Food Control最新文献

Contamination by aflatoxins and ochratoxin A of traditional Korean fermented soybean paste (Doenjang) is a serious food safety issue. In this study, we investigated the inhibitory effects of commercial Koji, a microbial starter culture used for fermentation, on mycotoxin contamination during Doenjang production at in vitro and scaled-up fermentation levels. A commercial Koji dominated by Aspergillus oryzae JI-4 exhibited strong antifungal and antimycotoxigenic activities against aflatoxigenic Aspergillus flavus and ochratoxigenic Penicillium verrucosum both in vitro and in situ. Furthermore, co-inoculation with Koji JI and mycotoxigenic fungi in the early stage of Doenjang fermentation significantly suppressed aflatoxins and ochratoxin A production by more than 93% (p < 0.05) and improved the nutritional properties and sensory qualities of the final product. These results suggest that the addition of commercial Koji could be an effective and practical approach to reduce aflatoxins and ochratoxin A contamination during the fermentation of soybean paste.

Watermelons and muskmelons are popular fruits among consumers worldwide which are sweet and have excellent nutritional composition. The quality detection of watermelon and muskmelon is an important factor in consumer preference, postharvest handling, and the commercial value of the fruit. Quality detection of watermelon and muskmelon has always been a challenging and essential task due to the uniqueness of their fruits and different application scenarios. Advances in optic and acoustic vibration techniques posted for their application in external and internal quality of watermelons and muskmelons, including machine vision, visible/near-infrared spectroscopy, hyperspectral imaging, and acoustic or vibration measurements. In this review, optic and acoustic vibration application in quality detection of watermelons and muskmelons with special emphasis on system composition, online equipment, merits, and limitations are presented. Moreover, the effectiveness of using multi-sensor information fusion technology for simultaneous detection of multiple quality is discussed. Furthermore, current challenges and future trends in this field are addressed. In particular, the multi-sensor-based commercial detection online equipment and smartphone-based mobile application will be the most useful tool for suppliers and consumers to assess the quality of watermelons and muskmelons.

Chia oil has high commercial value due to polyunsaturated fatty acids (PUFAs), especially α-linolenic acid (ALA), and suffers from tampering. Traditional adulterant detection in oils applies gas chromatography, but this approach has disadvantages such as time consumption. The development of fast analytical methods like infrared spectroscopy is important to detect oil fraud. The study aims to employ mid-infrared (FTIR) and chemometrics to detect adulteration in chia oil. Chia oil was extracted by cold pressing and adulterated with sunflower, corn, and soybean oils. FTIR-ATR spectra were obtained using a Fourier transform infrared spectrophotometer and horizontal attenuated reflectance accessory (HATR). Partial least square (PLS) models were adjusted to predict the adulteration content in chia oil and to predict the fatty acid content, including ALA. Gas chromatography was the reference method for the fatty acid content, and the adulteration content was known. The model obtained for adulteration content in chia oil had a high predictive capacity with r² = 0.9868 for the prediction set and a low limit of detection (1.47%) and limit of quantification (4.40%). The models for fatty acid content also had good prediction capabilities (0.90 < r², RMSE <21 mg g⁻¹, RSD <6.5%, LOD <12 mg g⁻¹, and LOQ <36 mg g⁻¹). The results indicate that it is possible to quantify fraud in chia oil even using different adulterants when analyzing FTIR-ATR spectra in tandem with PLS. The proposed method is an important, fast, low-cost alternative for monitoring adulterations in vegetable oils.

