查看更多>>摘要：The increase in fraudulent incidents has resulted in a change of focus in theory related to investigating food fraud from risk mitigation to vulnerability reduction. While the literature provided a framework from which to identify possible areas of vulnerability to food fraud, it does not provide a methodology that would allow food producers and processors to quantify and assess their vulnerability to food fraud more accurately. This paper developed a holistic approach to analyse food fraud vulnerability factors using a Bayesian Network (BN) approach based on the Decernis food fraud database incidents. Food fraud incidents related to seafood, dairy, alcoholic beverages and meat products were reviewed as they cover more than 50 % of the Decernis incident records (as in June 2018). 580 cases of food fraud were included in the development of the BN model. SPSS Modeler 18.2 was used to construct two BN model, and fraud vulnerability factors were directly linked to seven criteria of the country of origin, country of detection, year, food fraud types, product types, the weight of evidence, and types of adulterants. Possible food fraud vulnerability factors related to each case retrieved from Decernis database, combined Barrier Analysis technique and Routine Activity Theory, and additional sources from the literature. Two Bayesian Networks of Tree Augmented Naive (TAN) and Markov were selected to determine the most reliable holistic model. Based on the analysis result, the TAN model assessed the vulnerability to food fraud with a higher accuracy rate of 86 %. The country of origin (76 %), food product types (9 %), types of adulterants (counterfeiting) (9 %), and country of detection (China) (6 %) were the main predictors of food fraud vulnerability factors. This model helps authorities in border protection, policymakers, and quality assurance agencies assess fraud vulnerability for a range of food products for incoming (imported) food products, mainly if they know the country of origin and type of food products.
查看更多>>摘要：Sixty samples of chickpea (Cicer arietinum L.) harvested in the Italian territories of Cicerale (Campania), Val-entano (Lazio) and Navelli (Abruzzo) in 2019 were characterized by determination of the content of ten elements (Ca, K, P, Mg, Mo, Cu, Fe, Mn, Zn and Sr) with Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). Classification of the samples was performed using both discriminant (Linear Discriminant Analysis, LDA) and class-modelling (Soft Independent Modelling of Class Analogies, SIMCA) methods, after the application of Analysis of Variance (ANOVA) to assess the significance of the detected elements. Both discriminant and class models were calibrated on 33 samples and eventually applied on a prediction set of 27 samples to evaluate the classification ability and class-modelling efficiency, respectively. LDA led to 100% classification rate on the external set, whereas the class models developed using SIMCA exhibited good sensitivity (external samples accepted by the respective classes were 88% for Cicerale, 90% for Valentano and 100% for Navelli) and 100% specificity (all the extraneous samples were correctly rejected by each class-model).
Brasil, Yasmin LimaCruz-Tirado, J. P.Barbin, Douglas Fernandes
12页
查看更多>>摘要：Quail eggs are one of the main natural sources of essential nutrients, presenting high amounts of protein, antioxidants, calcium, iron and phosphorus. However, its quality assessment demands laborious methods and chemicals, and there is currently no standard method do quantify its freshness. This work aimed to investigate the performance of a portable NIR spectrometer, in combination with machine learning, to estimate the freshness of quail eggs. Since there is no standard index to classify quail eggs, we compared Haugh Unit (HU), Yolk Index (YI) and the Egg Quality Index (EQI) as reference methods. Partial Least Squares Regression (PLSR) and Support Vector Machine Regression (SVMR) were used to build prediction models, and Partial Least Squares-Discriminant Analysis (PLSDA) and Support Vector Machine Classification (SVMC) for the development of classification models. For the first time, we demonstrated that EQI, which is a parameter that measures egg freshness according to the quality of the yolk and the albumen, is the best way to express the freshness of quail eggs. The best prediction models were obtained for YI and EQI, using SVMR, with RPD = 2.0-2.5 and RER >10, indicating good predictive capacity. PLSDA and SVMC models showed similar performance, correctly classifying more than 80% of the samples. The results obtained demonstrate the potential of portable NIR spectrometer for monitoring quail eggs freshness during storage.
