Journal of Food Safety最新文献

Incidence of foodborne illness due to bacterial contamination of fresh produce continue to exist despite continuous research on processing interventions to mitigate the problem. In this study, we combined atmospheric cold plasma treatments with an antimicrobial solution containing specific organic acids generally recognized as safe (GRAS) by the FDA and tested its antimicrobial efficacy against Salmonella enterica inoculated on tomato surfaces. Tomato surfaces were inoculated with at 5.6 log CFU/g of Salmonella by spotting 0.1 mL of 7 log CFU/ml Salmonella onto the tomato stem scars, and by dipping whole tomatoes into a solution of 7 log CFU/ml Salmonella for 3 min to achieve 4.1 log CFU/g. Antimicrobial efficacy of the organic acid-based sanitizer + cold plasma treatments for 30, 60, 120, 180, and 360 s, were investigated, and significant bacterial inactivation was achieved above 120 s treatments. At 120 s, surviving populations of aerobic mesophilic bacteria recovered on the tomatoes surfaces averaged < 2 logs/g while yeast and mold survival averaged < 1 CFU/g. Treatment combination with this organic acid-based sanitizer + cold plasma for 120 s resulted in a 4.9 log reduction of Salmonella on the stem scar area and a 3.9 log reduction on the smooth peel surface. Similarly, populations of aerobic mesophilic bacteria recovered on treated tomato surfaces averaged < 0.3 log CFU/g. The results of this study indicate that combining an organic acid-based sanitizer with cold plasma treatments for ≥ 120 s can inactivates significant populations of Salmonella to enhance the microbial safety of tomato surfaces designated for fresh-cut salad.

Traditionally methods for assessing mutton quality rely on physical and chemical examination analyses that necessitate precise experimental environment conditions and specialized knowledge, often resulting in the compromise of the sample's structural integrity. To address these challenges, this study explores the application of near-infrared spectroscopy (NIR) as a non-destructive alternative for mutton quality evaluation, leveraging its operational simplicity, rapid analysis capabilities, and minimal requirement for technical expertise. Among various spectral data preprocessing techniques evaluated, multiple scattering correction (MSC) was found to significantly enhance model detection performance. Furthermore, principal component analysis (PCA) combined with the Mahalanobis Distance method was utilized for outlier identification. Finally, a mutton freshness detection model is constructed based on stacking ensemble learning, yielding an impressive accuracy rate of 0.976, outperforming other advanced approaches. In conclusion, our findings establish a robust theoretical framework for the rapid and non-destructive assessment of meat freshness, contributing to advancements in meat quality detection.

The impact of pulsed light treatment (PLT) on natural microbiota and inoculated microbes such as Salmonella Typhimurium, Bacillus cereus, and Aspergillus flavus on red chilies was investigated. Sequential drying did not completely inactivate the aerobic mesophiles and yeast and mold count. Hence, PLT (0.53–2.59 J cm⁻²) was employed as a decontamination technology on red chilies. PLT resulted in 8 log reduction of inoculated microorganisms on chilies at 2.59 J cm⁻². The microbial inactivation kinetics followed Weibull distribution (R² > 0.97) with β value of 1.1, 1.2, and 1.5 for S. Typhimurium, B. cereus, and A. flavus, respectively. Changes in structure and composition of cell components were identified by SEM and FTIR analysis. After PLT, phenolics, antioxidants, flavonoids, and capsaicinoids were better retained but a significant change in ascorbic acid and carotenoid's content was observed. Hence, PL can be a potential technology for decontamination of fresh and dried chilies along with maximum retention of bioactives.

Black bean skin anthocyanins (BBSAs), as by-products of black beans, have not been fully exploited. BBSAs are rich in anthocyanins and have a wide range of health benefits. In this study, the antibacterial and antibiofilm action mode of BBSAs against Vibrio parahaemolyticus (V. parahaemolyticus) was evaluated. The antibacterial and antibiofilm efficiency was evaluated under different conditions, shedding light on their mode of action against V. parahaemolyticus. The results showed that the inactivation efficacy of BBSAs on V. parahaemolyticus was positively correlated with its concentration and incubating time. The MIC value for BBSAs was determined to be 10 μg/mL. The formation of V. parahaemolyticus biofilm was hindered by the presence of the BBSAs, especially at higher concentrations of BBSAs and during the early intervention stage. After exposure to 1 MIC of BBSA, the inhibition rate of biofilm reached 91.94%. The release of cellular components and alterations in membrane morphology indicated that BBSAs can damage the integrity of V. parahaemolyticus cell membrane. Furthermore, BBSAs may interact with membrane proteins, causing a notable conformational change in membrane proteins. HPLC and UPLC-MS analysis confirmed that the major antibacterial compound in BBSAs was Cyanidin-3-O-glucoside (C3G), which can form a stable complex with LolB protein in the outer membrane via hydrogen bonding. This study can provide strong technical support for the accurate control of V. parahaemolyticus and pave the way for the application of natural antibacterial agents in the realm of food-borne bacterial control.

