Search Results (165)

Ready-to-eat meat products face quality challenges during storage and reheating. This study aimed to (i) characterize the physicochemical/microbiological changes in stewed mutton during storage (4 °C/−18 °C, 0–28 days) and (ii) evaluate reheating methods (boiling vs. microwaving) on day-7 samples. The nutritional analysis confirmed moisture reduction (57.32 vs. 72.12 g/100 g)-concentrated protein/fat levels. Storage at −18 °C suppressed microbial growth (the total plate count (TPC), 3.73 vs. 4.80 log CFU/g at 28 days; p < 0.05) and lipid oxidation (thiobarbituric acid reactive substances (TBARS): 0.14 vs. 0.19 mg/kg) more effectively than storage at 4 °C. The total volatile basic nitrogen (TVB-N) kinetics projected a shelf life ≥90 days (4 °C) and ≥120 days (−18 °C). Microwave reheating after frozen storage (−18 °C) maximized the yield (86.21% vs. 75.90% boiling; p < 0.05) and preserved volatile profiles closest to those in the fresh samples (gas chromatography–mass spectrometry (GC-MS)/electronic nose). The combination of freezing storage and subsequent microwave reheating has been demonstrated to be an effective method for preserving the quality of a precooked lamb dish, thereby ensuring its nutritional value. Full article

The art of food–drink pairing has always fascinated gourmets and cooking enthusiasts. While wine has long held pride of place on the table, natural mineral water plays a central role in this new concept. Through the Pyramid of Natural Mineral Waters, we aim to explore the relationships between the structure of water and food, flavors and aromas, revealing a world of previously unexplored nuances and tastes. This new approach is based on the analysis of the fixed residue of water, i.e., the amount of mineral salts dissolved in it. The fixed residue gives the water unique organoleptic characteristics, influencing the perception of flavors and sensations in the mouth. By analyzing the technical data sheet of mineral waters designed by us, it is possible to identify their main characteristics and combine them in a consistent way with various dishes, as proposed in the pyramid scheme. There are many possible combinations between natural mineral waters and foods, depending on numerous factors, including the type of water and the salts dissolved in it, the type of food, the cooking method, and the types of sauces and condiments present in the dish. To guide consumers in this fascinating universe, the figure of the water sommelier, or so-called hydro-sommelier, was born. As expert connoisseurs of natural mineral waters, they are able to recommend the ideal water for every occasion, maximizing the taste characteristics of the food served at the table. This study is completed with the construction of the Pyramid of Natural Mineral Waters, which relates the composition of water, specifically the salient characteristics related to dissolved minerals, with the respective food combinations recommended by us, in relation to the structure of both water and food. Full article

The growing imperative to mitigate climate change and accelerate the shift toward energy sustainability has called for a critical evaluation of heat and electricity generation methods. This article presents a comparative life cycle assessment (LCA) of solar and biogas energy systems on a common basis of 1 kWh of useful energy using SimaPro, the ReCiPe 2016 methodology (both midpoint and endpoint indicators), and cumulative energy demand (CED) analysis. This study is the first to evaluate co-located solar PV, solar thermal compound parabolic concentrator (CPC) and biogas combined heat and power (CHP) systems with in situ data collected under identical climatic and operational conditions. The project costs yield levelized costs of electricity (LCOE) of INR 2.4/kWh for PV, 3.3/kWh for the solar thermal dish and 4.1/kWh for biogas. However, the collaborated findings indicate that neither solar-based systems nor biogas technology uniformly outperform the others; rather, their effectiveness hinges on contextual factors, including resource availability and local policy incentives. These insights will prove critical for policymakers, industry stakeholders, and local communities seeking to develop effective, context-sensitive strategies for sustainable energy deployment, emissions reduction, and robust resource management. Full article