Vibrations during transportation inevitably lead to mechanical damage, endangering grape freshness and directly impacting their economic worth. While adequate packaging serves as a viable solution, current studies on packaging efficacy lack depth. Moreover, conventional methods for forecasting fruit freshness fail to accommodate the varying freshness levels of grapes across different packaging techniques. Consequently, a novel approach for predicting fruit freshness leveraging multi-sensing technology and machine learning algorithms is introduced. By reasonably evaluating packaging performance, the automation, intelligence, and accuracy of fruit freshness prediction are enhanced. Initially, critical control points in grape supply chain logistics were scrutinized using the HACCP method to identify key environmental parameters (vibration, temperature, and humidity) and their interaction with grape freshness. Subsequently, an environmental monitoring platform was devised for the grape supply chain, facilitating environmental surveillance under distinct packaging types (corrugated carton, foam box, plastic box, and inflatable package). Through a blend of environmental monitoring outcomes and physical-chemical indicators, the protective efficacy of diverse transport packaging was meticulously analyzed and appraised alongside finite element analysis. Notably, environmental data proved capable of characterizing grape freshness in lieu of quality data, with vibration metrics exhibiting strong correlations with quality metrics. Machine learning models were developed to predict grape freshness based on environmental cues, yielding prediction accuracies of 92.512% (SVM) and 94.334% (GA-ANN). The automated, non-destructive data acquisition and novel machine learning approaches offer a fresh avenue for evaluating packaging, predicting freshness, and managing food quality within grape logistics operations.

This study aims to explore the presence of mycotoxins in total mixed rations (TMR) employed for feeding dairy cattle and their potential carry-over to milk. A total of 87 TRM samples were collected in farms from the north of Portugal from 2019 to 2022. A method based on a QuEChERS extraction followed by UHPLC-MS/MS detection was employed for sample analysis. The method was in-house validated in terms of matrix effect, linearity, sensitivity, accuracy and precision. The most frequently detected regulated toxins were fumonisins, with a positivity rate of 74%, while deoxynivalenol and zearalenone were found in approximately 35% of the samples. Among the emerging toxins, beauvericin and enniatins exhibited the highest detection rates. In addition, milk samples were collected from 21 farms, providing insights into the carry-over of these toxins and roquefortine to milk, with an estimated rate ranging between 2% and 10%.

In order to develop the plant-derived active substance vanillin, 2-hydroxypropyl-β-cyclodextrin was used to encapsulate vanillin, and a chitosan-based edible coating: vanillin-HPβCD/CH was developed for chicken preservation. First, vanillin was inserted into the internal cavity of HPβCD through an ultrasonic-assisted method to form vanillin/HPβCD-IC. The inclusion complex of vanillin/HPβCD-IC was demonstrated to be successfully synthesized by ultraviolet–visible spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM). Through antibacterial testing, thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), it was verified that inclusion improved the thermal stability of vanillin while retaining the antibacterial effect of vanillin. The release of vanillin from encapsulated particle exhibited pH-dependent slow controlled release, and can described by First order model. Subsequently, vanillin/HPβCD-IC was compounded with chitosan through a composite film-forming method to prepare an edible coating: vanillin-HPβCD/CH. By characterizing the performance of vanillin-HPβCD/CH, it was found that the addition of vanillin/HPβCD-IC can improve the stability, isolation hydrophobicity and antibacterial performance of the plastic wrap. Finally, vanillin-HPβCD/CH was applied to chicken preservation, and it was found that vanillin-HPβCD/CH could effectively extend the shelf life of chicken and maintain sensory quality by slowing down the rise in pH, preventing the proliferation of microorganisms, and inhibiting lipid oxidation. In summary, vanillin-HPβCD/CH is an edible coating with superior performance and a promising packaging material for chicken freshness preservation.

Queen bee larvae (QBL), a by-product of royal jelly production, have nutritional value and confer health benefits. The commercialization of QBL is hindered because of the lack of evidence for its nutrition and safety parameters. Thus, this study was conducted to investigate the microbial dynamics, nutritional composition, and antioxidant activity of QBL, aiming to assess its potential as a food product. Lyophilized QBL powder samples were sterilized through gamma irradiation and high-pressure processing at varying doses and pressures. Gamma irradiation at 10 and 15 kGy effectively reduced the total aerobic count to 0, whereas high-pressure processing led to no significant reduction. Regarding the microbial profile of QBL, 16S rDNA gene sequencing unveiled five bacteria—Acinetobacter pittii, Bacillus thuringiensis, Enterococcus mundtii, Enterococcus faecalis, and Fructobacillus fructosus—but no major foodborne pathogens. Lactobacillus, Bombella, and Fructobacillus emerged as the predominant genera in QBL, with low abundances of Staphylococcus and Escherichia. Proximate composition analysis indicated no significant postirradiation changes in macronutrient contents; notably, protein was the predominant component (approximately 48.0%). Sugar and amino acid analyses revealed essential nutrients meeting human dietary requirements. Upon fatty acid analysis, palmitic and oleic acids emerged as predominant fatty acids. Gamma irradiation at 10 kGy exerted no significant effect on the nutritional composition or antioxidant activity of QBL. Our study provides valuable insights into the microbial safety and nutritional value of QBL, indicating its potential as a dietary protein source with favorable microbiota.

