Search Results (12,355)

Sorghum-based porridges are a key component of breakfast meals in South African school feeding programmes. While these meals support learner nutrition and educational outcomes, their effectiveness depends on learner acceptance and the extent of plate waste. This study assessed acceptance and plate waste of two sorghum-based porridges—Mabele (100% sorghum) and Morvite (pre-cooked sorghum, 75–100% depending on flavour, with possible inclusion of soya, cow’s milk, and wheat/gluten)—compared with instant maize meal, Jungle Oats (100% wholegrain oats), within the Tiger Brands Foundation breakfast programme. Patterns of waste and underlying reasons were examined across five provinces. A mixed-methods approach was used in 25 primary schools across Gauteng, KwaZulu-Natal, Limpopo, North West, and Northern Cape. Quantitative data were collected through 10-day food waste diaries completed by Volunteer Food Handlers and analysed using descriptive statistics, ANOVA, and regression models. Qualitative data were obtained from 75 semi-structured staff interviews and 25 learner focus groups, analysed thematically using ATLAS.ti version 22. Overall, food waste was low, with “no food waste” reported in over half of the observations. Acceptance of sorghum-based products varied. Morvite was generally well accepted, whereas Mabele was frequently disliked in some provinces. Key drivers of waste included food dislike, poor preparation, bland flavour, and learner absenteeism, with serving conditions and a lack of utensils as secondary factors. Although waste was modest, variability in acceptance of sorghum-based porridges suggests the need to improve preparation quality, flavour, and serving conditions to enhance programme effectiveness. Full article

Fish occupy pivotal trophic positions in aquatic ecosystems, mediating energy transfer and shaping community structure through their feeding interactions. Unraveling these dietary relationships is therefore fundamental for understanding ecosystem functioning and supporting sustainable fisheries management. Traditional morphological analyses, while informative, often fall short in resolving fine-scale prey diversity and trophic linkages. In contrast, DNA metabarcoding has revolutionized dietary studies by enabling comprehensive, high-resolution, and non-invasive characterization of prey assemblages. This review synthesizes recent progress in applying DNA metabarcoding to fish trophic ecology, emphasizing technical innovations, methodological standardization, and ecological insights. We discuss how DNA metabarcoding has advanced the understanding of food web complexity, species interactions, and ecological responses to environmental change. However, challenges persist in quantification accuracy, reference database completeness, and cross-source contamination. Future research integrating multi-marker approaches, standardized workflows, and multi-method integration holds promise for transforming DNA metabarcoding into a powerful, reliable and mechanistic tool for trophic ecology. Collectively, these developments will bridge molecular data with ecological theory, strengthening the scientific foundation for ecosystem-based fisheries management. Full article

Accurate patent valuation remains a persistent challenge in intellectual property management, particularly in the food industry, where technological homogeneity and rapid innovation cycles introduce substantial noise into observable performance indicators. Traditional valuation approaches, whether based on subjective expert judgment or citation-based metrics, often struggle to effectively reduce information uncertainty in this context. To address this limitation, this study proposes an objective, data-driven patent valuation framework grounded in information theory. We construct a multidimensional evaluation system comprising nine indicators across technological, legal, and economic dimensions and apply it to a large-scale dataset of 100,648 invention patents. To address the heavy-tailed nature of patent indicators without sacrificing the information contained in high-impact outliers, we introduce a square-root transformation strategy that stabilizes dispersion while preserving ordinal relationships. Indicator weights are determined objectively via Shannon entropy, capturing the relative scarcity and discriminatory information content of each signal, after which comprehensive value scores are derived using the TOPSIS method. Empirical results reveal that the entropy-based model assigns dominant weights to so-called “costly signals”, specifically PCT applications (29.53%) and patent transfers (24.36%). Statistical correlation analysis confirms that these selected indicators are significantly associated with patent value ($p<0.001$), while bootstrapping tests demonstrate the robustness of the resulting weight structure. The model’s validity is further evaluated using an external benchmark (“ground truth”) dataset comprising 55 patents recognized by the China Patent Award. The proposed framework demonstrates substantially stronger discriminatory capability than baseline methods, awarded patents achieve an average score 2.64 times higher than that of ordinary patents, and the enrichment factor for award-winning patents within the Top-100 ranking reaches 91.5. Additional robustness analyses, including benchmarking against the Weighted Sum Model (WSM), further confirm the methodological stability of the framework, with sensitivity analysis revealing an exceptional enrichment factor of 183.1 for the Top-50 patents. These findings confirm that the Entropy–TOPSIS framework functions as an effective information-filtering mechanism, amplifying high-value patent signals in noise-intensive environments. Consequently, the proposed model serves as a generalizable and theoretically grounded tool for objective patent valuation, with particular relevance to industries characterized by heavy-tailed data and high information uncertainty. Full article

