Search Results (1,385)

Reliable, high-quality rainfall data are vital for soil and water management, crop forecasting, and risk assessment. These applications are essential for food security, climate resilience, biodiversity monitoring, and rural livelihoods. Rainfall monitoring in Thailand is challenging due to the limited density of official stations and the inconsistent quality of data from multiple sources, compounded by calibration issues. This study introduces a comprehensive quality control (QC) approach tailored for the Thai context, presenting a systematic pipeline that clarifies the hierarchy and sequence of operations. The method uses rainfall data from 3075 stations of the Thai Meteorological Department (TMD) and the Thaiwater network. It includes basic QC for data completeness and advanced QC using a quality (Q) index to assess station reliability, diving the stations into five groups: poor (<50), moderate (50–80), acceptable (80–85), good (85–90), and excellent (>90). The results indicate that Thaiwater consistently achieved moderate to excellent Q index values, exceeding 70% annually, with values surpassing 90% in 2023. In contrast, the TMD maintained excellent quality, with values above 90% for all years. Out of over one million daily entries, 87% were verified as correct, though the Thaiwater data for 2024 showed only 70% accuracy. The QC procedures significantly improved data reliability, reducing the root mean square error for GSMaP and IMERG by 1.7% and 1.5%, respectively, and lowering the false alarm rate by approximately 0.001–0.002 without compromising heavy rainfall detection. A systematic QC framework is essential for ensuring high-quality datasets in rainfall applications. Full article

Cold-chain supply systems depend on a sequence of linked production and logistics decisions. In prepared-food cold chains, quality may deteriorate not because one visible failure occurs, but because testing, traceability records, temperature monitoring, and abnormal-condition reporting are gradually weakened under cost pressure. Once such hidden effort reduction accumulates, external disturbances may push the system from strict assurance to weakened governance. To explain this nonlinear process, an asymmetric evolutionary game is built between prepared-food producers and cold-chain logistics providers, each choosing between strict and weakened quality assurance. White Gaussian noise is introduced to represent random operating shocks, and the two-population strategy system is projected onto a system-level quality-governance coordinate, q. This projection is used as a transparent baseline coordinate rather than as an assumption of linear system evolution. The reduced system is then transformed into a stochastic cusp catastrophe model, with a resilience indicator used to measure the distance from critical transition conditions. Numerical simulations show that quality assurance costs and short-term cost-saving benefits move the system toward a weakened-governance basin, whereas external incentives, coordination degree, and credible accountability mechanisms support recovery toward strict collaboration. The framework offers a scenario-based resilience diagnosis approach for identifying threshold effects in cold-chain quality governance. Digital traceability, temperature-data sharing, incentive alignment, and accountability rules are further interpreted as operational innovations that improve resilience and reduce avoidable quality losses in sustainable cold-chain operations. Full article

This study evaluated the microbiological quality, phenolic compound profile, antimicrobial activity against foodborne pathogens, and the presence of potential chemical markers associated with microplastic polymers in 35 commercial bee pollen samples obtained from the seven geographical regions of Türkiye. Microbiological analyses included the enumeration of total mesophilic aerobic bacteria, coliforms, yeasts and molds, lactobacilli, lactococci, and psychrophilic bacteria. Antimicrobial activity was determined against Escherichia coli O157:H7, Staphylococcus aureus, and Salmonella Enteritidis using the disk diffusion method. Phenolic compounds were analyzed by HPLC-DAD, while characteristic pyrolysis products associated with microplastics were analyzed by PY-GC/MS. The results indicated that the pollen samples generally exhibited low microbial contamination levels and variable antimicrobial activity, depending on their geographical origin. Quercetin was identified as the predominant phenolic compound, and samples with higher phenolic content tended to show stronger antimicrobial effects, particularly against S. aureus. PY-GC/MS analyses revealed the presence of several chemical markers potentially associated with plastic polymers in a considerable proportion of the samples. Spearman correlation analysis showed a positive correlation between total phenolic content and particularly S. aureus inhibition. These findings highlight the nutritional and functional value of bee pollen while also drawing attention to emerging food safety concerns related to possible exposure to plastic-associated environmental contaminants. Regular monitoring of bee pollen is therefore recommended to ensure product quality and consumer safety. Full article

