Search Results (270)

This study investigates the thermal dynamics and material behavior involved in the baking process for Lebanese flatbread, focusing on the heat transfer mechanisms, water loss, and dough expansion under high-temperature conditions. Despite previous studies on flatbread baking using impingement or conventional ovens, this work presents the first experimental investigation of the traditional Lebanese flatbread baking process under realistic industrial conditions, specifically using a high-temperature tunnel oven with direct flame heating, extremely short baking times (~10–12 s), and peak temperatures reaching ~650 °C, which are essential to achieving the characteristic pocket formation and texture of Lebanese bread. This experimental study characterizes the baking kinetics of traditional Lebanese flatbread, recording mass loss pre- and post-baking, thermal profiles, and dough expansion through real-time temperature measurements and video recordings, providing insights into the dough’s thermal response and expansion behavior under high-temperature conditions. A custom-designed instrumented oven with a steel conveyor and a direct flame burner was employed. The dough, prepared following a traditional recipe, was analyzed during the baking process using K-type thermocouples and visual monitoring. Results revealed that Lebanese bread undergoes significant water loss due to high baking temperatures (~650 °C), leading to rapid crust formation and pocket development. Empirical equations modeling the relationship between baking time, temperature, and expansion were developed with high predictive accuracy. Additionally, an energy analysis revealed that the total energy required to bake Lebanese bread is approximately 667 kJ/kg, with an overall thermal efficiency of only 21%, dropping to 16% when preheating is included. According to previous CFD (Computational Fluid Dynamics) simulations, most heat loss in similar tunnel ovens occurs via the chimney (50%) and oven walls (29%). These findings contribute to understanding the broader thermophysical principles that can be applied to the development of more efficient baking processes for various types of bread. The empirical models developed in this study can be applied to automating and refining the industrial production of Lebanese flatbread, ensuring consistent product quality across different baking environments. Future studies will extend this work to alternative oven designs and dough formulations. Full article

This study aimed to assess the use of selected raw materials, such as whole-grain oat flakes, pumpkin seeds, sunflower seeds, and flaxseeds, to obtain bars using baking and drying methods. Modifying the bars’ composition involved selecting the fibre preparation, replacing water with NFC juice, and using fresh apple juice and apple pomace. The Psyllium fibre preparation, also in the form of a mixture with apple fibre, was the most useful in dough cohesion and the quality of the bars. Baked bars were characterised by higher sensory quality than those obtained by drying. Microwave–convection drying was a good alternative to baking, primarily due to the lower temperature resulting in a lower acrylamide content and comparable product quality. The basic grain ingredients and fibre preparations mainly shaped the nutritional and energy value and the sensory and microbiological quality. Modifying the recipe using NFC or fresh juice and apple pomace allowed the bars to develop new properties and quality characteristics. The use of NFC juices resulted in a reduction in the pH of the bars, which is associated with a higher microbiological quality of the bars. All bars had low acrylamide content, significantly lower than the permissible level. Using fresh pomace or fibre preparations made from by-products is a possibility to increase the fibre content in the bars and a method of managing by-products. Full article

Speaker profiling systems are often evaluated on a single corpus, which complicates reliable comparison. We present a fully reproducible evaluation pipeline that trains Convolutional Neural Networks (CNNs) and Long-Short Term Memory (LSTM) models independently on three speech corpora representing distinct recording conditions—studio-quality TIMIT, crowdsourced Mozilla Common Voice, and in-the-wild VoxCeleb1. All models share the same architecture, optimizer, and data preprocessing; no corpus-specific hyperparameter tuning is applied. We perform a detailed preprocessing and feature extraction procedure, evaluating multiple configurations and validating their applicability and effectiveness in improving the obtained results. A feature analysis shows that Mel spectrograms benefit CNNs, whereas Mel Frequency Cepstral Coefficients (MFCCs) suit LSTMs, and that the optimal Mel-bin count grows with corpus Signal Noise Rate (SNR). With this fixed recipe, EfficientNet achieves 99.82% gender accuracy on Common Voice (+1.25 pp over the previous best) and 98.86% on VoxCeleb1 (+0.57 pp). MobileNet attains 99.86% age-group accuracy on Common Voice (+2.86 pp) and a 5.35-year MAE for age estimation on TIMIT using a lightweight configuration. The consistent, near-state-of-the-art results across three acoustically diverse datasets substantiate the robustness and versatility of the proposed pipeline. Code and pre-trained weights are released to facilitate downstream research. Full article

