Ultra violet-C pretreatment enhances the antimicrobial efficacy of unpeeled carrots against subsequent contamination with Listeria monocytogenes.

To our knowledge, this study is the first to elucidate the bactericidal efficacy of unpeeled carrots (hereafter referred to as carrots) pretreated with Ultra Violet-C (UV-C) against subsequent contamination with Listeria monocytogenes. Carrots pretreated with UV-C (240 mJ/cm2) exhibited a significant antilisterial effect within 2 h. In fact, the population of UV-C-pretreated carrots decreased from 7.94 log CFU/cm2 to levels below the limit of detection (LOD; <1.65 log CFU/cm2) within 24 h. For carrots that were not pretreated with UV-C, 3-4 log reductions were found after 24 h. Carrots pretreated with UV-C exhibited antimicrobial activity against another gram-positive pathogen, Staphylococcus aureus, but not against the gram-negative pathogens, E. coli O157:H7 and Salmonella enterica. Pretreatment with UV-C created a lasting antimicrobial effect as introducing L. monocytogenes on carrots, 72 h post-UV-C treatment, still maintained the antilisterial effect. Notably, all UV-C doses in the range of 48-240 mJ/cm2 induced a lasting antilisterial effect. The bactericidal effects against L. monocytogenes were confirmed in three varieties of washed and unwashed carrots (Danvers, Nantes, and Chantenay). Fluorescence microscopy confirmed the bactericidal effect of UV-C-pretreated carrots on the survival of L. monocytogenes. Conclusively, pretreating carrots with UV-C can reduce the population of L. monocytogenes to levels below the LOD and may further prevent pathogen growth during cold storage. Additional studies are necessary to discern the mechanism underlying the bactericidal efficacy of UV-C-pretreated carrots.

Small polystyrene microplastics interfere with the breakdown of milk proteins during static in vitro simulated human gastric digestion.

Human ingestion of microplastics (MPs) is common and inevitable due to the widespread contamination of food items, but implications on the gastric digestion of food proteins are still unknown. In this study, the interactions between pepsin and polystyrene (PS) MPs were evaluated by investigating enzyme activity and conformation in a simulated human gastric environment in the presence or absence of PS MPs. The impact on food digestion was also assessed by monitoring the kinetics of protein hydrolysis through static in vitro gastric digestion of cow's milk contaminated with PS. The binding of pepsin to PS showed that the surface chemistry of MPs dictates binding affinity. The key contributor to pepsin adsorption seems to be π-π interactions between the aromatic residues and the PS phenyl rings. During quick exposure (10 min) of pepsin to increasing concentrations (222, 2219, 22188 particles/mL) of 10 µm PS (PS10) and 100 µm PS (PS100), total enzymatic activities were not affected remarkably. However, upon prolonged exposure at 1 and 2 h, preferential binding of pepsin to the small, low zeta-potential PS caused structural changes in the protein which led to a significant reduction of its activity. Digestion of cow's milk mixed with PS10 resulted in transient accumulation of larger peptides (10-35 kDa) and reduced bioavailability of short peptides (2-9 kDa) in the gastric phase. This, however, was only observed at extremely high PS10 concentration (0.3 mg/mL or 5.46E+05 particles/mL). The digestion of milk peptides, bound preferentially over pepsin within the hard corona on the PS10 surface, was delayed up to 15 min in comparison to bulk protein digestion. Intact caseins, otherwise rapidly digested, remained bound to PS10 in the hard corona for up to 15 min. This work presents valuable insights regarding the interaction of MPs, food proteins, and pepsin, and their dynamics during gastric digestion.

Prediction of essential oil content in spearmint (Mentha spicata) via near-infrared hyperspectral imaging and chemometrics.

