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Nowadays, the consumption of food products containing probiotics, has increased worldwide due to concerns regarding healthy diet and wellbeing. This trend has received a lot of attention from the food industries, aiming to produce novel probiotic foods, and from researchers, to improve the existing methodologies for probiotic delivery or to develop and investigate new possible applications. In this sense, edible films and coatings are being studied as probiotic carriers with many applications. There is a wide variety of materials with film-forming ability, possessing different characteristics and subsequently affecting the final product. This manuscript aims to provide significant information regarding probiotics and active/bioactive packaging, to review applications of probiotic edible films and coatings, and to discuss certain limitations of their use as well as the current legislation and future trends.

Over the years, technology has changed the way we produce and have access to our food through the development of applications, robotics, data analysis, and processing techniques. The implementation of these approaches by the food industry ensure quality and affordability, reducing at the same time the costs of keeping the food fresh and increase productivity. A system, as the one presented herein, for raw food categorization is needed in future food industries to automate food classification according to type, the process of algorithm approaches that will be applied to every different food origin and also for serving disabled people. The purpose of this work was to develop a machine learning workflow based on supervised PLS regression and SVM classification, towards automated raw food categorization from FTIR. The system exhibited high efficiency in multi-class classification of 7 different types of raw food. The selected food samples, were diverse in terms of storage conditions (temperature, storage time and packaging), while the variability within each food was also taken into account by several different batches; leading in a classifier able to embed this variation towards increased robustness and efficiency, ready for real life applications targeting to the digital transformation of the food industry.

As years progress, we are found more often in a postprandial than a postabsorptive state. Chrononutrition is an integral part of metabolism, pancreatic function, and hormone secretion. Eating most calories and carbohydrates at lunch time and early afternoon, avoiding late evening dinner, and keeping consistent number of daily meals and relative times of eating occasions seem to play a pivotal role for postprandial glycemia and insulin sensitivity. Sequence of meals and nutrients also play a significant role, as foods of low density such as vegetables, salads, or soups consumed first, followed by protein and then by starchy foods lead to ameliorated glycemic and insulin responses. There are several dietary schemes available, such as intermittent fasting regimes, which may improve glycemic and insulin responses. Weight loss is important for the treatment of insulin resistance, and it can be achieved by many approaches, such as low-fat, low-carbohydrate, Mediterranean-style diets, etc. Lifestyle interventions with small weight loss (7–10%), 150 min of weekly moderate intensity exercise and behavioral therapy approach can be highly effective in preventing and treating type 2 diabetes. Similarly, decreasing carbohydrates in meals also improves significantly glycemic and insulin responses, but the extent of this reduction should be individualized, patient-centered, and monitored. Alternative foods or ingredients, such as vinegar, yogurt, whey protein, peanuts and tree nuts should also be considered in ameliorating postprandial hyperglycemia and insulin resistance. This review aims to describe the available evidence about the effects of diet, chrononutrition, alternative dietary interventions and exercise on postprandial glycemia and insulin resistance.

Unsafe food is estimated to cause 600 million cases of foodborne disease, annually. Thus, the development of methods that could assist in the prevention of foodborne diseases is of high interest. This review summarizes the recent progress toward rapid microbial assessment through (i) spectroscopic techniques, (ii) spectral imaging techniques, (iii) biosensors and (iv) sensors designed to mimic human senses. These methods often produce complex and high-dimensional data that cannot be analyzed with conventional statistical methods. Multivariate statistics and machine learning approaches seemed to be valuable for these methods so as to “translate” measurements to microbial estimations. However, a great proportion of the models reported in the literature misuse these approaches, which may lead to models with low predictive power under generic conditions. Overall, all the methods showed great potential for rapid microbial assessment. Biosensors are closer to wide-scale implementation followed by spectroscopic techniques and then by spectral imaging techniques and sensors designed to mimic human senses.

The objective of this work was the isolation and characterization of Alicyclobacillus acidoterrestris strains from orange juice. In all, 72 isolates were recovered from commercial orange juice bought from the Greek market. The isolates were subjected to polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) to discriminate them at strain level and A. acidoterrestris types I and II. The restriction patterns of 16S rRNA gene revealed that isolates were categorized in different groups depending on the restriction endonucleases. Moreover, the digestion of the part of vdc operon gene with HphI restriction enzyme successfully differentiated between A. acidoterrestris types I and II. In conclusion, RFLP succeeded in differentiating A. acidoterrestris isolates at strain and type levels.

Fruit juices have an important place in humans’ healthy diet. They are considered to be shelf stable products due to their low pH that prevents the growth of most bacteria. However thermo-acidophilic endospore forming bacteria of the genus Alicyclobacillus have the potential to cause spoilage of commercially pasteurized fruit juices. The flat sour type spoilage, with absence of gas production but presence of chemical spoilage compounds (mostly guaiacol) and the ability of Alicyclobacillus spores to survive after pasteurization and germinate under favorable conditions make them a major concern for the fruit juice industry worldwide. Their special characteristics and presence in the fruit juice industry has resulted in the development of many isolation and identification methods based on cell detection (plating methods, ELISA, flow cytometry), nucleic acid analysis (PCR, RAPD-PCR, ERIC-PCR, DGGE-PCR, RT-PCR, RFLP-PCR, IMS-PCR, qPCR, and 16S rRNA sequencing) and measurement of their metabolites (HPLC, GC, GC-MS, GC-O, GC-SPME, Electronic nose, and FTIR). Early detection is a big challenge that can reduce economic loss in the industry while the development of control methods targeting the inactivation of Alicyclobacillus is of paramount importance as well. This review includes a discussion of the various chemical (oxidants, natural compounds of microbial, animal and plant origin), physical (thermal pasteurization), and non-thermal (High Hydrostatic Pressure, High Pressure Homogenization, ultrasound, microwaves, UV-C light, irradiation, ohmic heating and Pulse Electric Field) treatments to control Alicyclobacillus growth in order to ensure the quality and the extended shelf life of fruit juices.