Tempe has gained global popularity, with local vegetable oils commonly used for frying. This study evaluates the cooking temperature and stability of five vegetable oils (olive [Oo], palm [Po], canola [Cnlo], sunflower [Sfo], and coconut [Cco]) for deep-frying Tempe, using acid and peroxide values (AV and PV), antiradical activity, and saturated and unsaturated fatty acids. AV, PV, and linolenic acid (LNA) were referenced to international standards for vegetable oil (0.6 mg KOH/g, 10 mEq of oxygen/kg oil, and 2% for AV, PV, LNA respectively). The initial oil temperature was 130°C ± 1°C, with final temperatures between 145.7°C ± 6.8°C at the lowest and 156.8°C ± 13.0°C at the highest, well below existing studies (≥170°C–250°C). Based on AV and PV, Oo, Po, and Cco were stable up to the fourth, fifth, and eighth frying repeat (FR). The PV of Cnlo (10.2 mEq of oxygen/kg oil) and Sfo (15.5 mEq of oxygen/kg oil) exceeded the maximum limit after one use. The Fresh Cnlo LNA (7.35%) was higher than the limit, while the rest of the oils remained lower and stable until the seventh FR. Po exhibited the highest average antiradical activity (85.42% ± 4.63%), followed by Oo (31.01% ± 10.26%), Sfo (27.96% ± 9.67%), Cnlo (21.85% ± 5.71%), and Cco (14.40% ± 3.46%). Cco had the highest saturated fatty acids (SFA), Oo had the highest monounsaturated fatty acids (MUFA), and Sfo had the highest polyunsaturated fatty acids (PUFA). No significant SFA, MUFA, or PUFA changes were observed up to the seventh FR. Trans-fatty acids C18:1n 9T and C18:2n 6T were undetected in fresh and used oil, indicating a unique character in low-temperature deep-frying in domestic settings. This study provides a comprehensive analysis of low-temperature deep-frying of Tempe. It suggests that Oo, Po, Cnlo, Sfo, and Cco were stable to deep-fried Tempe for four, five, zero, one, and eight FR, respectively. Deep-frying Tempe at lower temperatures and for a shorter duration may enhance its health benefits and help retain its flavor.”

Sprouts are popular due to their high nutritional content, including vitamins, minerals, antioxidants, and enzymes. However, the conditions favorable for sprouting, such as warm and humid environments, are also ideal for the growth of bacteria, including food-borne pathogens. Here, we analyzed the growth and developed predictive models of locally isolated and commercial strains of Salmonella enterica and Listeria monocytogenes in alfalfa sprouts under various constant temperatures, ranging from 5°C to 25°C. Our findings indicated that these pathogens could grow at 5°C in sprouts, albeit with a low growth rate. A rapid increase in concentration occurred at temperatures of 10°C and above. The fitted models demonstrated high performance, with R² values ranging from 0.964 to 0.997 and RMSE values ranging from 0.15 to 0.51, respectively. Based on the fitted values, bias factor (A_f) values varied between 1.01 and 1.06, with all accuracy factor (B_f) values at 1.00. Acceptable prediction zone (APZ) values ranged from 81.8% to 100%. Validation of the models under dynamic temperature conditions for specific strains showed acceptable performance. This study enhances our understanding of S. enterica and L. monocytogenes growth in alfalfa sprouts. The findings of this study could be used to improve the risk assessment of these pathogens in alfalfa sprouts.

In the present study, the ethanolic extracts derived from Hass avocado pulp were observed to exhibit exceptional bioactive qualities and demonstrate bactericidal efficacy against a wide range of microorganisms, encompassing both gram-positive and gram-negative bacteria, as well as fungi. Therefore, this work aimed to develop a biodegradable active film by incorporating the Hass avocado extracts into chitosan/gelatin-based film (HGCF) for the preservation of beef and pork. The study reveals that the chitosan/gelatin-based film (GCF) and HGCF exhibit significant water stability and absorption capabilities. HGCF offered the synergy of antimicrobial properties of Hass avocado extracts and high swelling in water of chitosan/gelatin blend to absorb liquid discharged from fresh meat for prolonged storage. HGCF demonstrated a significant effectiveness in controlling microbial density in comparison to uncoated samples and samples coated with plain gelatin/chitosan film. In detail, HGCF was able to partially eliminate Staphylococcus aureus and Escherichia coli during storage, resulting in the densities after 14 days that were similar to those of uncoated meat samples after 6 days. These results demonstrate the potential of HGCF as active packaging for food preservation and advance the sustainable production and preservation of meat products.

To address the challenges posed by chemical methods for detecting pesticide residues in sorghum, such as complicated sample preparation and prolonged detection periods, this study presents a rapid and nondestructive detection approach based on hyperspectral imaging (HSI) technology. A group of sorghum without pesticide residues and three groups uniformly sprayed with pesticides were used in this study. Firstly, support vector machine (SVM) classification models were built using spectral data preprocessed with Savitzky–Golay (SG), discrete wavelet transform (DWT), and standard normal variate (SNV) methods, respectively, and SNV was determined to be the best preprocessing method. Secondly, the gradient boosting decision tree (GBDT) algorithm, principal component analysis (PCA), and the successive projections algorithm (SPA) were respectively used to extract feature wavelengths. Pesticide residue identification models based on full and feature wavelengths were then respectively established using backpropagation neural network (BPNN), SVM, and partial least squares discriminant analysis (PLS-DA). The results show that the BPNN model developed using the feature wavelengths obtained from GBDT was the best for identification of pesticide residues, with an accuracy of 97.8% for both the training and testing sets. Finally, visualization of pesticide residue species in sorghum was achieved using the optimal model. This study demonstrates that utilizing HSI in conjunction with the GBDT-BPNN model is an effective, rapid, and nondestructive method for identifying pesticide residues in sorghum.