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Abstract: Salmonella enteritidis (S. enteritidis) and Listeria monocytogenes (L. monocytogenes) are two main foodborne pathogens. Cold plasma (CP), a non-thermal technology used for food decontamination, has attracted considerable attention in recent years. Hence, we studied the effects of CP treatment on S. enteritidis and L. monocytogenes growth and bacterial respiratory enzyme activities to elucidate the CP disinfection mechanism. Bacterial colonies were counted, respiratory enzyme activity and reactive species (RS) contents were measured, and relationships between these factors were assessed immediately after CP treatment. Both the colony numbers and enzymatic activities of the two bacterial species decreased as the treatment voltage increased from 60 to 80 kV, regardless of the treatment time. Moreover, similar increasing trends in RS were found in treated bacterial samples. The enzymatic activity of S. enteritidis was reduced to a greater extent than that of L. monocytogenes under the same treatment conditions. After CP treatment at 80 kV for 180 s the activity levels of both malate dehydrogenase (MDH) and succinate dehydrogenase (SDH) in S. enteritidis decreased below the detection limit. The RS levels showed a significant negative correlation with respiratory enzyme activities in these bacteria. Cold plasma displayed a high inhibitory effect on respiratory enzymes in both S. enteritidis and L. monocytogenes. SDH and hexokinase showed the highest correlation with the growth of treated S. enteritidis and L. monocytogenes, respectively. These results indicate that CP affects the growth of S. enteritidis and L. monocytogenes through different pathways, with CP disruption of normal aerobic respiration to induce cell death being the main antimicrobial mechanism. PubDate: 2022-05-13
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Abstract: Patients with celiac disease have to rely on the safety of gluten-free foods (GFF), which are frequently contaminated by gluten. Hence, the evaluation of the gluten level in these foods is important. The aim of this study was to assess the gluten content in GFF available in Morocco. It was carried out on 84 food samples including 52 labelled gluten-free foods (L-GFF) and 32 naturally gluten-free foods (N-GFF), belonging to six categories (pasta, cookies and cakes, baker's yeast, dried vegetables, dried fruits, and cereals). To quantify their gluten content, samples were analysed using a sandwich enzyme immunosorbent assay (R5 ELISA Ridascreen® gliadin Mendez), considering 20 mg/kg (ppm) as the contamination threshold. The overall contamination rate was 23.8% (L-GFF: 21.9%, N-GFF: 25%). Among the six analysed categories, three did not show any contamination (pasta, cookies, and baker's yeast). The contamination rate was 5.3% in dried vegetables, 25% in dried fruits, and 42.1% in cereals. All oat samples were affected. L-GFF locally manufactured were more often contaminated than those imported (28.6 vs. 16.7%). Our data show a high prevalence of gluten contamination of GFF, affecting both N-GFF and L-GFF, and oats were the most contaminated food. Therefore, regular checks of GFF by the competent authorities are necessary in order to avoid the sale of unsafe GFF for celiac patients. Likewise, manufacturers should be encouraged to adopt adequate quality management systems. PubDate: 2022-05-04
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Abstract: Abstract As wheat flour is a raw material for many food products, its cleanliness has a great impact on the safety of flour-derived products. The red flour beetle known as Tribolium castaneum Herbst (Coleoptera: Tenebrionidae) is a major pest of wheat flour. Insects’ invasion in wheat flour increases the pollutants, which may result in the reduction of edibility and safety as well as substantial economic losses. Therefore, this review aimed to elucidate the recent research regarding the reproduction, detection, and disinfestation of T. castaneum in wheat flour. Environmental factors and wheat flour varieties directly affect the reproduction of T. castaneum. In terms of detection methods, the uric acid method, near-infrared spectroscopy, and molecular biology detection have shown promising results. To control T. castaneum, physical processes such as the impact insecticidal machine, temperature control, and diatomaceous earth were introduced. For industrial applications, impact insecticidal machines may become the most common control method in the future. PubDate: 2022-03-22
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Abstract: Patulin is a fungal by-product that contaminates fruits and vegetables, especially apples, and is mainly produced by Penicillium expansum. In the present study, thiourea-polygalacturonic acid (TPGA) complexes were synthesized in three ratios, i.e. 1:1 (T1P1), 1:2 (T1P2), and 2:1 (T2P1). They were evaluated for patulin removal from apple-juice simulated solution. The characterization of TPGA complexes was specified by Fourier transform infrared spectroscopy, energy dispersive X-ray spectroscopy, and scanning electron microscopy. Adsorption tests were carried out to study variable effects of the TPGA ratio, TPGA concentration, contact time, and patulin initial concentration. The results showed that the amide bond was the main binding agent of the TPGA complexes, and the complexes formed aptly in having nano particle sizes. The T1P2 nanocomplex gave the best results, which means that polygalacturonic acid was more effective than thiourea in the adsorption process. The results also indicated that increasing the contact time, adsorbent, and patulin concentration ultimately increased the adsorption capacity. This nanocomplex could adsorb the whole toxin at all patulin concentrations (i.e. 25, 50, and 100 μg/L) in short durations (i.e. 1, 2.5 and 5 h, respectively). The results of adsorption tests were well adapted to the pseudo-first order model (with R2 of 0.991, 0.993, and 0.996) and Freundlich isotherm model (R2 = 0.997). Moreover, these nanocomplexes were able to remove 91.35% of patulin from contaminated apple juice. This work demonstrated that TPGA nanocomplexes can serve as potential materials for removing patulin. Graphical abstract PubDate: 2022-03-21