Industry 4.0 is speeding up the move to connected, data-driven, and automated production, where the Internet of Things (IoT) enables sensing, communication, and real-time support for decisions. At the same time, rapid growth in industrial IoT studies has led to scattered technologies, architectures, and results. This paper fills this gap through a systematic literature review on IoT for Industry 4.0. It also helps readers compare methods and choose suitable building blocks for real deployments today. We focus on key technologies, integration architectures, application areas, challenges, trends, and reported benefits. Using PRISMA 2020, we searched five major databases (Scopus, MDPI, IEEE Xplore, ScienceDirect, and Web of Science) for 2020–2025 and found 584 records. After removing duplicates and screening, we kept 96 peer-reviewed studies for detailed analysis. Results show that most studies use a layered stack that combines sensing/actuation, industrial networking, data collection pipelines, and analytics across edge, fog, and cloud resources. MQTT, OPC UA, CoAP, LPWAN, and 5G connectivity are often used for communication, while RAMI 4.0, IIRA, and similar layered models guide system design. Many architectures follow an edge–cloud pattern, with growing focus on digital twin/CPS links and security-by-design. Applications are mainly smart manufacturing, predictive maintenance, and logistics, with added work in energy management, Construction 4.0, and agri-food monitoring. The key barriers remain interoperability, data quality and evaluation gaps, cybersecurity risks, legacy integration, and deployment limits. The review points to future work on edge AI/TinyML, deterministic connectivity, scalable digital twins, trusted data sharing, and sustainable industrial IoT. Full article

The modern food industry faces increasing pressure to reduce environmental impacts, while at the same time preserving product safety, quality, nutritional value, and industrial relevance. This review synthesizes three related pillars of sustainable food processing: green extraction technologies, natural fermentation, and analytical quality validation. Green extraction methods can reduce dependence on conventional organic solvents, shorten processing time, and support the extraction of bioactive compounds from plant materials and by-products of the food industry. Natural fermentation is a low-impact biotechnological approach to improve sensory quality, shelf life, nutritional value, and valorization of low-cost raw materials or residues. However, sustainability cannot be judged only through lower consumption of resources or general “green” claims. It also requires analytical confirmation of the content of bioactive compounds, oxidative stability, contaminants, authenticity, traceability, standardization, and product safety. In response to reviewers’ recommendations, the review includes a transparent literature selection protocol, a clearer distinction of challenges, research gaps, and future perspectives, as well as additional quantitative comparative tables covering extraction technologies, fermentation applications, and analytical methods. The review shows that the future of sustainable food processing depends on integrating extraction, fermentation, by-product valorization, foodomics approaches, life cycle thinking, real-time monitoring, and industrial-scale validation within the circular economy. Full article

Black rice is abundant in polyphenolic antioxidants, but conventional thermal processing degrades these heat-sensitive compounds, limiting their bioactivity. Although single-strain fermentation can improve the extraction of bioactive components, it remains challenging to simultaneously balance the flavor and bioactivity of fermented black rice products. Low-temperature co-fermentation with yeast and lactobacillus has emerged as a promising strategy to enhance both the flavor profile and functional quality of fermented foods. Therefore, this study investigates the effects of low-temperature co-fermentation with Saccharomyces cerevisiae and Lactobacillus bulgaricus 134 on the quality of black rice slurry. The efficacy was systematically evaluated by monitoring fermentation kinetics, conducting polyphenol and anthocyanin metabolomics analysis, performing flavoromics analysis, and combining in vitro ABTS radical scavenging assays with a Caco-2 cell-based oxidative stress model. The results showed that this process activated β-glucosidase within the first 24 h of fermentation. By activating terpenoid and phenolic metabolic pathways, it maximized the accumulation of anthocyanins and short-chain esters during 30–36 h, which conferred the product with prominent fruity and sweet notes. Fermented black rice slurry (FBRS) exhibited potent ABTS radical scavenging activity. In the Caco-2 oxidative stress model, FBRS pretreatment restored cellular viability, upregulated the activity of endogenous antioxidant enzymes, and reduced MDA content. This study provides a theoretical foundation for developing high-nutritional, flavor-enhanced fermented black rice products. Full article