The growing demand for functional and sustainable foods has driven food innovation, enhancing its nutritional value. This study aimed to develop a nutritious bread using local rye from the Trás-os-Montes region of Portugal and incorporating whey, a by-product of the dairy industry, as a replacement for water. Three bread formulations were tested: a traditional recipe with 37.5% rye flour and water (Control—CTR); the same recipe using whey instead of water (Rye Whey—RW); and a formulation with 100% local rye and whey replacing water (Full Rye Whey—FRW). Nutritional composition was assessed, including moisture, ash, protein, dietary fiber, sodium, potassium, lipids, and carbohydrates. Sensory analysis included both quantitative descriptive analysis and consumer acceptance testing. Microbiological quality was also evaluated. Whey-containing samples showed lower moisture and increased levels of ash, lipids, carbohydrates, and potassium. RW had the highest protein content (6.54 ± 0.28 g/100 g, p < 0.05), while FRW exhibited the highest dietary fiber (6.96 ± 0.15 g/100 g, p < 0.05). RW demonstrated a balanced nutritional and sensory profile, with high consumer acceptance. Overall, the combination of local rye and whey presents a promising strategy for producing nutritious bread while valorizing local agricultural resources and dairy by-products. These findings support sustainable food production practices and contribute to circular economy approaches. Full article

In the Alpine region of Austria, Italy, and Switzerland, transhumance is widespread and the production of local traditional dairy products during summer is important. Raw milk cheeses are produced according to traditional recipes, using hurdles as a technique to guarantee food safety. In the present study, we aim to provide an overview of S. aureus and its enterotoxins in raw milk cheeses, identify the key parameters responsible for the enterotoxin production, and identify ways to improve food safety. The results demonstrate that safe artisanal raw milk cheese production is achievable under elementary conditions by applying effective hurdles, including high scalding temperatures or thermization, quality starter cultures, and robust milk quality management. The hurdle index (HI), which we introduce in this paper, is a promising tool for assessing and improving safety in raw milk cheese production. Full article

The main objective of this study is to assess the environmental life cycle of the materials, components, and elements of a mono-Si photovoltaic power plant towards their sustainable development. Currently, photovoltaic installations are considered to be environmentally friendly systems that produce “green” energy. During their exploitation, no pollutants are emitted into the environment. However, the processes of manufacturing and post-used management of their materials, components and elements are associated with both high demand for energy and matter, as well as with emissions of harmful substances into the atmosphere, water, and soil. For this reason, from the perspective of the entire life cycle, photovoltaic power plants may contribute to the deterioration of human health, the reduction in the quality of the environment, and the depletion of non-renewable fossil resources. Due to these potential threats, it was considered appropriate to conduct a Life Cycle Assessment of a real 2 MW photovoltaic power plant located in northern Poland, in terms of compliance with the main assumptions of sustainable development. The analysis was conducted using the Life Cycle Assessment (LCA) methodology (the ReCiPe 2016 model). Impacts on the environment was assessed in three areas: human health, ecosystem quality, and material resources. Two scenarios were adopted for the post-used management of materials, components, and elements: landfill disposal and recycling. Based on the conducted research, it was found that, among the assessed groups of photovoltaic power plant components (photovoltaic modules, supporting structure, inverter station, and electrical infra-structure), photovoltaic modules have the highest level of harmful impact on the environment (especially the manufacturing stage). The use of recycling processes at the end of their use would reduce their harmful impact over the entire life cycle of a photovoltaic power plant and better fit with the main principles of sustainable development. Full article

Public transportation in cities is negatively affected by reliance on petroleum-based fuels, leading to emissions and poor air quality. Although the environmental evaluation of alternative buses in terms of sustainability has been extensively studied, the social dimensions have not received as much attention. In this regard, this research examines the social implications of alternative urban buses through life cycle impact assessment (LCIA) methods, including Eco-Indicator 99, Impact 2002+, and ReCiPe Endpoint. The results indicate that diesel buses significantly impact health, while hybrid, fuel cell, and electric buses can decrease emissions by 50%. These results underscore the necessity of zero-emission technologies to enhance urban air quality and promote better public health. Full article