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Abstract: Abstract Food contamination and food poisoning are presenting a substantial safety risk to consumers worldwide. In the era of information quantity and availability, the potential of social-media data has attracted increasing attention from relevant government regulatory agencies, food companies, and consumers. This paper takes text data from online media as a research object and innovatively proposes a new type of food text-mining technology based on the associated attention mechanism to quickly screen for potential food safety issues. First, we used the mutual information between each review Chinese word segment(CWS) and label to calculate the correlation score between each word and food safety hazards. Then, the attention score in supervised deep learning was combined in order to assess whether foods sold online may be unsafe for consumers. We compared the method in this paper with existing text-mining methods on food-safety-related datasets and found that the proposed method performs markedly better than the benchmark model, achieving an accuracy rate of 96.95 \(\%\) . A team of food safety experts also performed a food risk assessment on the prediction results produced by the proposed model, and experimental results showed that the proposed tool can markedly reduce the time required to screen for food safety risks. This study provides a fast and cost-effective food-safety screening method and helps reduce consumer dietary safety hazards. PubDate: 2022-03-18
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Abstract: Abstract Internationally, food regulations are centred on human health and safety to prevent health crises. In Australia, regulatory control over the health and safety of humans is sound, however from a criminological perspective, control over fraudulent activities within food supply chains lack. Food fraud knows no geographical boundaries and has endless reach, therefore should be prioritised by policymakers, regulators and law enforcement. Australia’s reputation for high-quality food is important domestically, but also for establishing and maintaining trust in international food trade relationships, therefore lack of enforcement over food could damage ‘Brand Australia’. Given the food industry’s vested interest in maintaining this reputation, it must also play a role to protect it. This research reviews regulatory landscape against food fraud in Australia and then, questions whether coupling informal controls to support existing formal regulatory controls may be the most appropriate and holistic way forward to protect the industry and consumers. It tests a regulatory pluralism framework to determine whether it can logically organize informal, innovative responses to contribute cohesively alongside formal controls at various points along the supply chain to prevent food fraud. Finally, it considers available informal, innovative technologies to: enhance testing regimes; prevent product and label tampering; and trace food supply chains adopted internationally show positive progress in responding to increasingly sophisticated and organized global food fraud. The research concludes adopting a regulatory pluralism framework, coupling existing regulatory controls and innovative technology could enhance and strengthen Australia’s regulatory response to fraud within its food industry. PubDate: 2022-03-05 DOI: 10.1007/s00003-022-01372-2
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Abstract: Abstract Investigation of potential biopolymers for developing edible films as alternatives for plastic packaging is a recent trend. Among the biopolymers used in edible film making, galactomannan is a good film-forming agent. Caesalpinia pulcherrima seed gum is a rich source of galactomannan and could be used as an edible film making material. The main objective of this study was to identify the ability of Caesalpinia pulcherrima seed gum in making a food packaging film and assessing its performance. In this study, the gum was extracted from Caesalpinia pulcherrima seeds and dissolved in distilled water along with the plasticizer glycerol. In preparing film-forming solutions, a previously selected range of glycerol concentrations (0.0, 0.5, 1.0 and 1.5%) was used. After casting and drying, the resultant films were analyzed for their physical and mechanical properties. In the present study, the film prior to incorporating glycerol was brittle, less flexible and had a strong film matrix. With the increase of glycerol content, the film became more flexible, sticky and weak. Further, the physical properties namely thickness, moisture content, swelling index, water solubility of Caesalpinia pulcherrima seed gum-based films were increased from 0.039 ± 0.001 to 0.076 ± 0.001 mm, from 62.92 ± 0.51 to 69.40 ± 0.15%, from 5.39 ± 0.17 to 8.45 ± 0.17, from 55.69 ± 0.51 to 66.66 ± 0.45%, respectively, with the increase of glycerol content from 0.0 to 1.5%. Concerning the mechanical properties, the tensile strength and Young’s module were decreased from 10.90 ± 0.08 to 2.11 ± 0.05 MPa and from 48.46 ± 0.24 to 3.47 ± 0.09 MPa, respectively, and the elongation was increased from 22.50 ± 0.05 to 60.84 ± 0.04% with increasing the glycerol content from 0.0 to 1.5%. Due to its physical and mechanical properties, Caesalpinia pulcherrima seed gum is a potential source for edible packaging film manufacture. PubDate: 2022-03-01 DOI: 10.1007/s00003-021-01347-9