查看更多>>摘要：As part of an extended fish product (mixed salmon spread) value chain involving multiple treatment procedures and mixing processes, oxidation and microbial spoilage can be initiated at any number of steps and go on to accelerate product deterioration. This may occur, for example, when salmon rest raw materials are processed to form mixed emulsion products. To investigate the effect of selected variables in the value chain, a model experiment was designed and implemented, consisting of a chain divided into four steps involving fish feed composition, fish processing, fish spread production and storage. By using this case, the objectives of the paper are to 1) show how a complex split-plot design can be analysed using analysis of variance (ANOVA) and multivariate statistical analyses, 2) show how an interplay of the methodologies can contribute to improvement in the interpretation and validation of results, and 3) identify the quality markers most affected by the design variables, and then use these to optimise response measurements for different raw material properties. We also propose some new monitoring and control strategies based on the PCA and results obtained. The analysis has indicated in this case that it may be beneficial for the long shelf-life of the spread to use fresh and lean salmon cuts, to store the product under superchilled conditions and to avoid the addition of secondary seafood ingredients. Salmon feed variables do not affect the eating quality of the spreads. The early addition of a smoke component and the rigor status of the salmon at the time of processing had little effect on eating quality. The variables that did not affect eating quality or shelf-life can be optimised based on aspects such as nutritional or health benefits, or production costs. This article demonstrates that PCA is a useful method both for the monitoring of eating quality with storage time, the definition of control limits for product acceptability, and the statistical validation of split-plot ANOVA results.
查看更多>>摘要：Zearalenone (ZEN), mainly produced by Fusarium species in many crops worldwide, is an estrogenic mycotoxin that causes reproductive disorders in livestock. In this study, we developed a different degradation mode by choosing specific microorganisms to catalyze directional reactions to produce less toxic or non-toxic target products. One promising strain, Candida parapsilosis ATCC 7330, with high reductase activity was evaluated for its ability to directly convert ZEN to less toxic beta-Zearalenol (beta-ZOL). Glucose was added to trigger ZEN glucosylation by yeast. Thin layer chromatography (TLC) combined with liquid chromatography-mass spectrometry (LC-MS) revealed that ZEN exposed to C. parapsilosis ATCC 7330 was transformed into beta-ZOL and zearalenone glucosides ([M+H]+ at 643.2581), and it was proposed to be ZEN-14,16-diglucoside according to NMR analysis, which was stable under digestive conditions. Furthermore, kinetic analysis indicated that the ZEN level (20 mu g/mL) decreased by 97% within 5 h, which relied on enzymes on the cell membrane. In addition, C.parcupsilosis ATCC 7330 also exhibited glucosyltransferase activities toward beta-ZOL, alpha-Zearalenol (alpha-ZOL) and Zearalanone (ZAN) with yields of 100%, 76%, and 100%, respectively. Considering the estrogenic toxicity of target metabolites after complex transformation without coenzyme addition, detoxification by specific biodegradable microorganisms may open new opportunities and innovations for mycotoxin detoxification.
查看更多>>摘要：The risk of reactions due to the unintentional presence of allergens, such as traces in packaged products, remains difficult to characterize. The aim was to assess the risk regarding unintended traces of peanut in packaged food products in peanut allergic patients using original data from the MIRABEL survey. We developed an integrated Bayesian probabilistic risk model based on relevant data including consumption of a panel of selected products with and without precautionary labelling by peanut allergic patients, and their individual threshold dose at oral food challenge (OFC). 785 patients (<16 years: 86%) were included in the survey. Data on OFC and food consumption were available for 238 and 443 patients, respectively. For eight food categories with precautionary labelling (30%) or without (70%), the risk was nil (no peanut traces). For chocolate tablets and spreads, the risk was not significantly different from zero. For appetizers, from the different models and including uncertainty intervals, the mean estimated risk was between 38 reactions for 1 000 000 eating occasions and 55 reactions for 10 000 eating occasions. For the 1% lowest dose reactors at OFC, the estimated risk was between 8 reactions for 10 000 and 71 reactions for 1000 eating occasions. According to these results, the allergic risk related to peanut traces in packaged food products was only significant for the most sensitive allergic consumers of appetizers. If the link between food consumption and threshold dose is not taken into account, individual variability could be overlooked, and the risk underestimated. These findings need to be confirmed by larger and representative studies including non-packaged products.
Hernandez-Hernandez, CarolinaFernandez-Cabanas, Victor M.Rodriguez-Gutierrez, GuillermoFernandez-Prior, Africa...