Background/Objectives: The majority of Canadian children bring a home-packed lunch to school, and previous research suggests lunches are of poor nutritional quality. This pilot study aimed to test the feasibility, acceptability, and preliminary impact of an eHealth family-based intervention designed to improve the nutritional quality of home-packed lunches. Methods: In this 12-week intervention, families (n = 20 parents with children aged 4–8 years) received a toolkit which included a cookbook on tips for preparing healthy lunches and 15 tested lunch box-friendly recipes, a lunch box, text messages, and an online cooking class. Feasibility was assessed via documentation of intervention delivery and participant retention rates. Acceptability was assessed via post-intervention surveys and semi-structured interviews in a sub-sample of parents (n = 9). Preliminary impact was assessed using 3-day lunch food records. Descriptive statistics were used to assess feasibility and acceptability, and Wilcoxon signed-rank tests were used to evaluate changes in the nutritional content of packed lunches. Results: Findings indicated a high retention rate (85%), and the majority (94%) of participants reported that the intervention was helpful and that they would recommend it to another parent. Qualitative interviews suggest parents found the recipes practical and diverse, the lunch box and the cooking class helpful, and some reported increased confidence and greater awareness of the foods being packed. No changes in the nutritional content of packed lunches were observed (n = 10 children). Conclusions: In summary, a home-packed lunchbox intervention is feasible and well accepted by families, but further refinements are needed to optimize its impact before a full-scale trial. Full article

Background/Objectives: Adopting sustainable dietary patterns is essential for addressing environmental sustainability and improving public health outcomes. However, food service providers and consumers often face challenges in making informed choices due to a lack of information on the environmental, nutritional, and cost implications of different meal options. The aim of this paper was to provide an integrated assessment of the nutritional quality, environmental impact and cost of vegan, vegetarian, and meat-based versions of four popular meals (lasagne, chilli, teriyaki, and curry) offered in the lunch service of a university food service establishment in London, UK. Methods: In this study, real recipes from the food service provider were analysed. The nutritional quality of meals was evaluated using the Nutrient Rich Food Index (NRF 9.3 and 17.3), the environmental impact was assessed using life cycle assessment (LCA), and the cost was calculated using recipe costing. Results were normalised using the min–max method, and recipes were ranked relative to each other based on their final nutritional quality, environmental impact and cost scores using a normalised integrated scoring method to identify which recipe version of meals was the most optimal when considering environmental sustainability, nutrition, and cost simultaneously. Results: The integrated assessment revealed that vegan recipe versions of meals made with whole foods consistently outperformed their meat-based counterparts across all three criteria—environmental impact, nutritional quality, and cost—ranking highest in environmental sustainability and nutrition while also being more cost-effective, regardless of cuisine or dish type. Conclusions: These findings suggest that shifting towards plant-based recipes made with whole-foods (e.g., vegetables, legumes, etc.) can improve micronutrient intake, reduce environmental impact, and lower costs, thus supporting sustainable dietary transitions and public health. Full article

The effect of various natural antioxidants—grape seed extract (GSE), ascorbic acid (AA), α-tocopherol (TP), a combination of GSE and AA, and a combination of GSE and TP—on pH, water activity, color change, lipid oxidation, antioxidant capacity, total bacterial count, protein content and free fatty acids was studied in sausages during the drying process. The model sausage system was prepared according to a traditional Bulgarian recipe for “lukanka”. AA and KNO₃ were used in the recipe as antioxidants and preservatives, respectively. The results obtained with natural antioxidants were compared with the results of samples prepared according to the traditional recipe and with a synthetic antioxidant, butylated hydroxytoluene. The samples with a combination of GSE and AA showed the highest antilipid potential, the lowest malondialdehyde values (0.41 mg/kg MDA), the highest antimicrobial capacity (TBC 78.50 × 10³ cfu/g), the lowest color change, and the lowest change in antioxidant activity (17.74%), through the sausage drying process. There was an obviously synergistic effect between GSE and AA, and their antioxidant activity was highly effective. The sample with 0.05% GSE ranked second. The samples with a synthetic antioxidant and a combination of KNO₃ and AA gave similar results, but KNO₃ had a toxic effect. The samples with α-tocopherol had lower results. It was found that grape seed extracts and the combination of GSE and AA were the most effective and could successfully replace synthetic antioxidants, improve the quality of sausages, and provide healthier foods to consumers. Full article

