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Cell walls are important structural components of plants, affecting both the bioaccessibility and subsequent digestibility of the nutrients that plant-based foods contain. These supramolecular structures are composed of complex heterogeneous networks primarily consisting of cellulose, and hemicellulosic and pectic polysaccharides. The composition and organization of these different polysaccharides vary depending on the type of plant tissue, imparting them with specific physicochemical properties. These properties dictate how the cell walls behave in the human gastrointestinal tract, and how amenable they are to digestion, thereby modulating nutrient release from the plant tissue. This short narrative review presents an overview of our current knowledge on cell walls and how they impact nutrient bioaccessibility and digestibility. Some of the most relevant methods currently used to characterize the food matrix and the cell walls are also described.

Rapid detection of the foodborne pathogen Salmonella in food processing is of crucial importance to prevent food outbreaks and to ensure consumer safety. Detection and quantification of Salmonella species in food samples is routinely performed using conventional culture-based techniques, which are labor intensive, involve well-trained personnel, and are unsuitable for on-site and high-throughput analysis. To overcome these drawbacks, many research teams have developed alternative methods like biosensors, and more particularly aptasensors, were a nucleic acid is used as biorecognition element. The increasing interest in these devices is related to their high specificity, convenience, and relative rapid response. This review aims to present the advances made in these last years in the development of biosensors for the detection and the quantification of Salmonella, highlighting applications on meat from the chicken food chain.

Color additives are widely used by the food industry to enhance the appearance, as well as the nutritional properties of a food product. However, some of these substances may pose a potential risk to human health, especially if they are consumed excessively and are regulated, giving great importance to their determination. Several matrix-dependent methods have been developed and applied to determine food colorants, by employing different analytical techniques along with appropriate sample preparation protocols. Major techniques applied for their determination are chromatography with spectophotometricdetectors and spectrophotometry, while sample preparation procedures greatly depend on the food matrix. In this review these methods are presented, covering the advancements of existing methodologies applied over the last decade.

The growth of and hemolysin production by two V. alginolyticus strains (HY9901 and ATCC 17749T) at 30°C were investigated in briny tilapia, shrimp, scallop, oyster, pork, chicken, freshwater fish, and egg fried rice. Bacteria were enumerated by plate counting. Hemolysin production was evaluated with blood agar and hemolytic titer tests. The two V. alginolyticus strains had similar growth and hemolysin production patterns in all tested foods. Based on the goodness-of-fit primary model statistics (coefficient of determination, mean square error, bias factor, and accuracy factor), the modified Gompertz model was a better fit than the logistic model to V. alginolyticus growth in foods. Growth kinetic parameters of V. alginolyticus had a higher μmax and shorter λ in the following order: briny tilapia > shrimp > freshwater fish > egg fried rice > scallop > oyster > chicken > pork. V. alginolyticus levels were similar at the stationary phase, with no significant growth difference between raw and cooked foods. Significantly higher thermostable direct hemolysin activity (P < 0.05) was found for V. alginolyticus in the following order: briny tilapia > freshwater fish > shrimp > chicken > egg fried rice > scallop > oyster > pork. However, the hemolytic titer was not consistent with the thermostable direct hemolysin activity and was significantly higher (P < 0.05) in the following order: briny tilapia > egg fried rice > shrimp > freshwater fish > chicken > scallop > oyster > pork. Contrary to current belief, V. alginolyticus produced more hemolysin in some nonseafoods (freshwater fish, egg fried rice, and chicken) than in scallops or oysters. This report is the first on the growth and toxicity of V. alginolyticus in different food matrices and confirms that some nonseafoods can be contaminated with pathogenic V. alginolyticus. These results should increase awareness of nonseafood safety issues and improve the accuracy of V. alginolyticus risk assessments.

Ensuring food safety requires a rapid and reliable method for detecting food-borne pathogens. Mass spectrometry has been demonstrated as a powerful tool to classify pure bacterial species. However, matrix interference from food backgrounds may lead to false results because of the suppression of microbial signals. It is useful to develop a method for bacterial enrichment and marker identification in food samples. Magnetic zirconia nanoparticles were used to concentrate spiked microorganisms from apple juice/lettuce under specific conditions (pH 4.5). Bacterial identification was achieved using nanoLC–MS. Selected reaction monitoring of bacteria-related peptides was applied for the first time to identify bacteria including Staphylococcus aureus and Escherichia coli. This study presents an accurate means for bacterial identification in food matrixes using MS. The analysis time is less than 90 min and the minimum concentration of E. coli detected was 5 × 103 CFU/mL. The interaction between bacteria and the magnetic nanoparticles was electrostatic and nonspecific, in contrast to immunoassays which require specific antibodies. The targeted peptide analysis focuses on the bacterial markers, thus significantly simplifying the analysis and leading to an accurate identification of bacteria. [Display omitted] •Selected reaction monitoring of bacteria-related peptides was applied to identify bacteria.•Proteotypic peptides were analyzed by nanoLC–ESI MS and database searching.•Magnetic zirconia particles efficiently concentrate the bacterial cells in food matrixes.

Nowadays, it is evident that food ingredients have different roles and distinct health benefits to the consumer. Over the past years, the interest in functional foods, especially those targeting gut health, has grown significantly. The use of industrial byproducts as a source of new functional and sustainable ingredients as a response to such demands has raised interest. However, the properties of these ingredients can be affected once incorporated into different food matrices. Therefore, when searching for the least costly and most suitable, beneficial, and sustainable formulations, it is necessary to understand how such ingredients perform when supplemented in different food matrices and how they impact the host’s health. As proposed in this manuscript, the ingredients’ properties can be first evaluated using in vitro gastrointestinal tract (GIT) simulation models prior to validation through human clinical trials. In vitro models are powerful tools that mimic the physicochemical and physiological conditions of the GIT, enabling prediction of the potentials of functional ingredients per se and when incorporated into a food matrix. Understanding how newly developed ingredients from undervalued agro-industrial sources behave as supplements supports the development of new and more sustainable functional foods while scientifically backing up health-benefits claims.