Background: Management of pediatric anaphylaxis in the emergency department remains clinically important. The research investigated pediatric anaphylaxis medical indicators together with physician adherence to international treatment protocols at a Turkish tertiary medical center. Methods: Between September 2014 and July 2025, 166 pediatric anaphylaxis patients were retrospectively reviewed for triggering factors, clinical findings, treatment approaches, and quality indicators. Results: The mean age of the patients was 7.4 ± 5.6 years. Food allergy was the main cause with 53%, followed by drugs with 24.7%. Food allergy in infants was 85.7%, while drug reactions in adolescents reached 37.2% (p < 0.001). Skin findings were present in 93.4% of the patients, and respiratory symptoms were present in 67.5% of the patients. Epinephrine was administered to 97.6% of patients, 95.2% of whom were given intramuscularly. The rate of epinephrine administration in the first 30 min was 61.1%. Drug-induced anaphylaxis showed the highest proportion of severe cases (81.6%, p < 0.001). A biphasic reaction was seen in 6%. The auto-injector prescription rate was 7.8%, and the allergist referral rate was 15.7%. No deaths were observed. Conclusions: While acute-phase management largely adheres to international guidelines, significant gaps persist in post-discharge care with low auto-injector prescription and allergist referral rates. Full article

A rapidly emerging approach within the scientific community involves the utilization of waste streams for renewable energy generation, particularly through biomethane production. A key aspect of this approach lies in the co-digestion of diverse waste streams, which can enhance process efficiency and contribute to a more effective reduction in the organic load. The present study investigates the anaerobic digestion of a mixture of food waste leachates and dairy waste (cheese whey wastewater), with a dual objective: to evaluate the reduction in organic-load efficiency of the mixed substrate and to assess the production of biogas enriched in biomethane content. Three distinct mixing ratios by volume of the two waste streams (25%/75%, 50%/50% and 75%/25%) were subjected to an anaerobic digestion process under the same SIR. The performance of each mixture was assessed in terms of both reduction in organic-load efficiency and biomethane yield, followed by a comparative analysis to identify the optimal mixing ratio. The results indicate that while the organic-load reduction remains consistently effective across all mixing ratios, the biomethane production potential is notably higher for the 25%/75% waste mixture, highlighting it as the most promising configuration for both energy recovery and waste treatment efficiency. Full article

Background: Rice is one of the world’s main staple crops , and improving its productivity and resilience is important to achieving food security under varying climatic conditions. Objectives: This systematic review synthesizes the existing evidence on the application, technical limitations, and potential of the development of genome editing technologies (CRISPR-Cas) in rice (Oryza sativa L.), as well as presents a novel approach called the CRISPR Trait Prioritization and Readiness Framework (CTPRF). Methods: Peer-reviewed articles that reported applications of genome editing based on the CRISPR-Cas system in the genome of rice for trait improvement or functional genomics were identified through searches fromPubMed, Scopus, Web of Science, and Google Scholar with studies published between 2012 and 2025. Studies were screened on predefined inclusion criteria related to experimental validation, reporting of editing efficiency, and clear phenotypic results. Data on CRISPR systems, target genes, methods of delivery, traits modified, and phenotypic results were extracted and synthesized by comparative analysis. Results: A wide variety of different CRISPR systems have been used in rice, and our results indicate that NHEJ-mediated knockouts are effective in average genotypes with editing efficiencies in the range of 70–90%, but HDR and prime editing are still under 10%. The CTPRF is being introduced as a strategic decision support tool to evaluate traits from four dimensions: technical feasibility, phenotypic predictability, impact potential, and regulatory pathway. We use this framework for case studies in pioneering countries (USA, Japan, China) and show how it can be useful for guiding research investment and policy. Conclusions: CRISPR-Cas technologies have transformed rice breeding, but their introduction requires overcoming genotype-dependent barriers to transformation and negotiating patchwork regulatory environments. The CTPRF offers a roadmap for the acceleration of the development of climate-resilient and nutritious rice varieties for the action plan. Full article