The objective of this study was to investigate the results of the two Brazilian national pesticide residue monitoring programs obtained from January 2010 to December 2020. A total of 35,321samples of 44 different food crops were analyzed, of which 55.3% tested positive for at least one compound, with pear, peach, strawberry and sweet pepper having over 90% of the analyzed samples containing residues. Approximately one-third of the positive samples had at least one irregularity, of which 86.7% due to the presence of non-authorized pesticides for the crop, 26.3% exceeding the maximum residue level, and 13.1% showing both irregularities. A total of 191 different compounds were detected, primarily organophosphorus (OP) (37.4% of positive samples, of which over 60% of cereal/flour, potatoes, and peanuts). Chlorpyrifos, acephate, pirimiphos-methyl, and methamidophos were the main OPs detected. Triazoles were present in 27.2% of the positive samples, mainly rice, and pyrethroids in 22.4% of the positive samples, mainly in popcorn. Dithiocarbamates were present in 19.7% of the positive samples, predominantly in apples, and 5.0% of the positive samples contained N-methyl carbamates, mainly in sweet peppers. Carbendazim was the most detected pesticide (30% of positive samples), mainly in papaya (18.2% of samples containing this pesticide). About 60% of positive samples contained multiple residues, primarily in sweet pepper, pear, strawberry, and orange (over 80% of positive samples). Compared to the previous decade (2001–2010), these results indicated increased percentages of positive, irregular and of samples containing multiple residues. Dithiocarbamates were no longer the most detected pesticide group, while carbendazim remained the most detected pesticide in both periods.

Olive oil, being very salubrious, is one of the main ingredients of the Mediterranean diet. However, high oil prices combined with high consumption have increasingly subjected olive oils to fraudulent practices. The large rise in numbers of producers engaging in this illicit practice has made it necessary to develop a swift, convenient, and consistent analytical methodology to detect adulterating oil products and ensure product quality. In this study, we have merged multivariate statistical analysis with one-dimensional (1D) 700 MHz ¹H nuclear magnetic resonance (NMR) to analyze different types of vegetable and olive oil.

Additionally, we have spiked virgin olive oil with varying percentages (1%–75% (v/v)) of other vegetable oils to obtain the spectra of adulterated olive oil. As a result, the method applied in our study can not only detect adulterated olive oils but also identify mixed adulterants. Ease of sample preparation, quick sample analysis, and straightforward data comprehension distinguishes this method from the currently published ones.

Staphylococcus aureus (S. aureus) is a significant food-borne pathogen that poses a threat to human health. The classical serotypes staphylococcal enterotoxin (SE) A, B, C1, C2, C3, D, E produced by S. aureus are the primary cause of its food-borne pathogenic toxicity. Therefore, establishing a highly sensitive, rapid, robust, high-throughput detection method for the total amount of classical serotypes of SEs is crucial for food safety and public health. This study prepared 10 rabbit polyclonal antibodies and 40 mouse monoclonal antibodies targeting SEA, SEB, SEC1, SEC2, SEC3. Upon identifying the optimal antibody pairs through square array method and optimization, a sandwich ELISA kit for the detection of SEs (SEA, SEB, SEC1, SEC2, SEC3, SED, SEE) was developed, with respective limits of detection at 0.169–0.688 ng/mL. In addition, this sandwich ELISA kit could detect SEs in raw cow milk, pasteurized milk, fermented milk, milk powder, whey powder, rice, raw pork, and canned beef samples with coefficients of variation below 7%. Meanwhile, this sandwich ELISA kit was stable at 4 °C for one-year storage. The study fills a research gap in the detection of the total amount of classical serotypes of SEs.