Climate change increases microbial contamination risks in food, highlighting the need for real-time biosensors. However, food residues often interfere with detection signals, limiting the direct application. An integrated system of filter-assisted sample preparation (FASP) and an immunoassay-based colorimetric biosensor offers the rapid and simple on-site detection of foodborne pathogens in complex food matrices. The accuracy and stability of biosensor analysis were ensured via filter-assisted preprocessing, which separated food residues from bacteria. The system was applied to various food matrices, including vegetables, meats, and cheese brine, using samples spiked at contamination levels ranging from 102 to 103 CFU per 25 g, thereby demonstrating broad applicability. Bacterial recovery varied by food matrix, with vegetables showing a 1-log reduction and meats, melon, and cheese brine showing a 2-log reduction relative to the initial inoculum. A detection limit of 101 CFU/mL was achieved for Escherichia coli O157:H7, Salmonella Typhimurium, and Listeria monocytogenes in the final preprocessed sample solutions. Sample preparation took under 3 min, and detection was completed within 2 h under stationary conditions. This approach enables rapid pathogen detection in various food matrices without the need for special reading devices, contributing to food safety as a real-time, rapid-response food biosensor.

Due to the heterogeneity among households across locations, predicting the impacts of stay-at-home mitigation and lockdown strategies for COVID-19 control is crucial. In this study, we quantitatively assessed the effects of the Namibia government’s lockdown control measures on food insecurity in urban informal settlements with a focus on Windhoek, Namibia. We developed three types of conditional regression models to predict food insecurity prevalence (FIP) scenarios incorporating household frequency of food purchase (FFP) as the impacting factor, based on the Hungry Cities Food Matrix. Empirical data were derived from the 2017 African Food Security Urban Network (AFSUN) Windhoek study and applied univariate probit and bivariate partial observability models to postulate the relation between food insecurity and FFP within the context of stay-at-home disease mitigation strategy. The findings showed that FFP was positively correlated with the prevalence of food insecurity (r = 0.057, 95% CI: 0.0394, 0.085). Daily purchases portrayed a survivalist behaviour and were associated with increased food insecurity (coeff = 0.076, p = 0.05). Only those who were purchasing food twice monthly were significantly associated with reduced food insecurity (coeff = −0.201, p = 0.001). Those households in informal settlements were severely impacted by food insecurity (coeff = 0.909, p-value = 0.007). We conclude that public health compliance should precede with cash or food support to poor households in balance with the need for long-term placement of control measures to fully contain COVID-19 or related infectious diseases.

The growth and hemolytic activity profiles of two Vibrio parahaemolyticus strains (ATCC 17802 and ATCC 33847) in shrimp, oyster, freshwater fish, pork, chicken, and egg fried rice were investigated, and a prediction system for accurate microbial risk assessment was developed. The two V. parahaemolyticus strains displayed a similar growth and hemolysin production pattern in the foods at 37°C. Growth kinetic parameters showed that V. parahaemolyticus displayed higher maximum specific growth rate and shorter lag time values in shrimp > freshwater fish > egg fried rice> oyster > chicken > pork. Notably, there was a similar number of V. parahaemolyticus in all of these samples at the stationary phase. The hemolytic activity of V. parahaemolyticus in foods increased linearly with time ( R > 0.97). The rate constant ( K) of hemolytic activity was higher in shrimp, oyster, freshwater fish, and egg fried rice than in pork and chicken. Significantly higher hemolytic activity of V. parahaemolyticus was evident in egg fried rice > shrimp > freshwater fish > chicken > oyster > pork. The above-mentioned results indicate that V. parahaemolyticus could grow well regardless of the food type and that contrary to current belief, it displayed a higher hemolytic activity in some nonseafood products (freshwater fish, egg fried rice, and chicken) than in one seafood (oyster). The prediction system consisting of the growth model and hemolysin production algorithm reported here will fill a gap in predictive microbiology and improve significantly the accuracy of microbial risk assessment of V. parahaemolyticus.

The recent detection of nuts (including peanut) in spices across the globe has led to enormous recalls of several spices and food products in the last two years. The lack of validated detection methods specific for spices makes it difficult to assess allergen presence at trace levels. Because of the urgent need for confirmation of possible peanut presence in chili peppers, an LC-MS/MS method was optimized and developed for this particular food matrix. Although several studies optimized LC-MS detection strategies specific for peanuts, the presence of complex components in the spices (e.g., phenolic components) makes method optimization and validation necessarily. Focus was laid on validation of the method with real incurred chili peppers (whereby a known amount of peanut is added) at low concentrations, to deal with possible matrix interferences. LC-MS/MS proves to be a good alternative to the currently most applied methods (ELISA and RT-PCR) and can be used as a complementary method of analysis when results are unclear. Peanut marker peptides were selected based on their abundancy in digested incurred chili peppers. The limit of detection was determined to be 24 ppm (mg peanut/kg), a level whereby the risk for potential allergic reactions is zero, considering the typical portion size of spices. The chili pepper powder under investigation proved to contain low levels of peanuts after LC-MS/MS, ELISA, and RT-PCR testing. Graphical abstract Standard curve of the detected peanuts in chili pepper samples using the novel LC-MS/MS method