Scalability of the cooling die unit operation is critical to lowering the manufacturing cost of high moisture meat analogs(HMMA), but it is unclear what scale-up criteria are important. An experiment consisting of two cooling die cross-section geometries (tall and narrow or short and wide), two production rates (2.7 or 4.5 kg/hr) and 4 cooling media inlet temperatures (36, 48, 60, and 72 °C) was employed to study their effect on product texture, anisotropy, and extrusion system parameters. Comprehensive temperature measurements were made along the dies to observe the product temperature gradient and to quantify the energy balance associated with cooling. It was found that textural hardness had a positive relationship with axial temperature gradient (p < 0.05), while anisotropy had a negative and positive relationship with axial temperature gradient and die height, respectively (p < 0.05). Extruder motor torque and die inlet pressure were found to be functions of the cooling media inlet temperature and apparent Newtonian shear rate applied to the material in the die (p < 0.05). The energy balance indicated that enhanced anisotropy is associated with more exothermic in-situ phase changes, which are controlled by the product formulation and applied die conditions. There are likely 3 scalable variables most relevant to controlling the HMMA product quality: 2 critical phase transition temperatures, and the axial product temperature gradient. Therefore, scaling up HMMA cooling dies will require balancing the heat transfer rate away from the product such that an optimal product temperature profile can be maintained at scale.

Research on the content of polyphenolic compounds in fruits and vegetables, the extraction of bioactive compounds, and the study of their impact on the human body has received growing attention in recent years. This is due to the great interest in bioactive compounds and their health benefits, resulting in increased market demand for natural foods. Bioactive compounds from plants are generally categorized as natural antioxidants with health benefits such as anti-inflammatory, antioxidant, anti-diabetic, anti-carcinogenic, etc. Thermal processing has been used in the food sector for a long history. Implementing different thermal processing methods could be essential in retaining the quality of the natural antioxidant compounds in plant-based foods. A comprehensive review is presented on the effects of thermal blanching (i.e., hot water, steam, superheated steam impingement, ohmic and microwave blanching), pasteurization, and sterilization and drying technologies on natural antioxidants in fruits and vegetables.

BACKGROUND: Real-time monitoring of food consumer quality remains challenging due to diverse bio-chemical processes taking place in the food matrices, and hence it requires accurate analytical methods. Thresholds to determine spoiled food are often difficult to set. The existing analytical methods are too complicated for rapid in situ screening of foodstuff.
RESULTS: We have studied the dynamics of meat spoilage by electronic nose (e-nose) for digitizing the smell associated with volatile spoilage markers of meat, comparing the results with changes in the microbiome composition of the spoiling meat samples. We apply the time series analysis to follow dynamic changes in the gas profile extracted from the e-nose responses and to identify the change-point window of the meat state. The obtained e-nose features correlate with changes in the microbiome composition such as increase in the proportion of Brochothrix and Pseudomonas spp. and disappearance of Mycoplasma spp., and with representative gas sensors towards hydrogen, ammonia, and alcohol vapors with R2 values of 0.98, 0.93, and 0.91, respectively. Integration of e-nose and computer vision into a single analytical panel improved the meat state identification accuracy up to 0.85, allowing for more reliable meat state assessment.
CONCLUSIONS: Accurate identification of the change-point in the meat state achieved by digitalizing volatile spoilage markers from the e-nose unit holds promises for application of smart miniaturized devices in food industry.

The food industry is a significant contributor to carbon emissions, impacting carbon footprint (CF), specifically during the heat drying process. Conventional heat drying processes need high energy and diminish the nutritional value and sensory quality of food. Therefore, this study aimed to investigate the integration of artificial intelligence (AI) in food processing to enhance quality and reduce CF, with a focus on heat drying, a high energy-consuming method, and offer a promising avenue for the industry to be consistent with sustainable development goals. Our finding shows that AI can maintain food quality, including nutritional and sensory properties of dried products. It determines the optimal drying temperature for improving energy efficiency, yield, and life cycle cost. In addition, dataset training is one of the key challenges in AI applications for food drying. AI needs a vast and high-quality dataset that directly impacts the performance and capabilities of AI models to optimize and automate food drying.