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Abstract: Abstract This article presents a method for nondestructively determining water content and firmness of potatoes using hyperspectral imaging (HSI) in the visible near-infrared (VIS/NIR) and short-wave infrared (SWIR) bands. Potatoes were scanned to acquire their hyperspectral images. First derivatives (FD), Savitzky–Golay (SG) smoothing, standard normal variable (SNV) and multiplicative scatter correction (MSC) were used to process the spectral data. Competitive adaptive weighted sampling (CARS) was employed to extract the effective wavelengths. Prediction models were established using several algorithms. The SG-CARS-partial least-squares regression (PLSR) model presented the best performance in the VIS/NIR band; the corresponding R2P, root mean square error of the prediction set (RMSEP), and residual predictive deviation (RPD) values for water content and firmness were 0.9219 and 0.9118, 0.0034 and 0.0640 Newton (N), and 2.5780 and 2.4353, respectively. In the SWIR band, the FD-CARS-PLSR prediction model performed best; the R2P values for water content and firmness were 0.9313 and 0.9317, respectively, the RMSEP values were 0.0025 and 0.0216 N, and RPD values were 2.7453 and 2.7531. This study confirmed the feasibility of the HSI technology for nondestructively determining water content and firmness of potatoes. PubDate: 2022-03-01 DOI: 10.1007/s00003-021-01343-z
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Abstract: Abstract The present study aimed to use the autoregressive integrated moving average (ARIMA) model to forecast foodborne disease incidence in Shenzhen city and help guide efforts to prevent foodborne disease. The data of foodborne diseases in Shenzhen comes from the infectious diarrhea surveillance network, community foodborne disease surveillance network, and student foodborne disease surveillance network. The incidence data from January 2012 to December 2017 was used for the model-constructing, while the data from January 2018 to December 2018 was used for the model-validating. The mean absolute percentage error (MAPE) was used to assess the performance of the model. The monthly foodborne disease incidence from January 2012 to December 2017 in Shenzhen was between 954 and 32,863 with an incidence rate between 4.77 and 164.32/100,000 inhabitants. The ARIMA (1,1,0) was an adequate model for the change in monthly foodborne disease incidence series, yielding a MAPE of 5.34%. The mathematical formula of the ARIMA (1,1,0) model was (1 − B) × log(incidencet) = 0.04338 + εt/(1 + 0.51106B). The predicted foodborne disease incidences in the next three years were 635,751, 1,069,993, 1,800,838, respectively. Monthly foodborne disease incidence in Shenzhen were shown to follow the ARIMA (1,1,0) model. This model can be considered adequate for predicting future foodborne disease incidence in Shenzhen and can aid in the decision-making processes. PubDate: 2022-03-01 DOI: 10.1007/s00003-021-01346-w
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Abstract: Abstract Matrix-assisted laser-desorption/ionization-time-of-flight-mass-spectrometry (MALDI-TOF-MS) is widely used to identify microorganisms. Recently, new applications such as identification of the animal species from meat, milk or fish are emerging. Standards for the validation of species identifications are still missing. Now, the § 64-LFGB working-group “MALDI-TOF”, established at the Federal Office of Consumer Protection and Food Safety, has compiled a guideline for the validation of species identifications. This guideline is intended for single laboratories as well as for lab networks and shows practical ways for validation of qualitative MALDI-TOF-MS methods. The special opportunities of the technology, in particular the use of extended reference databases and of collections of well-documented individual spectra for validation, have been taken into account in the guideline presented. PubDate: 2022-03-01 DOI: 10.1007/s00003-021-01353-x