The expansion of the seaweed aquaculture sector along with the rapid deterioration of these products escalates the importance of implementing rapid, real-time techniques for their quality assessment. Seaweed samples originating from Scotland and Ireland were stored under various temperature conditions for specific time intervals. Microbiological analysis was performed throughout storage to assess the total viable counts (TVC), while in parallel FT-IR spectroscopy, multispectral imaging (MSI) and electronic nose (e-nose) analyses were conducted. Machine learning models (partial least square regression (PLS-R)) were developed to assess any correlations between sensor and microbiological data. Microbial counts ranged from 1.8 to 9.5 log CFU/g, while the microbial growth rate was affected by origin, harvest year and storage temperature. The models developed using FT-IR data indicated a good prediction performance on the external test dataset. The model developed by combining data from both origins resulted in satisfactory prediction performance, exhibiting enhanced robustness from being origin unaware towards microbiological population prediction. The results of the model developed with the MSI data indicated a relatively good prediction performance on the external test dataset in spite of the high RMSE values, whereas while using e-nose data from both MI and SAMS, a poor prediction performance of the model was reported.

Biofilm formation is a phenomenon occurring almost wherever microorganisms and surfaces exist in close proximity. This study aimed to evaluate the possible influence of bacterial interactions on the ability of Listeria monocytogenes and Pseudomonas putida to develop a dual-species biofilm community on stainless steel (SS), as well as on the subsequent resistance of their sessile cells to benzalkonium chloride (BC) used in inadequate (sub-lethal) concentration (50 ppm). The possible progressive adaptability of mixed-culture biofilms to BC was also investigated. To accomplish these, 3 strains per species were left to develop mixed-culture biofilms on SS coupons, incubated in daily renewable growth medium for a total period of 10 days, under either mono- or dual-species conditions. Each day, biofilm cells were exposed to disinfection treatment. Results revealed that the simultaneous presence of L. monocytogenes strongly increased the resistance of P. putida biofilm cells to BC, while culture conditions (mono-/dual-species) did not seem to significantly influence the resistance of L. monocytogenes biofilm cells. BC mainly killed L. monocytogenes cells when this was applied against the dual-species sessile community during the whole incubation period, despite the fact that from the 2nd day this community was mainly composed (>90%) of P. putida cells. No obvious adaptation to BC was observed in either L. monocytogenes or P. putida biofilm cells. Pulsed field gel electrophoresis (PFGE) analysis showed that the different strains behaved differently with regard to biofilm formation and antimicrobial resistance. Such knowledge on the physiological behavior of mixed-culture biofilms could provide the information necessary to control their formation.

The aim of the study was to evaluate the efficacy of oregano essential oil (OEO) incorporated in Na-alginate edible films when applied to sliced ham inoculated with a cocktail of Listeria monocytogenes strains, with or without pretreatment by high pressure processing (HPP). Microbiological, physicochemical and sensory analyses (in Listeria-free slices) were performed, while, the presence/absence and the relative abundance of each Listeria strain, was monitored by pulsed field gel electrophoresis (PFGE). The OEO incorporation in the films, caused approximately 1.5 log reduction in Listeria population at 8 and 12 °C at the end of the storage period, and almost 2.5 log reduction at 4 °C. The HPP treatment caused 1 log reduction to the initial Listeria population, while levels kept on decreasing throughout the storage for all the tested temperatures. The pH of the samples was higher in the cases where HPP was involved, and the samples were evaluated as less spoiled. Furthermore, the presence of OEO in the films resulted in color differences compared to the control samples, whilst the aroma of these samples was improved. In conclusion, the combined application of HPP and OEO edible films on the slices, led to a significant reduction or absence of the pathogen.

A study on the occurrence of Aspergillus section Nigri species on grapes from four traditional grape-producing areas in Greece during the 2011/2012 vintage, and their capability to produce OTA was conducted. One hundred and twenty-eight black aspergilli isolates were characterised at the species level initially by the use of morphological criteria in accordance with appropriate keys, followed by molecular characterisation performed with Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) of the 5.8 ribosomal RNA gene Internal Transcribed Spacer region (5.8 rRNA ITS). Restriction enzyme digestion of the ITS amplicons using the HhaI, HinfI and RsaI, endonucleases distinguished eleven different patterns of restriction fragment length polymorphism (RFLP), four for each of the HhaI and RsaI digests and three for HinfI. From a total number of 128 individual isolates, 124 were classified into four Aspergillus species corresponding to A. carbonarius, A. tubingensis, A. japonicus and A. ibericus, and the remaining 4 were classified as members of the A. niger aggregate. A. carbonarius and A. tubingensis being the main representative species were equally counted, with higher geographical representation of the former in southern and the latter in northern regions, respectively. All isolates were tested for their ochratoxigenic potential by use of High Performance Liquid Chromatography (HPLC) and Enzyme Linked Immuno Sorbent Assay (ELISA), resulting in significant interspecies differences in OTA production.