Near infrared spectroscopy (NIRS) is an analytical technique that offers a real advantage over laboratory analysis in the food industry due to its low operating costs, rapid analysis, and non-destructive sampling technique. Numerous studies have shown the relevance of NIR spectra analysis for assessing certain food properties with the right calibration. This makes it useful in quality control and in the continuous monitoring of food processing. However, the NIR calibration process is difficult and time-consuming. Analysis methods and techniques vary according to the configuration of the NIR instrument, the sample to be analyzed and the attribute that is to be predicted. This makes calibration a challenge for many manufacturers. This paper aims to provide a data-driven methodology for developing a decision support tool based on the smart selection of NIRS wavelength to assess various food properties. The decision support tool based on the methodology has been evaluated on samples of cocoa beans, grains of wheat and mangoes. Promising results were obtained for each of the selected models for the moisture and fat content of cocoa beans (R2cv: 0.90, R2test: 0.93, RMSEP: 0.354%; R2cv: 0.73, R2test: 0.79, RMSEP: 0.913%), acidity and vitamin C content of mangoes (R2cv: 0.93, R2test: 0.97, RMSEP: 17.40%; R2cv: 0.66, R2test: 0.46, RMSEP: 0.848%), and protein content of wheat-DS2 (R2cv: 0.90, R2test:0.92, RMSEP: 0.490%) respectively. Moreover, the proposed approach allows results to be obtained that are better than benchmarks for the moisture and protein content of wheat-DS1 (R2cv: 0.90, R2test: 94, RMSEP: 0.337%; R2cv: 0.99, R2test: 0.99, RMSEP: 0.177%), respectively. PRACTICAL APPLICATION: This research introduces a practical tool aimed at determining the quality of food by identifying specific light wavelengths. However, it is important to acknowledge potential challenges, such as overfitting. Before implementation, it is crucial for further research to address and mitigate the issues to ensure the reliability and accuracy of the solution. If successfully applied, this tool could significantly enhance the accuracy of near-infrared spectroscopy in assessing food quality attributes. This advancement would provide invaluable support for decision-making in industries involved in food production, ultimately leading to better overall product quality for consumers.

Incorporating insect meals into poultry diets has emerged as a sustainable alternative to conventional feed sources, offering nutritional, welfare benefits, and environmental advantages. This study aims to monitor and compare volatile compounds emitted from raw poultry carcasses and subsequently from cooked chicken pieces from animals fed with different diets, including the utilization of insect-based feed ingredients. Alongside the use of traditional analytical techniques, like solid-phase microextraction combined with gas chromatography-mass spectrometry (SPME-GC-MS), to explore the changes in VOC emissions, we investigate the potential of S3+ technology. This small device, which uses an array of six metal oxide semiconductor gas sensors (MOXs), can differentiate poultry products based on their volatile profiles. By testing MOX sensors in this context, we can develop a portable, cheap, rapid, non-invasive, and non-destructive method for assessing food quality and safety. Indeed, understanding changes in volatile compounds is crucial to assessing control measures in poultry production along the entire supply chain, from the field to the fork. Linear discriminant analysis (LDA) was applied using MOX sensor readings as predictor variables and different gas classes as target variables, successfully discriminating the various samples based on their total volatile profiles. By optimizing feed composition and monitoring volatile compounds, poultry producers can enhance both the sustainability and safety of poultry production systems, contributing to a more efficient and environmentally friendly poultry industry.

The need to increase food safety and improve human health has led to a worldwide increase in interest in gamma-aminobutyric acid (GABA), produced by lactic acid bacteria (LABs). GABA, produced from glutamic acid in a reaction catalyzed by glutamate decarboxylase (GAD), is a four-carbon, non-protein amino acid that is increasingly used in the food industry to improve the safety/quality of foods. In addition to the possible positive effects of GABA, called a postbiotic, on neuroprotection, improving sleep quality, alleviating depression and relieving pain, the various health benefits of GABA-enriched foods such as antidiabetic, antihypertension, and anti-inflammatory effects are also being investigated. For all these reasons, it is not surprising that efforts to identify LAB strains with a high GABA productivity and to increase GABA production from LABs through genetic engineering to increase GABA yield are accelerating. However, GABA\'s contributions to food safety/quality and human health have not yet been fully discussed in the literature. Therefore, this current review highlights the synthesis and food applications of GABA produced from LABs, discusses its health benefits such as, for example, alleviating drug withdrawal syndromes and regulating obesity and overeating. Still, other potential food and drug interactions (among others) remain unanswered questions to be elucidated in the future. Hence, this review paves the way toward further studies.