Food quality and safety are paramount in preserving the culinary authenticity and cultural integrity of Chinese cuisine, characterized by intricate ingredient combinations, diverse cooking techniques (e.g., stir-frying, steaming, and braising), and region-specific flavor profiles. Traditional non-destructive detection methods often struggle with the unique challenges posed by Chinese dishes, including complex textural variations in staple foods (e.g., noodles, dumplings), layered seasoning compositions (e.g., soy sauce, Sichuan peppercorns), and oil-rich cooking media. This study pioneers a hyperspectral imaging framework enhanced with domain-specific deep learning algorithms (spatial–spectral convolutional networks with attention mechanisms) to address these challenges. Our approach effectively deciphers the subtle spectral fingerprints of Chinese-specific ingredients (e.g., fermented black beans, lotus root) and quantifies critical quality indicators, achieving an average classification accuracy of 97.8% across 15 major Chinese dish categories. Specifically, the model demonstrates high precision in quantifying chili oil content in Mapo Tofu with a Mean Absolute Error (MAE) of 0.43% w/w and assessing freshness gradients in Cantonese dim sum (Shrimp Har Gow) with a classification accuracy of 95.2% for three distinct freshness levels. This approach leverages the detailed spectral information provided by hyperspectral imaging to automate the classification and detection of Chinese dishes, significantly improving both the accuracy of image-based food classification by >15 percentage points compared to traditional RGB methods and enhancing food quality safety assessment. Full article

This study aimed to improve the visual appeal of texture-modified (TM) dishes for individuals with dysphagia by developing a method to unify the texture of solid and liquid components through innovative food processing techniques. It investigated various meat-softening methods while preserving its solid appearance and ensuring a uniform texture when combined with a thickened soup. A grinding and reconstitution approach enabled the incorporation of pea protein (0% and 1%), olive oil (0%, 5%, or 10%), and papain (0% and 0.2%) to enhance the nutritional and sensory properties. This method successfully matched the firmness of TM meat with that of the thickened soup. Papain significantly reduced the firmness, and olive oil decreased the cohesiveness. After categorizing the TM meat and thickened soup as IDDSI level 4, four dishes at three firmness levels were developed. This study highlighted the potential of this approach to integrate solid and liquid food matrices, contributing to the advancement of TM food engineering and to the challenge of improving visual sensory acceptance and personalizing TM diets for individuals with dysphagia. Full article

The global market size of animal parasiticides was valued at USD 12.9 billion in 2024. Animal deworming only results in temporary cures with little to no preventive effects; therefore, a strategy that combines animal deworming with prevention is essential in improving the control of helminths. The effectiveness of co-administrating curative and preventive agents and their compatibility were considered based on the parasitophagous fungus Mucor circinelloides, which was developed in edible agar–agar (red seaweed)-carrying dewormers. Accordingly, Petri dishes were prepared with either a biopolymer alone (control, G-C) or with the anthelmintic piperazine (550, 1102, 2210, and 5500 mg/plate) or levamisole (37.5, 75, 150, and 300 mg/plate) and were used to culture the fungus Mucor circinelloides. Strong fungal growth and high numbers of spores were observed in the presence of the anthelmintics. No differences were measured between the control plates and those containing parasiticide drugs. Similar mycelial growth patterns and sporogenesis rates were recorded for different amounts of each anthelmintic. In conclusion, this novel formulation based on biopolymers containing anthelmintics and enriched with the parasitophagous fungus represents a highly promising tool to consider for jointly deworming animals and minimizing the risks of helminth infection. Further studies are in progress to confirm these in vitro results. Full article