Monitoring chemical residue levels in foods of animal origin is essential to ensure food safety and protect consumer health. Sulfites are commonly used in crustaceans to preserve quality; however, excessive levels may raise public health concerns, particularly for sensitive individuals. This study aimed to assess the compliance of shrimp from offshore and coastal fisheries in Morocco with current regulatory standards. A total of 60 samples were collected and analyzed for residual sulfite levels using the semi-quantitative strip test method. The results showed that sulfite concentrations ranged from 5 to 100 mg/kg in offshore samples, with a mean value of 41 mg/kg. Higher concentrations were observed in coastal samples, with an average of 172 mg/kg. Despite the observed differences between fishing origins, most samples complied with the established regulatory limits. These results support the importance of systematic monitoring programs within the fisheries supply chain to strengthen food safety control and contribute to veterinary public health protection. Full article

Edible insects have emerged as a promising alternative to conventional livestock as the global demand for sustainable protein sources rises. Ensuring the safety of insect-based foods is crucial for consumer acceptance and regulatory approval. This review provides a comprehensive overview of the primary chemical and microbiological contaminants associated with edible insects, including heavy metals, pesticides, veterinary drugs, persistent organic pollutants (POPs), mycotoxins, microbiological hazards, and allergenic risks. Current evidence indicates that, when insects are farmed and processed under controlled conditions and in compliance with existing European Union regulations, contaminant levels are generally low and within the range of those found in traditional animal-derived foods. Most studies report that current risks are primarily linked to substrate quality and storage practices. Allergenic risks, particularly cross-reactivity with crustacean and mite allergens, remain a crucial consideration for individuals with sensitivities. Despite these reassuring findings, knowledge gaps persist regarding insect-specific contaminant limits, the metabolic fate of toxins, and the long-term safety of consuming novel insect-derived products. Continued research, targeted monitoring, and regulatory adaptation will be essential to ensure the safe and sustainable integration of insect-based foods into the human diet. Full article

Shrimp are among the most valuable seafood commodities worldwide, but are also highly perishable, making their quality preservation a critical issue for both food safety and supply chain sustainability. The rapid deterioration of fresh shrimp contributes to significant post-harvest losses, highlighting the need for reliable freshness indicators capable of supporting shelf-life assessment under commercial conditions. This study evaluated the evolution of microbiological, physicochemical, and sensory parameters in two commercially important Mediterranean shrimp species, Parapenaeus longirostris and Melicertus kerathurus, stored on ice for up to 15 days under retail-like conditions. Microbial load, pH, total volatile basic nitrogen (TVB-N), thiobarbituric acid reactive substances (TBARS), formaldehyde, formic acid, and sensory attributes were monitored during storage. Microbial populations increased progressively over time but remained below commonly accepted spoilage thresholds, while physicochemical indicators showed significant changes associated with post-mortem biochemical processes. In particular, TVB-N, pH, and formic acid increased during storage, whereas formaldehyde levels decreased, suggesting the progressive transformation of trimethylamine-N-oxide degradation products. Sensory analysis indicated that shrimp maintained high quality up to approximately 12 days of iced storage, whereas samples stored for 15 days approached the limit of consumer acceptability. The combined behaviour of microbial, chemical, and sensory indicators highlights the importance of a multidimensional approach for evaluating shrimp freshness under commercial storage conditions. Based on the experimental dataset, practical reference ranges for key quality parameters are proposed (pH < 7.4; TVB-N ≤ 30 mg N/100 g; formaldehyde < 10 mg/kg; formic acid < 18 mg/kg). These results may support improved freshness evaluation, contribute to more accurate shelf-life estimation, and help reduce unnecessary seafood waste within the supply chain. Full article

Traditional petroleum-based packaging suffers from pollution and functional limits, making it unsuitable for next-generation food systems. In contrast, bio-based smart packaging—combining renewable substrates with responsive components—transforms packaging from a passive shell into an active quality monitor and supply chain information node through three interconnected pillars: renewability, real-time responsiveness to freshness markers, and digital traceability. Market figures confirm this shift, with the smart food packaging sector projected to reach USD 48.97 billion by 2028 (CAGR 4.49% from 2023). This review covers recent progress in natural polymers (cellulose, chitosan, alginate, gelatin) and bio-based polyesters (PLA, PHA). Their multiscale structures enable tunable mechanical and barrier properties while serving as hosts for intelligent functions. Two functional directions stand out: active preservation (antimicrobial, antioxidant, gas-regulating, stimulus-controlled release) and intelligent sensing (colorimetric indicators, bio-based sensors, nano-amplified signals for real-time freshness monitoring). Beyond material functions, digital tools such as IoT and blockchain turn packaging into interactive data nodes, linking material intelligence with full traceability to enhance food safety and supply chain efficiency. Key challenges remain with long-term operational stability, production costs, scalable manufacturing, and life cycle assessments. Nevertheless, bio-based smart packaging is expected to evolve through biomimetic design, process innovation, and system-level integration toward adaptability, multifunctionality, and intelligence, ultimately supporting safer, more transparent, efficient, and sustainable food systems. Full article