Food computing refers to the integration of digital technologies, such as artificial intelligence (AI), the Internet of Things (IoT), and data-driven approaches, to address various challenges in the food sector. It encompasses a wide range of technologies that improve the efficiency, safety, and sustainability of food systems, from production to consumption. It represents a transformative approach to addressing challenges in the food sector by integrating AI, the IoT, and data-driven methodologies. Unlike traditional food systems, which primarily focus on production and safety, food computing leverages AI for intelligent decision making and the IoT for real-time monitoring, enabling significant advancements in areas such as supply chain optimization, food safety, and personalized nutrition. This review highlights AI applications, including computer vision for food recognition and quality assessment, Natural Language Processing for recipe analysis, and predictive modeling for dietary recommendations. Simultaneously, the IoT enhances transparency and efficiency through real-time monitoring, data collection, and device connectivity. The convergence of these technologies relies on diverse data sources, such as images, nutritional databases, and user-generated logs, which are critical to enabling traceability and tailored solutions. Despite its potential, food computing faces challenges, including data heterogeneity, privacy concerns, scalability issues, and regulatory constraints. To address these, this paper explores solutions like federated learning for secure on-device data processing and blockchain for transparent traceability. Emerging trends, such as edge AI for real-time analytics and sustainable practices powered by AI–IoT integration, are also discussed. This review offers actionable insights to advance the food sector through innovative and ethical technological frameworks. Full article

In recent years, the semiconductor industry has embraced advanced artificial intelligence (AI) techniques to facilitate intelligent manufacturing throughout their organizations, with particular emphasis on virtual metrology (VM) systems. Nonetheless, the practical application of data-driven virtual metrology for product quality inspection encounters notable hurdles, such as annotating inspections in highly dynamic industrial environments. This leads to complexities and significant expenses in data acquisition and VM model training. To address the challenges, we delved into transfer learning (TL). TL offers a valuable avenue for knowledge sharing and scaling AI models across various processes and factories. At the same time, research on transfer learning in VM systems remains limited. We propose a novel parameter transfer learning (PTL) architecture for VM systems and examine its application in industrial process automation. We implemented cross-factory and cross-recipe transfer learning to enhance VM performance and offer practical advice on adapting TL to meet individual needs and use cases. By leveraging extensive data from Seagate wafer factories, known for their large-scale and high-dimensional nature, we achieved significant PTL performance improvements across multiple performance metrics, with the true positive rate (TPR) increasing by 29% and false positive rate (FPR) decreasing by 43% in the cross-factory study. In contrast, in the cross-recipe study, TPR increased by 27.3% and FPR decreased by 6.5%. With our proposed PTL architecture and its performance achievements, insufficient data from the new manufacturing sites, new production lines and new products are addressed with shorter VM model training time and smaller computational power with strong final quality prediction confidence. Full article