In recent years, against the backdrop of increasingly prominent global climate change and environmental issues, high-efficiency cooling technologies and energy-saving materials have become key research focuses. Radiative cooling, which reflects sunlight and emits thermal radiation into outer space, enables passive cooling without energy consumption. The phase separation method has emerged as a promising approach for fabricating porous daytime radiative cooling materials, attracting extensive research interest due to its favorable processability, excellent cooling performance, low cost, and scalability. Based on radiative cooling principles, this review summarizes the preparation methods, structural design, and application fields of porous radiative cooling films fabricated via the phase separation method. Furthermore, it is suggested that phase-separated porous radiative cooling films hold great potential in green buildings, personal thermal management, and food preservation. Full article

Water scarcity in arid/semi-arid regions restricts agricultural sustainability systems and hinders the achievement of regional sustainable development goals, especially in northwest China’s extremely arid areas, where acute water supply–demand conflicts and inefficient traditional practices intensify competition for water between agricultural and ecological sectors. This study aims to verify the effectiveness of an intelligent automatic irrigation system in mitigating water scarcity pressures and enhancing agricultural sustainability in the Shule River Basin of northwestern China, a region where traditional irrigation methods not only yield suboptimal crop outputs but also undermine long-term water resource sustainability. A smart irrigation module, integrating “sensing–decision–execution” processes, was embedded within a digital twin platform to enable precise, resource-efficient water management that aligns with sustainable development principles. Sunflower (Helianthus annuus L.), the most popular cash crop in the area, was used as the test crop, with three soil moisture-based irrigation levels compared against traditional farmer practices. Key indicators including leaf area index (LAI), dry biomass, grain yield, and irrigation water use efficiency (IWUE) were systematically evaluated. The results showed that (1) LAI increased from the seedling to flowering stage, with smart irrigation treatments significantly outperforming farmer practices in both crop growth and water-saving effects, laying a foundation for sustainable yield improvement; (2) total dry biomass at maturity was positively correlated with irrigation amount but smart irrigation optimized the allocation of water resources to avoid waste, balancing productivity and sustainability; (3) grain yield peaked within 70–89% field capacity (fc), with further increases leading to diminishing returns and unnecessary water consumption that impairs sustainable water use; (4) IWUE followed a parabolic trend, reaching its maximum under the same optimal irrigation range, indicating that smart irrigation can maximize water productivity while preserving water resources for ecological and future agricultural needs. The digital twin-driven smart irrigation system enhances both crop yield and water productivity in arid regions, providing a scalable model for precision water management in water-stressed agricultural zones. The results provide a key empirical basis and technical approach for sustainably using irrigation water, optimizing water–energy–food–ecology synergy, and advancing sustainable agriculture in arid regions of Northwest China, which is crucial for achieving regional sustainable development objectives amid worsening water scarcity. Full article

Deoxynivalenol (DEOX), a dangerous mycotoxin, causes serious health problems for humans and animals. Hence, the on-site monitoring of DEOX has begun to be important in the health and food sectors in recent years. In the present study, a molecularly imprinted surface plasmon resonance (SPR) sensor based on sulfur-doped boron graphitic carbon nitride (S-B-g-C₃N₄) was developed and applied for detecting DEOX in drinking water and orange juice samples, achieving high recovery. After the S-B-g-C₃N₄ nanocomposite was synthesized via thermal polycondensation and microwave treatment with a highly environmentally friendly approach, a SPR chip was modified with the S-B-g-C₃N₄ nanocomposite considering the high affinity between gold and sulfur. Then, the molecularly imprinted SPR sensor based on the S-B-g-C₃N₄ nanocomposite was prepared in the presence of methacryloylamidoglutamic acid (MAGA) as the monomer and N,N′-azobisisobutyronitrile (AIBN) as the initiator. The DEOX-imprinted SPR sensor based on the S-B-g-C₃N₄ nanocomposite showed linearity from 1.0 to 10.0 ng L⁻¹, with a limit of quantification (LOQ) of 1.0 ng L⁻¹ and a limit of detection (LOD) of 0.30 ng L⁻¹. Finally, the selectivity, repeatability, and reproducibility of the DEOX-imprinted SPR sensor based on the S-B-g-C₃N₄ nanocomposite were investigated. Full article