Proteins with additives, especially in small quantities, are of great interest as a subject of study. Machine learning approaches implemented on Raman spectroscopy data could provide an insight into the chemical structures of such mixtures or conjugates. Although decision tree models could be powerful in solving either classification or regression tasks and could provide accessible predictions, they are prone to overfitting. Ensemble models that implement several decision trees could overcome the determined problem. Five different model types are discussed: RandomForest, GradientBoosting, AdaBoost, Voting, and Stacking. Raman spectroscopy data of whey protein isolates (5 wt.%) with different amounts of hyaluronic acid (0, 0.1, 0.25, and 0.5 wt.%) were used as datasets. In order to generalize the results of the study, WPI samples from three different manufacturers were used. Optimization established that ensembles of 200 decision trees with a maximum depth of four were optimal. The Stacking algorithm, which used RandomForest, GradientBoosting, and AdaBoost as base models with either LogisticRegressor (classification task) or RidgeCV (regression task), was found to be the most efficient in finding differences between the whey protein isolate and its conjugates with hyaluronic acid: specificity of 68.7% and sensitivity of 95.4% (classification task); R² = 0.764 with mean absolute error of 0.068 (regression task). According to the feature importance plots, the Raman bands that were most influential in predicting the results were 1003 cm⁻¹ (phenylalanine, ring breath), 1125 cm⁻¹ (rocking of NH₃⁺), 1206 cm⁻¹ (C–C stretching), 1240 cm⁻¹ (amide III (β-sheet), N–H in-plane bend, C–N stretch), and 1399 cm⁻¹ (aspartic and glutamic acids, C=O stretch of COO–). The findings of this study may contribute to the development of novel methods for quality control and analysis of complex multicomponent systems in various industrial settings. In particular, the ensemble approach can be adapted for monitoring in food processing or as a screening tool in pharmaceutical formulation development. Full article

Water hyacinth (Pontederia crassipes Mart.) is native to the Amazon basin. It has spread to freshwater ecosystems in over 80 countries in tropical, subtropical, and warm temperate regions. Due to its invasive nature, water hyacinth is listed among the world’s 100 worst invasive alien species. Infestations of water hyacinth affect the abiotic components of these ecosystems, including water evaporation, flow, and quality; oxygen and nitrogen levels; sunlight transmission; and greenhouse gases. These changes reduce the abundance and diversity of primary producers in the food web, including phytoplankton and aquatic plants. Consequently, these alterations affect consumers in the food web, including zooplankton, invertebrates, fish, and birds. A negative correlation has often been observed between water hyacinth infestations and the abundance and diversity of these organisms, particularly native species. However, the abundance of some introduced species among these consumers has increased due to water hyacinth infestations. These changes alter the structure and function of natural ecosystems compared to what they were before infestations occurred. Infestations also negatively impact daily human activities and livelihoods, harming local communities and increasing disease transmission. Global warming and the eutrophication of freshwater ecosystems allow water hyacinth to spread into additional non-native areas in high latitudes, thereby increasing the threat it poses. Water hyacinth also contributes to global warming by increasing methane emissions. Over the past century, management strategies have shifted toward restoring the structure and function of ecosystems by progressively integrating various sectors. The infestation of water hyacinth is a complicated, site-specific process influenced by time, climate, existing biotic and abiotic factors, and ecosystem resilience. Therefore, long-term monitoring of environmental outcomes is essential for developing sustainable, site-specific strategies. Robust evaluation systems are necessary to track the efficacy of interventions and to understand the broader ecological ramifications of management strategies. Water hyacinth is still sold in some local markets for ornamental purposes. Raising public awareness of its invasive characteristics is necessary. Full article