9页
查看更多>>摘要：Near Infrared (NIR) spectroscopy was evaluated as a fast and easy method for identifying the most interesting cocoa genotypes according to chemical composition, including bioactive compound contents, in more than 80 samples of cocoa beans from the Mexican Germplasm Bank, which were harvested over three years. Clear differences in chemical composition were detected in fermented and dried samples among genotypes. The contents in fat, protein, total sugars, total phenols, phenolic compounds and theobromine were determined for both whole cocoa beans and ground cotyledon samples; and calibration models were developed from the spectra of intact beans, nibs and ground cotyledons. In general, the calibration models obtained for cotyledon composition from the spectra of cocoa nibs and ground beans were better than those obtained from the spectra of intact beans. Fat content showed better calibration statistic values from the spectra of nibs and ground cotyledon (r2 = 0.70). Bioactive compounds, such as theobromine (r2 = 0.77), total sugars (r2 = 0.74), total phenols (r2 = 0.66) and derivatives of epicatechin (r2 = 0.88), together with fat (r2 = 0.70), protein (r2 = 0.64) and husk content (r2 = 0.82), were well-predicted using NIR spectroscopy in intact beans, cocoa nibs and/or ground cotyledon. The potential of NIRS technology was confirmed to support germplasm banks and breeding programs for the rapid identification of interesting genotypes based on their contents in bioactive compounds.
查看更多>>摘要：Activated carbons were applied to the removal of imidacloprid and acetamiprid from tea infusion and both pesticides were determined by HPLC in this study. Results presented that the YQFB, an activated carbon with large BET surface area and more mesopores was effective for the removal of both pesticides from tea infusion. The removal rates were significantly (p <= 0.05) affected by absorbent dosage, adsorption time, temperature, tea concentration and initial concentration of pesticide. Removal rates of both pesticides were improved with the dosage increased and the adsorption time prolonged, while decreased as the increase of tea concentration and initial concentration of pesticides. The maximum removal rates were 85.0% for imidacloprid and 85.7% for acetamiprid. The adsorption of both pesticides by YQPB followed the pseudo-second-order kinetics model well. The quality of tea infusion after activated carbon treatment was analyzed and results revealed that the retention rates of most components were higher than 85% and the stability of tea infusion was not significantly (p > 0.05) affected by activated carbon treatment. The present study found a low-cost and effective way to remove imidacloprid and acetamiprid from tea infusion, and it has the potential to be applied to the ready-to drink tea beverages production in industrial scale.
查看更多>>摘要：Effective packages can extend shelf life and quality of mushrooms in storage. This study is to investigate the effects of nano-SiO2/nano-TiO2 loaded polyvinyl alcohol (PVA) packages on preservation of Agaricus bisporus. Quality properties, including weight loss, respiration rate, color, total soluble solid, pH, malondialdehyde content, electrolyte leakage rate, total phenolics, ascorbic acid, polyphenol oxidase, peroxidase, microbial growth and microstructure have been evaluated in 15 days storage at 4 +/- 1 degrees C and 90 % relative humidity. Results showed that mushrooms packaged in nano-SiO2/nano-TiO2 loaded PVA films exhibited a better retention in pH, color, total phenolics, ascorbic acid and antimicrobial activity than those with PVA or polyethylene films. They can make the weight loss, respiration rate, electrolyte leakage rate and accumulation of malondialdehyde more slowly, and lower polyphenol oxidase and peroxidase activities. These positive effects might be attributed to their effectively control of O-2 and CO2 in these packages.
查看更多>>摘要：Patulin (PAT) is a mycotoxin that exists in a wide range and is harmful to human health, which has aroused great attention to food safety. In this study, we established a novel assay to detect food samples contaminated by PAT. First of all, we proposed a truncation protocol based on the secondary structure of aptamer. By removing the stem-loop structure one by one, an optimized truncated PAT aptamer (P-30) was obtained. To the best of our knowledge, the mechanism between PAT and P-30 was elaborated in the assisting of molecular docking and circular dichroism for the first time. Furthermore, we developed a sensitive aptasensor platform to detect PAT in food samples. The aptamer modified with gold nanoclusters (AuNCs) was used as fluorescent probe, and BSA-directed synthesized MnO2 nanoflakes (MnO2 NFs) as fluorescence receptor. Additionally, fluorescence signal amplification strategy assisted by DNase I successfully improved the sensitivity of aptasensor. The developed assay had a low detection limit of 8.5 ng/L, and can be effectively used in apple and grape juice samples. Thus, the established aptasensor shows a broad application prospect in PAT detection.
NSTL
Elsevier