Background/Objectives: Deep learning (DL) has shown strong potential in analyzing food images, but few studies have directly predicted mass, energy, and macronutrient content from images. In addition to the importance of high-quality data, differences in country-specific food composition databases (FCDBs) can hinder model generalization. Methods: We assessed the performance of several standard DL models using four ground truth datasets derived from Nutrition5k—the largest image–nutrition dataset with ~5000 complex US cafeteria dishes. In light of developing an Italian dietary assessment tool, these datasets varied by FCDB alignment (Italian vs. US) and data curation (ingredient–mass correction and frame filtering on the test set). We evaluated combinations of four feature extractors [ResNet-50 (R50), ResNet-101 (R101), InceptionV3 (IncV3), and Vision Transformer-B-16 (ViT-B-16)] with two regression networks (2+1 and 2+2), using IncV3_2+2 as the benchmark. Descriptive statistics (percentages of agreement, unweighted Cohen’s kappa, and Bland–Altman plots) and standard regression metrics were used to compare predicted and ground truth nutritional composition. Dishes mispredicted by ≥7 algorithms were analyzed separately. Results: R50, R101, and ViT-B-16 consistently outperformed the benchmark across all datasets. Specifically, when replacing it with these top algorithms, reductions in median Mean Absolute Percentage Errors were 6.2% for mass, 6.4% for energy, 12.3% for fat, and 33.1% and 40.2% for protein and carbohydrates. Ingredient–mass correction substantially improved prediction metrics (6–42% when considering the top algorithms), while frame filtering had a more limited effect (<3%). Performance was consistently poor across most models for complex salads, chicken-based or eggs-based dishes, and Western-inspired breakfasts. Conclusions: The R101 and ViT-B-16 architectures will be prioritized in future analyses, where ingredient–mass correction and automated frame filtering methods will be considered. Full article

During processing and storage, vegetables often experience undesirable color changes, including fading, lightening, or yellowing and softening, due to browning (enzymatic and non-enzymatic) and chlorophyll degradation. These changes diminish commercial and nutritional value. Therefore, it is necessary to maintain vegetable color and improve the quality of vegetable-based dishes. To address these issues, it is a scientific and practical necessity to summarize and discuss existing strategies and innovative techniques. This review first highlights the mechanisms of vegetable browning. This review then provides a comprehensive overview of recent advances in methods for color preservation, focusing on underlying mechanisms and techniques for inhibiting color changes from physical, chemical, and biological perspectives. A review of innovative technologies suggests that effective color preservation in vegetables is achieved by inhibiting the conditions that lead to three unfavorable color change reactions: enzymatic browning, non-enzymatic browning, and chlorophyll degradation. Current research frequently employs combined approaches that integrate two or more techniques to mitigate these adverse color changes. Moreover, most of these methods could simultaneously inhibit the three reaction processes. Future research directions are proposed for in-depth investigations into the molecular mechanisms of color changes in vegetables and the impact of treatments on the nutritional value. Full article

Pig large intestines (PLIs) are usually processed into various dishes for consumption through cooking methods such as stir frying, stewing, and braising, which are difficult for many consumers to accept because of their unique and pungent off-odours. To reduce the number of off-odour substances present in PLIs, we compared the effects of an untreated control group (blank), added flour (WF), and added S. cerevisiae mixed 4% flour in PLIs for fermentation (SC) on the treatment of PLIs. We analysed colour, thiobarbituric acid reactive substance (TBARS) values, and total volatile basic nitrogen (TVB-N) values; additionally, sensory evaluations were performed. The results showed that after 5 h of fermentation, the S. cerevisiae mixed flour exhibited the most significant effect on reducing the off-odour of PLIs, exhibited the least effect on the TBARS value and TVB-N was controlled within a reasonable range, while simultaneously maintaining good quality. A total of 415 volatile compounds were identified via flavouromics. Combined with principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), the key off-odour substances, including indole (faecal odour), 2-pentylthiophene (fat odour), (E)-2-octenal (fishy odour), and 2-methoxy-phenol (smoky odour), were reduced by 28.1%, 23.90%, 21%, and 22.89%, respectively, after fermentation. Moreover, the content of ethyl octanoate increased 31.04-fold, which enriched the flavour components of the PLIs. The results showed that fermentation of S. cerevisiae mixed flour could be used as a method to reduce the off-odours of PLIs. Full article