Background/Objectives: GLP-1-based obesity pharmacotherapy has shifted clinical attention from the magnitude of weight loss to the quality of weight loss. This review evaluates whether body composition changes during treatment with GLP-1-based agents represent clinically meaningful muscle loss and identifies nutrition, supplementation, exercise, and monitoring strategies that may help preserve lean mass, function, bone health, and nutritional adequacy. Methods: A comprehensive narrative review was performed using focused searches of PubMed, publisher-hosted journal platforms, and reference lists of key primary studies and recent evidence syntheses through March and May 2026. Evidence was organized around body composition, muscle quality and function, dietary protein and micronutrient adequacy, exercise, supplementation, bioelectrical impedance analysis, imaging, and emerging biomarkers. Results: Semaglutide and tirzepatide preferentially reduce fat mass, including visceral and ectopic adiposity, while producing smaller but consistent reductions in lean mass or lean soft tissue. However, DXA-derived lean mass and BIA-derived fat-free mass are not equivalent to skeletal muscle, and lean tissue loss does not necessarily indicate impaired strength or physical performance. The most defensible supportive care model combines food-first nutritional counseling, adequate protein intake, structured resistance exercise, management of gastrointestinal adverse effects, and risk-based monitoring of micronutrient inadequacy. Protein supplementation and nutritionally complete meal replacements may be useful when intake is insufficient, whereas creatine, essential amino acids or leucine, beta-hydroxy-beta-methylbutyrate, fiber, probiotics, omega-3 fatty acids, and multi-ingredient products remain adjunctive options supported mainly by indirect or phenotype-specific evidence. Conclusions: Future GLP-1 trials and clinical care should move beyond body weight and total lean mass toward integrated assessment of muscle quantity, muscle quality, function, bone, and nutritional adequacy, and standardized BIA-based clinical monitoring where advanced imaging is not feasible. Full article

The growing demand for sustainable smart packaging arises from the urgent need to preserve food quality and minimize environmental waste. In this study, multifunctional gelatin-based pH-responsive indicator films were fabricated by incorporating anthocyanins extracted from Hibiscus x archeri W Watson (HAE) and zinc oxide nanoparticles (ZnO-NPs). The incorporation of HAE and ZnO-NPs enhanced surface hydrophobicity, as evidenced by an increase in the water contact angle from 99° to 106°. The Fourier transform infrared (FTIR) analysis verified the lack of new chemical bond formation, indicating that the interactions among components were primarily physical in nature. Distinct colour transitions in buffer solutions of differing pH demonstrated the films’ colorimetric behavior. The films exhibited strong antimicrobial activity against Listeria monocytogenes (18.961 mm), Salmonella typhimurium (18.969 mm), and Aeromonas hydrophila (18.237 mm), whereas the neat gelatin film showed no inhibitory zone. The films also demonstrated superior UV-blocking capacity, with an opacity value (1.34 a.u/mm) compared to the control gelatin film (0.79 a.u/mm). Notably, fish fillets wrapped with the films remained fresh for up to 10 days, compared to day 4 for the unwrapped samples. These findings highlight the considerable potential of multifunctional, active and intelligent packaging for food preservation and real-time freshness monitoring. Full article

The agricultural sector, particularly animal production, faces numerous unprecedented challenges driven by climate change, resource depletion, and an ever-growing global demand for quality food. These challenges are further compounded by the increasing environmental impact of livestock farming, including greenhouse gas emissions, overuse of water and land resources, and the destruction of vital ecosystems. Ensuring the sustainability of animal production systems while mitigating the negative environmental impacts of these factors is essential for future global food security. As the demand for animal-derived products continues to rise, there is a pressing need for innovations that can enhance productivity without compromising environmental integrity or animal welfare. Artificial intelligence (AI) has emerged as a transformative technology with the potential to revolutionize the animal production industry. AI-driven solutions offer promising avenues for optimizing production efficiency, enhancing animal health and welfare, and reducing the environmental footprint of livestock farming. Machine learning, sensor technologies, and advanced data analytics are being increasingly utilized to monitor and predict various aspects of animal farming, such as feed efficiency, disease prevention, and climate resilience. These technologies enable farmers to make data-driven decisions, fostering more sustainable and environmentally responsible practices. This review examines the integration of AI into animal production systems, emphasizing its applications in climate change mitigation, resource management, and advancing sustainability. The discussion addresses how AI technologies can be utilized to improve productivity while minimizing environmental impact and enhancing animal welfare. Additionally, the paper outlines future opportunities, challenges, and potential barriers to integrating AI technologies into livestock farming, thereby ensuring long-term sustainability amid global challenges. Full article