For millennia, cats have been valued worldwide as biological agents for rodent control. Our previous qualitative research found that Australian dairy farmers valued cats for rodent management and companionship, while also highlighting welfare and operational challenges when populations were unmanaged. We therefore argued for a structured, humane management approach. Critics questioned our methodology and portrayed our publications as a blanket endorsement of placing cats on farms. Here, we clarify the scope and limitations of our earlier work and reaffirm that unmanaged cats can create significant risks, including disease transmission, poor welfare, environmental concerns, and psychological stress for farmers and veterinary professionals tasked with lethal control. Responsible management, through sterilization, feeding, healthcare, and formal recognition of some cats as working animals, has the potential to reduce these harms while aligning with farmer values and food safety requirements. Farmers also supported barn/working-cat programs to replace sterilized cats lost through attrition and because they recognized the wellbeing impact on shelter staff required to humanely kill healthy cats. While more research is needed to empirically examine the benefits of the humane management of farm cats, alternatives to cats suggested by critics, such as owls or dogs, lack equivalent evidence or feasibility in dairy systems. Given that cats already exist on many farms, we conclude that responsible management offers a pragmatic, humane, and One Welfare-aligned pathway while longer-term studies are undertaken. Full article

Background/Objectives: Emotional eating is a tendency to increase food consumption in order to modify a negative emotional state, but little is known about this phenomenon or about the way to assess it. The aim of the study was to assess the emotional eating in the population of Polish girls using various questionnaires, in order to compare the results obtained while using various tools. Methods: The emotional eating was assessed in a sample of n = 771 girls (age 15–18 years) from a nationwide PLACE-19 Study population, recruited based on a random quota sampling of Polish secondary schools. The results were gathered within the Computer-Assisted Web Interview (CAWI) and compared for four tools: Emotional Eating Scale for Children and adolescents (EES-C), Emotional Eating Subscale (EE-3) of Three-Factor Eating Questionnaire (TFEQ), Emotional Overeating Questionnaire (EOQ-5), and Emotional Eater Questionnaire (EEQ). Results: The analysis of correlation revealed statistically significant association for comparison of all the questionnaires (p < 0.001). For a comparison of EE-3 and EOQ-5, the strongest correlation between the results, and the second highest share of the studied group presenting agreement in emotional eating category was stated, indicating the strongest agreement. For a comparison of EES-C and EOQ-5, as well as EES-C and EEQ, the weakest correlation between the results, and the lowest share of the studied group presenting agreement in emotional eating category was stated, indicating the weakest agreement. Conclusions: It may be suggested that in studies conducted in a group of girls the recommended approach would be to use at least two various questionnaires to assess emotional eating, to enable comparing results, as the knowledge gathered so far does not allow an indication of the most reliable tool. As there is only a fair agreement between compared tools, the arbitrary choice of one tool may significantly influence the formulated conclusions. Moreover, there is a need to conduct more studies assessing emotional eating while using various questionnaire methods, in order to compare the results obtained while using various tools and to indicate the most reliable questionnaires. Full article

This study adopts a biochemical approach to sequester CO₂ while producing biomass rich in protein and lipids, using an adapted strain of Chlorella vulgaris (ALE-Cv), which had previously evolved to tolerate a gas mixture containing 10% CO₂ and 90% air. The research studied the operating parameters of the batch photobioreactor for ALE-Cv to evaluate the effects of inoculum size, photoperiod, light intensity, pH of culture, and CO₂ supply rate on biomass productivity and CO₂ bio-fixation rate. The optimal conditions were identified as 16:8 h light–dark cycles, 5000 lux, pH 7, 20 mL of 10 g/L inoculum, and 0.6 VVM; the system achieved a maximum total biomass production of 7.03 ± 0.21 g/L with a specific growth rate of 0.712 day⁻¹, corresponding to a CO₂ bio-fixation of 13.4 ± 0.45 g/L in batch cultivation. While the pre-adapted strain of Chlorella vulgaris under the same operating conditions, except for the gas supply, which was air, achieved a maximum total biomass production of 0.52 ± 0.008 g/L, and the total CO₂ bio-fixation was 1.036 ± 0.021 g/L during 7-day cultivation. A novel semi-continuous harvesting process, with and without nutrient addition, was also investigated to maximise biomass yield and enable water recycling for culture media. The maximum biomass production in semi-continuous harvesting process with and without nutrition added was 5.29 ± 0.09 and 9.91 ± 0.11 g/L, while the total corresponding CO₂ bio-fixation was 9.70 ± 0.13 and 18.16 ± 0.11 g/L, respectively, during 15-day cultivation. The findings provide critical insights into enhancing CO₂ bio-fixation through adaptive evolution of ALE-Cv and offer optimal operational parameters for future large-scale microalgae cultivation. This research also links microalgae-based CO₂ sequestration to green technologies and the bioeconomy, highlighting its potential contribution to climate change mitigation while supporting environmental sustainability, food security, and ecosystem resilience. Full article