This study addresses the challenge of rapidly and accurately distinguishing zones of microbial activity from antibiotic inhibition zones in Petri dishes. We propose a laser speckle imaging technique enhanced with subpixel correlation analysis to monitor dynamic changes in the inhibition zone surrounding an antibiotic disc. This method provides faster results compared to the standard disk diffusion assay recommended by EUCAST. To enable automated analysis, we used machine learning algorithms for classifying areas of bacterial or fungal activity versus inhibited growth. Classification is performed over short time windows (e.g., 1 h), supporting near-real-time assessment. To further improve accuracy, we introduce a correction method based on the known spatial dynamics of inhibition zone formation. The novelty of the study lies in combining a speckle imaging subpixel correlation algorithm with ML classification and with pre- and post-processing. This approach enables early automated assessment of antimicrobial effects with potential applications in rapid drug susceptibility testing and microbiological research. Full article

Oats are an important grain-feeding crop with strong saline–alkali tolerance; however, the genetic mechanism of this tolerance is not clear, which hinders the development of oat varieties adapted to saline soils. In this study, the saline–alkali tolerance of 524 oat germplasm resources was comprehensively evaluated using culture-dish germination and field identification methods. During the germination period, saline–alkali stress significantly inhibited the germination potential, germination rate, and shoot and root lengths of oat germplasm. The indicators decreased by 71.15%, 49.32%, 59.03%, and 63.90%, respectively. The relative value of each trait was used as the evaluation metric. The 524 oat germplasm resources were classified into five groups by cluster analysis, and 174 oat germplasm resources with saline-alkali tolerance at the germination stage were screened. A regression equation for the identification of germinated saline-alkali-tolerant oat germplasm resources under the same conditions was also established. The field experiment showed that the coefficients of variation of oat germplasm resources were 4.03–54.12% and 6.97–38.50% in the two locations, which was rich in genetic variation; the correlation analysis showed that the biological yield was positively correlated with the D-value, and 18 high–quality and high-yielding saline–alkali-tolerant oat germplasm resources were identified by combining the saline–alkali-tolerant and weak germplasm resources of the two locations. Based on the multidimensional evaluation of germination and field performance, the 18 saline–alkali–tolerant germplasms screened in this study provide high–quality germplasm resources and a theoretical basis for saline oat cultivation and saline-tolerant breeding. Full article

This study evaluated the repellent activity of DEET, eugenol, methyl eugenol, 1,8-cineole, and their combinations against Amblyomma sculptum nymphs through laboratory and field tests. Initially, the botanical compounds were tested individually in Petri dish assays to assess repellent activity over various intervals (1 min to 168 h) at concentrations of 2%. Eugenol and methyl eugenol exhibited the highest average repellent percentages (60 to 90%), with significant effects (p < 0.05) across most evaluation periods, in contrast to 1,8-cineole. Therefore, eugenol and methyl eugenol were selected for combination testing with DEET. The combinations of 7% DEET + 1% eugenol and 7% DEET + 2% methyl eugenol showed the best results, with average repellent efficacy exceeding 85%. The first combination was selected for field evaluation. In this test, volunteers wore treated socks and walked for two hours in a naturally infested area. A significant reduction (p < 0.05) in the number of ticks recovered from the socks was observed in the 7% DEET and 7% DEET + 1% eugenol treatments, with efficacies of 82.5% and 88.5%, respectively, after 120 min. Isolated eugenol showed limited field efficacy, with significant repellent activity (p < 0.05) lasting only 20 min. The results highlight the potential of eugenol and methyl eugenol as repellent compounds, especially when combined with DEET. The field study confirmed the efficacy of the 7% DEET + 1% eugenol. Full article