Döner kebab, a meat product of Middle-Eastern origin, has gained significant popularity and is now widely consumed across Europe. The recipe varies depending on the area, with beef, turkey, lamb, or chicken being used as main ingredients. The aim of this work was to assess the hygienic-sanitary quality of raw and cooked döner kebabs stored at 4 ± 2 °C for 10 days and at 8 ± 2 °C for the next 20 days or frozen (−18 °C) for one month. One additional aim was to determine the potential growth of Listeria monocytogenes intentionally inoculated in cooked döner kebab during storage at 4 ± 2 °C or freezing. The concentration of Total Viable Count (TVC) and the Enterobacteriaceae of the 100 samples of raw döner kebab were less than 7 log CFU/g and 4 log CFU/g, respectively. Consequently, the samples can be considered acceptable and similar to traditional raw meat. The cooked döner kebab can be considered safe for a period of 30 days, especially from a microbiological point of view, when stored under refrigerated conditions, also taking into account possible thermal abuse. Coagulase Positive Cocci (CPC), Clostridium H₂S⁺, Salmonella spp., and Listeria monocytogenes were never found in any of the samples. After 30 days, the TVC was at the level of 6 log CFU/g and Enterobacteriaceae at less than 4 log CFU/g. The main concern was related to microbial or tissue activity, resulting in an increase in total volatile basic nitrogen (TVB-N) content. However, in the cooked samples, the TVB-N content remained below 40 mg N/100 g at the end of the shelf-life period (32.5 mg N/100 g), which is still considered an acceptable value. In addition, the level of Malondialdehyde (MDA) was found to be within acceptable limits, with a reading of 1.4 nmol/g attained after 30 days. The same product, when frozen and stored at −18 °C, can be considered stable for a minimum of 6 months, both from a microbiological and a physico-chemical point of view. No microbial growth was observed. The TVB-N and the MDA levels increased, but after 6 months, their levels were still acceptable, with values of 19.1 mg N/100 g and 1.2 nmol/g, respectively. These observations demonstrate low protein degradation and lipid oxidation during the shelf-life period. The challenge test showed that Listeria monocytogenes did not grow in döner kebab either when stored at 4 ± 2 °C for 10 days and 8 ± 2 °C for 20 days or when stored at −18 °C for 6 months. The concentration of L. monocytogenes was found to be 5.4 log CFU/g in the refrigerated products and 4.9 log CFU/g in the frozen products. At the end of the shelf-life period, the L. monocytogenes load in both products was lower than the initial concentration that had been added. Finally, the use of air-packaging has been proven to be beneficial to the preservation of the product and maintained its microbiological and physico-chemical properties intact. Despite these good results, future directions could be to investigate different plastic films and packaging such as Modified Atmosphere (MAP), Vacuum (VP), and Sous Vide packaging (SVP). Full article

Technological issues with the production of gluten-free rice crackers with spirulina powder were examined in this work through their rheological, textural, color, sensory, and nutritional aspects. A part of gluten-free whole-grain rice flour was replaced with 5, 10, and 15% spirulina powder in an appropriate recipe for crackers. The rheological analysis presented obtained dough samples as viscoelastic systems with dominant elastic components (G′ > G″ and Tan δ = G″/G′ is less than 0). The addition of spirulina contributed to a softer dough consistency according to a statistically significant (p < 0.5) decrease of Newtonian viscosity during the creep phase for a maximum of 43.37%, compared to the control dough. The 10 and 15% quantities of spirulina powder led to a statistically significant (p < 0.5) increase in the viscoelastic parameter J_max, which indicated a greater dough adaptability to stress. The textural determination of the dough pointed statistically significantly (p < 0.05) to decreased dough hardness and improved dough extensibility and confirmed all rheological measurements with high correlation coefficients, indicating good physical dough properties during processing. Spirulina certainly affected the change in the color of the dough from a yellow-white to intense green, which also had a significant impact on the sensory quality of the baked crackers. Many sensory properties of the crackers were improved by the addition of and increasing amounts of spirulina (appearance, brittleness, hardness, graininess, and stickiness). The results for the dough and for the final crackers pointed to very good technological aspects for the development of a gluten-free bakery product with high nutritional value, such as increased polyphenolic content (with the majority of catechins), protein, total dietary fibers, and mineral content compared to the control sample. Full article

An upward trend has been observed in recent years in which consumers are actively more conscious about finding healthier food alternatives to purchase. Based on the constantly increasing demands of the diabetes food market, a new product of canned peach halves was designed at the Laboratory of Technology & Food Quality & Food Safety of the University of Thessaly through the substitution of sugar with sweetening agents coming from the Stevia plant and Agave syrup. For the production process of the samples the ingredients were carefully selected. Then, the recipes were designed along with the determination of the all the parameters that should be taken into account according to the thermal processing of previous studies. After the completion of the production process, the samples were stored in a dark and cold environment for a 6-month period. Subsequently, the samples were analyzed before and after simulated digestion (INFOGEST protocol) to determine their nutritional characteristics and their microbiological safety. The samples were then given to consumers to test the organoleptic characteristics of the new products. The results of the microbiological, nutritional, organoleptic, and meal tests were analyzed in order to assess the quality of samples. The canned peaches with Stevia had higher bio-availability and liking scores, and resulted in lower post-prandial glucose levels. Full article