and rapeseed/canola oil, and those with a high MUFA content such as olive oil and peanut oil. The FA composition appears to influence the density and compressibility of the oil, which determine the ultrasound velocity.