This study examines the relationship between the 1141 most consumed foods in Brazil and their individual and combined health and environmental impacts. Foods are analyzed across different food system clusters, based on the health burden (DALYs) in minutes of healthy life using the Health Nutritional Index (HENI), greenhouse gas emissions, and water use. The most consumed foods were in natura products, such as rice, beans and meat, and a few ultra-processed products such as biscuits and soft drinks. Our results revealed an average HENI of −5.89 min, with values varying from −39.69 min of healthy life (stuffed cookies) to 17.22 min (freshwater fish). Animal-derived products, particularly red meat, had the highest environmental costs, contributing significantly to greenhouse gas emissions and water use. In contrast, plant-based foods like beans and fruits had better HENI scores and lower environmental impacts. We also found that greenhouse gas emissions reached up to 21.3 kg CO_2eq (beef dish), and water use peaked at 306.1 L (mozzarella pizza). Our findings provide valuable insights into the real-world consequences of individual and institutional food choices, demonstrating their measurable impacts on health and the environment. By moving beyond theoretical assumptions, this evidence strengthens the case for integrating sustainability into public food policies, including dietary guidelines that consider regional specificities and environmental concerns alongside nutritional recommendations. Full article

The rising prevalence of antibiotic resistance underscores the need for localized drug delivery systems that minimize systemic exposure. Autologous platelet concentrates (APCs), including concentrated platelet-rich fibrin (c-PRF) and liquid-phase concentrated growth factors (LPCGFs), have emerged as potential carriers for antimicrobial agents. This study aimed to evaluate the efficacy of c-PRF and LPCGF as carriers for three antibiotic formulations—amoxicillin with clavulanic acid, clindamycin, and a combination of amoxicillin with metronidazole—against methicillin-sensitive Staphylococcus aureus (MSSA), methicillin-resistant Staphylococcus aureus (MRSA), and Enterococcus faecalis (low-level natural resistance). The disk diffusion method was employed to incorporate antibiotics into both APC types, which were then applied to disks placed on bacterial cultures. The size of the inhibition zones was measured at 20-, 40-, 60-, and 80-h intervals. Every 20 h, the disks were transferred to a new Petri dish. Statistical analysis included Welch’s t-test and two-way ANOVA. c-PRF demonstrated superior performance as a carrier for amoxicillin and clindamycin, showing the presence of inhibition zones for up to 60 h. In contrast, LPCGF exhibited greater efficacy when used with the amoxicillin–metronidazole combination, particularly at higher concentrations. Both APCs showed limited effectiveness against E. faecalis when combined with clindamycin. The study confirms the suitability of autologous platelet concentrates as localized antibiotic delivery systems. The choice between c-PRF and LPCGF should be guided by the drug’s physicochemical properties and clinical application. APCs offer a promising alternative for targeted antimicrobial therapy in dental and surgical settings. Full article

The extraction of adherent cells, such as B16 murine melanoma cells, from Petri dish cultures is critical in biomedical applications, including cell reprogramming, transplantation, and regenerative medicine. Traditional detachment methods—enzymatic, mechanical, or chemical—often compromise cell viability by altering membrane integrity and disrupting adhesion proteins. To address these challenges, this study investigated sensor-based detection of the pre-detachment phase in a MPWM (Microfluidic Pulse Width Modulation) extraction system. Our approach integrates a micromechatronic system with a microfluidic suction circuit, real-time CCD imaging, and computational analysis to detect and characterize the pre-detachment moment before full extraction. A precisely controlled hydrodynamic force field progressively disrupts adhesion in multiple stages, reducing mechanical stress and preserving cell integrity. Real-time video analysis enables continuous monitoring of positional dynamics and oscillatory responses. Image processing and deep learning algorithms determine object center coordinates, allowing the MPWM system to dynamically adjust suction parameters. This optimizes detachment while minimizing liquid absorption and reflux volume, ensuring efficient extraction. By combining microfluidics, sensor detection, and AI-driven image processing, this study established a non-invasive method for optimizing adherent cell detachment. These findings have significant implications for single-cell research, regenerative medicine, and high-throughput biotechnology, ensuring maximal viability and minimal perturbation. Full article