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Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Phosphorus (P) is an important nutrient for all plant growth and it has become a critical and often imbalanced element in modern agriculture. A proper crop fertilization is crucial for production, farmer profits, and also for ensuring sustainable agriculture. The European Commission has published the Farm to Fork (F2F) Strategy in May 2020, in which the reduction of the use of fertilizers by at least 20% is among one of the main objectives. Therefore, it is important to look for the optimal use of P in order to reduce its pollution effects but also ensure future agricultural production and food security. It is essential to estimate the P budget with the best available data at the highest possible spatial resolution. In this study, we focused on estimating the P removal from soils by crop harvest and removal of crop residues. Specifically, we attempted to estimate the P removal by taking into account the production area and productivity rates of 37 crops for 220 regions in the European Union (EU) and the UK. To estimate the P removal by crops, we included the P concentrations in plant tissues (%), the crop humidity rates, the crop residues production, and the removal rates of the crop residues. The total P removal was about 2.55 million tonnes (Mt) (± 0.23 Mt), with crop harvesting having the larger contribution (ca. 94%) compared to the crop residues removal. A Monte-Carlo analysis estimated a ± 9% uncertainty. In addition, we performed a projection of P removal from agricultural fields in 2030. By providing this picture, we aim to improve the current P balances in the EU and explore the feasibility of F2F objectives. PubDate: 2022-02-05 DOI: 10.1007/s00003-022-01363-3
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Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract We aimed to quantify spray drift-based exposure of fruits and vegetables grown in gardens or allotments next to agricultural areas to plant protection products (PPP). The amount of spray drift transported into gardens during the treatment of tall growing crops or field crops was simulated. Two different test systems in an outdoor wind tunnel were used, approximating conditions for the application to both crop types. For the experiments, strawberries, tomatoes and lettuce were used representing non-target food crops in gardens. After spraying, distance-related residues of the tracer pyranine were measured on the three food crops positioned 1–15 m downwind in the non-target area. Additionally, petri dishes were placed in front of the food crops to measure the ground deposition concurrently. For both scenarios, good correlation of residues on the non-target food crops and the ground deposition was found (linear regression model, R2 = 0.88–0.97). But unlike the field crops scenario, the experimental setup of the tall growing crops shows large deviations from the field situation, not allowing the transfer of the results to the field situation. The results of the wind tunnel experiments and of field trials on ground deposition were used to estimate the amount of PPP residues on food crops cultivated near agricultural fields. For example, application of a pesticide (1.3 kg active ingredient per ha−1) to field crops was estimated to result in residue levels of 0.39 mg kg−1 on lettuce, 0.32 mg kg−1 on strawberries, and 0.06 mg kg−1 on tomatoes cultivated 5 m from the field, thus indicating an exceedance of the default maximum residue level (MRL) (0.01 mg kg−1). Therefore, further in-depth studies are required to broaden the range of non-target crops and to refine the tall growing crop scenario to allow estimations of spray drift-based residues. PubDate: 2022-01-17 DOI: 10.1007/s00003-021-01355-9
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Abstract: Abstract An international web meeting on the topic of operator safety for pesticide operators was held on 20–21 September 2021. The meeting provided an opportunity for experts from regulatory agencies, pesticide industry, the Food and Agriculture Organization (FAO), and other organizations to discuss operator safety in low- and middle-income countries (LMIC). The meeting focused on risk assessment and risk mitigation, the first steps to address operator safety. The key message at the meeting was the need for an operator exposure model that includes common hand-held scenarios used in LMIC and consistent personal protective equipment communication. The experts supported a transparent collaborative process that will enable us to build on the past efforts. PubDate: 2022-01-06 DOI: 10.1007/s00003-021-01359-5
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Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Hepatitis E virus (HEV) is a foodborne zoonotic pathogen and known as the causative agent of hepatitis E in humans. The specific role of porcine liver as a vehicle for human HEV infections has been highlighted in different studies. Nevertheless, gaps of knowledge still exist regarding possible HEV cross-contamination both at consumer and production level. Furthermore, people working in the food production industry, e.g. veterinarians and abattoir employees, are exposed to an increased risk of HEV infection. The aim of the present study was to investigate HEV cross-contamination on the surface of porcine liver in a German abattoir. The sample set included 250 samples of porcine liver parenchyma and the corresponding 250 superficial layer samples of the same livers, which were analyzed for the presence of HEV ribonucleic acid (RNA). Afterwards, the initial status of the tested liver parenchyma was compared with the occurrence of HEV RNA in the corresponding superficial layer. HEV RNA was detectable in 34% (85/250) of superficial layer samples, with 58% (49/85) of the samples originated from initially HEV negative livers. To our knowledge, this is the first study that provides an insight in the potential of HEV cross-contamination at abattoir level in Germany. Furthermore, it could be identified that the joint storage of livers in Euro meat containers has a significant impact on the presence of HEV RNA on the surface of porcine liver. PubDate: 2021-12-03 DOI: 10.1007/s00003-021-01357-7