The quality of preparations offered in the workplace can vary according to the different segments of food services and may impact the health of the workers. This study aimed to qualitatively assess the food preparation offered to workers in from different food services. A total of 384 preparations were offered to workers in Curitiba City, Brazil. The preparations from three different segments of food services were evaluated: commercial (pilot study), non-commercial, and outsourced, selected for convenience. To identify the preparations, the nutritionist was interviewed, and the production process was monitored. The Score for Qualitative Assessment of Preparations (EAQP) was applied to evaluate the preparations, and they were classified according to their quality: high, intermediate, low, and very low quality. The chi-square and Kruskal-Wallis tests with post-hoc Least Significant Difference (LSD) Test were used. Most of the preparations were of high quality (72.9%), using mainly the unprocessed or minimally processed ingredients. The preparations offered by the non-commercial food service provider had a better mean quality score when compared to other food services (p < 0.01). This study outcome is essential to help food service professionals to decide and choose the ingredients used in the preparations.

Low-salt pickled vegetables are in line with a healthier diet, yet ensuring consistent quality of such products is challenging. In this study, low-salt tuber mustard pickles fermented with Lactiplantibacillus plantarum LPP95 in the presence of chitosan and inulin were analyzed over a 30-day period, and quality changes were evaluated. Total acid productions along with high bacterial counts (106 CFU/mL) were observed in the initial 20 days during indoor storage temperature, in which the reduced fiber aperture was found significantly lead to an increase in crispness (16.94 ± 1.87 N) and the maintenance of a low nitrate content (1.23 ± 0.01 mg/kg). Moreover, the combined pickling treatment resulted in higher malic acid content, lower tartaric acid content, and a decrease in the content of bitter amino acids (e.g., isoleucine and leucine), thus leading to an increase in the proportion of sweet amino acids. Additionally, combined pickling led to the production of unique volatile flavor compounds, especially the distinct spicy flavor compounds isothiocyanates. Moreover, the combined pickling treatment resulted in an increase in the abundance of Lactiplantibacillus and promoted microbial diversity within the fermentation system. Thus, the synergistic effect among chitosan, inulin, and L. plantarum LPP95 significantly enhanced the quality of pickles. The study offers a promising strategy to standardize the quality of low-salt fermented vegetables.

Black dot and silver scurf caused by Colletotrichum coccodes and Helminthosporium solani, respectively, are tuber blemish diseases affecting quality in the fresh and pre-pack potato industry. In the last 20 years, the importance of high-quality tuber appearance has increased considerably due to the growing demand for washed and pre-packed potatoes in the UK. Changing climate characterised by rising temperatures and wetter summers is a threat as this will favour the development of pathogens such as C. coccodes in the soil increasing the risk of food spoilage. Moreover, both diseases can develop not only in the field but also after harvest, with postharvest storage temperatures being a crucial factor in controlling fungal growth. Furthermore, anecdotal evidence showed differences on the aggressiveness of black dot depending on its origin (i.e. England and Scotland) on potato tubers. Silver scurf and black dot are difficult to differentiate as they present similar phenotypes characterised by silvery lesions making it challenging for managers to take the necessary corrective action during storage. Hence, the aim of this study was to give a general insight into the ecological conditions affecting the establishment of the causal agent of potato black dot in the field, and black dot and silver scurf during the supply chain. Therefore, invitro experiments were designed to study the growth rate and lag times simulating both scenarios respectively: on soil extract agar (SEA) media at different temperatures (4, 11, 15 °C) and matric potentials (control [unmodified] and - 1.4 MPa [modified]); and on natural potato dextrose agar (NPDA) for different temperatures (4, 11, 15 and 20 °C) at 99 % relative humidity (RH) for 25 days. When simulating the field environment, drier conditions (matric potential = -1.4 MPa) reduced fungal growth for both isolates by 0.1 cm day-1 at the temperature of 15 °C, suggesting temperature as the main limiting factor for the growth of C. coccodes in the soil. The causal agent of black dot exhibited a faster growth rate under retailer-like conditions (i.e., 15 °C) compared to H. solani. Understanding the environmental influence on both the pathogen and the crop is vital for proper disease management to help reduce food loss and waste.