Bongkrekic acid (BKA), a highly lethal toxin, has been implicated in frequent poisoning incidents in recent years, posing a serious threat to global food safety and creating an urgent need for rapid and sensitive detection methods. This review provides a systematic analysis of the entire BKA detection technologies, covering sample pretreatment techniques, instrumental analysis, immunoassays, and biosensing methods. It assesses the merits of key methods and also explores the strategic cross-application of detection paradigms developed for analogous toxins. This review delivers a comprehensive and critical evaluation of BKA detection technologies. First, it discusses sample pretreatment strategies, notably solid-phase extraction (SPE) and QuEChERS. Subsequently, it analyzes the principles, performance, and applications of core detection methods, including high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS), high-resolution mass spectrometry (HRMS), time-resolved fluorescence immunoassay (TRFIA), dual-mode immunosensors and nanomaterial-based sensors. Instrumental methods (e.g., HRMS) offer unmatched sensitivity [with a limit of detection (LOD) as low as 0.01 μg/kg], yet remain costly and laboratory-dependent. Immunoassay and biosensor approaches (TRFIA and dual-mode sensors) enable rapid on-site detection with high sensitivity (ng/mL to pg/mL), though challenges in stability and specificity remain. Looking forward, the development of next-generation BKA detection could be accelerated by cross-applying cutting-edge strategies proven for toxins—such as Fumonisin B1 (FB1), Ochratoxin A (OTA), and Aflatoxin B1 (AFB1)—including nanobody technology, CRISPR-Cas-mediated signal amplification, and multimodal integrated platforms. To translate this potential into practical tools, future research should prioritize the synthesis of high-specificity recognition elements, innovative signal amplification strategies, and integrated portable devices, aiming to establish end-to-end biosensing systems capable of on-site rapid detection through multitechnology integration. Full article

The farmland protection compensation system plays a pivotal role in addressing the dual global crises of food insecurity and ecological degradation, as well as in overcoming persistent challenges in China’s agricultural governance. By internalizing the opportunity costs borne by stakeholders fulfilling statutory obligations for farmland protection, this mechanism offers effective incentives for their active engagement, thereby establishing a societal-level interest-balancing framework conducive to sustainable land management. Existing research in China has mainly concentrated on empirical analyses of implementation models, regional disparities, and policy effectiveness evaluations of farmland protection compensation schemes. Nevertheless, systematic exploration of the normative construction and improvement pathways of the compensation rules themselves remains relatively underdeveloped. Based on the practical requirements and institutional constraints of China’s current farmland protection compensation regime, this study adopts an integrated approach that combines comparative legal analysis, textual review of regulatory documents, and empirical research to critically examine feasible paths for institutional improvement. The research findings emphasize that the optimization of China’s farmland protection compensation rules should be guided by three core principles: market orientation, ecological sustainability, and precision-based targeting. Specifically, the establishment of scientifically sound methods for calculating compensation amounts is crucial for reconciling the interests of conservation actors with inter-regional development disparities. Meanwhile, the compensation mechanism should be strategically utilized to strengthen positive incentives for ecosystem conservation. Ultimately, such institutional improvement aims to ensure the sustainable utilization of farmland resources while safeguarding global food security and maintaining the Earth’s ecological balance. Full article

Accurate and timely agricultural mapping is essential for supporting sustainable agricultural development, resource management, and food security. Despite its importance, Vietnam lacks detailed and consistent large-scale agricultural maps. In this study, we produced the first national-scale agricultural map of Vietnam for 2024 using a UNet++ deep learning architecture that integrates multi-temporal Sentinel-1 and Sentinel-2 imagery with Global-30 DEM data. The resulting product includes 15 land-cover categories, eight of which represent the most popular agricultural types in Vietnam. We further evaluate the model’s transferability by applying the 2024 trained model to generate a corresponding map for 2020. The approach achieves overall classification accuracies of $83.01\%\pm 1.37\%$ (2020) and $80.09\%\pm 0.76\%$ (2024). To address class imbalance within the training dataset, we introduced an adaptive weight combined loss function that automatically adjusts the weight of dice loss and cross-entropy loss within a combined loss function during the model training process. Full article