Spearmint (Mentha spicata L.) is grown for its essential oil (EO), which find use in food, beverage, fragrance and other industries. The current study explores the ability of near infrared hyperspectral imaging (HSI) (935 to 1720 nm) to predict, in a rapid, nondestructive manner, the essential oil content of dried spearmint (0.2 to 2.6% EO). Spectral values of spearmint samples varied considerably with spatial coordinates, and so the use of averaging the spectral values of a surface scan was warranted. Data preprocessing was done with Multiplicative Scatter Correction (MSC) or Standard Normal Variate (SNV). Selection of spectral input variables was done with Least Absolute Shrinkage and Selection Operator (LASSO), Principal Component Analysis (PCA) or Partial Least Squares (PLS). Regression was executed with linear regression (LASSO, PLS regression, PCA regression), Support Vector Machine (SVM) regression, and Multilayer Perceptron (MLP). The best prediction of EO concentration was achieved with the combination of MSC or SNV preprocessing, PLS dimension reduction, and MLP regression (1 hidden layer with 6 nodes), achieving a good prediction with a ratio of performance to deviation (RPD) of 2.84 ± 0.07, an R2 of prediction of 0.863 ± 0.008, and a RMSE of prediction of 0.219 ± 0.005% EO. These results show that NIR-HSI is a viable method for rapid, nondestructive analysis of EO concentration. Future work should explore the use of NIR in the visible spectrum, the use of HSI for determining EO in other plant materials and the potential of HSI to determine individual compounds in these solid plant/food matrices.

Hyperspectral Imaging and Chemometrics for Authentication of Extra Virgin Olive Oil: A Comparative Approach with FTIR, UV-VIS, Raman, and GC-MS.

Limited information on monitoring adulteration in extra virgin olive oil (EVOO) by hyperspectral imaging (HSI) exists. This work presents a comparative study of chemometrics for the authentication and quantification of adulteration in EVOO with cheaper edible oils using GC-MS, HSI, FTIR, Raman and UV-Vis spectroscopies. The adulteration mixtures were prepared by separately blending safflower oil, corn oil, soybean oil, canola oil, sunflower oil, and sesame oil with authentic EVOO in different concentrations (0-20%, m/m). Partial least squares-discriminant analysis (PLS-DA) and PLS regression models were then built for the classification and quantification of adulteration in olive oil, respectively. HSI, FTIR, UV-Vis, Raman, and GC-MS combined with PLS-DA achieved correct classification accuracies of 100%, 99.8%, 99.6%, 96.6%, and 93.7%, respectively, in the discrimination of authentic and adulterated olive oil. The overall PLS regression model using HSI data was the best in predicting the concentration of adulterants in olive oil with a low root mean square error of prediction (RMSEP) of 1.1%, high R2pred (0.97), and high residual predictive deviation (RPD) of 6.0. The findings suggest the potential of HSI technology as a fast and non-destructive technique to control fraud in the olive oil industry.

Measuring Circularity in Food Supply Chain Using Life Cycle Assessment; Refining Oil from Olive Kernel.

Valorization of food waste is a potential strategy toward a circular food supply chain. In this regard, measuring the circularity of food waste valorization systems is highly important to better understand multiple environmental impacts. Therefore, this study investigated the circularity of a food waste valorization system (refining oil from olive kernel) using a life cycle assessment methodology. An inventory of an industrial-based olive kernel oil production system is also provided in this study. The system boundary was the cradle to the factory gate of the production system. The results indicated that natural gas consumption was the highest contributor to most of the investigated impact categories. The global warming potential of one kg of oil produced from olive kernel was calculated to be 1.37 kg CO2eq. Moreover, the calculated damages of 1 kg oil production from olive kernel to human health, ecosystem quality, and resource depletion were 5.29 × 10-7 DALY, 0.12 PDF∙m2∙yr., and 24.40 MJ, respectively.

Association between bacterial survival and free chlorine concentration during commercial fresh-cut produce wash operation.

Determining the minimal effective free chlorine (FC) concentration for preventing pathogen survival and cross-contamination during produce washing is critical for developing science- and risk-based food safety practices. The correlation between dynamic FC concentrations and bacterial survival was investigated during commercial washing of chopped Romaine lettuce, shredded Iceberg lettuce, and diced cabbage as pathogen inoculation study during commercial operation is not feasible. Wash water was sampled every 30 min and assayed for organic loading, FC, and total aerobic mesophilic bacteria after chlorine neutralization. Water turbidity, chemical oxygen demand, and total dissolved solids increased significantly over time, with more rapid increases in diced cabbage water. Combined chlorine increased consistently while FC fluctuated in response to rates of chlorine dosing, product loading, and water replenishment. Total bacterial survival showed a strong correlation with real-time FC concentration. Under approximately 10 mg/L, increasing FC significantly reduced the frequency and population of surviving bacteria detected. Increasing FC further resulted in the reduction of the aerobic plate count to below the detection limit (50 CFU/100 mL), except for a few sporadic positive samples with low cell counts. This study confirms that maintaining at least 10 mg/L FC in wash water strongly reduced the likelihood of bacterial survival and thus potential cross contamination of washed produce.