Search Results (3,730)

Electrochemical sensing provides an alternative approach for the trace detection of bioactive substances in fruits. However, the complex matrix in fruit tissues, the coexistence of multiple active components, and the varied pH environments limit the sensing performance and accurate quantitative detection of conventional electrochemical sensors. Herein, a dual-mode electrochemical sensor based on a Co₃O₄@N-MWCNTs modified glassy carbon electrode was developed for the sequential detection of quercetin, rutin, and glucose in fruits under acidic and alkaline conditions. The as-prepared electrode exhibited improved charge transfer efficiency and favorable electrocatalytic activity toward the three target analytes. Under optimal conditions, the sensor displayed wide linear ranges of 0.5~70 μM for quercetin and 0.5~5 μM for rutin in acidic environment, with low detection limits of 0.124 μM and 0.045 μM, respectively. In alkaline environment, the detection limit for glucose was determined to be 8.86 μM. Moreover, four combined machine learning models with feature selection algorithms were established, among which the CARS-RFE+RFR model achieved the best prediction accuracy and robustness for multicomponent quantification. Furthermore, the proposed sensing system was applied to the rapid determination of quercetin, rutin, and glucose in real litchi samples, with recoveries ranging from 98.4% to 105.4%. This study provides a feasible electrochemical strategy for multicomponent detection in complex plant matrices, showing good applicability for rapid on-site analysis in agricultural and food-related applications. Full article

This review analyzes the economic, social, and environmental dimensions of water buffalo (Bubalus bubalis) production and its contribution to the Sustainable Development Goals (SDGs). A scoping review following PRISMA-ScR guidelines was conducted using the Web of Science (2020–2026), resulting in 225 included studies. Buffalo production is a multipurpose system that generates value through milk, meat, hides, manure, draft power, and animal-assisted services, with greater longevity than most livestock species. Economically, it supports income diversification, resource efficiency, and functions as a financial asset that can be sold to cover unexpected expenses. Socially, it enhances food security by providing nutrient-dense products, particularly milk with bioactive compounds associated with potential health benefits, and promotes women’s participation in livestock management and household economies. Environmentally, buffalo systems efficiently utilize low-quality forages, are adapted to marginal conditions, contribute to wetland conservation, and provide ecosystem services. These contributions align with several SDGs (1, 2, 5, 8, 12, 13, and 15). However, sector expansion is constrained by limitations in nutrition, management, veterinary services, and reproductive efficiency, as well as environmental challenges related to methane emissions and life cycle impacts. While global methane emissions from buffalo are lower due to their smaller population, emission intensity remains system-dependent and represents a critical challenge. In conclusion, water buffalo production represents a multifunctional and context-dependent system with significant potential to support sustainable development, although targeted innovations are required to improve productivity and address environmental challenges. Future research should integrate One Health and One Welfare approaches, develop long-term studies, and expand research under diverse experimental and field conditions to better characterize the potential health implications of buffalo-derived products. In addition, strengthening circular economy strategies, including region-specific diets to reduce emissions, remains a priority. Full article

Bacterial infections pose a persistent global threat to public health, driving the demand for rapid, sensitive, and specific detection technologies applicable to disease diagnosis, food safety, and environmental monitoring. Conventional methods like plate culture and polymerase chain reaction are often hampered by lengthy procedures, dependence on complex instrumentation, and requirements for specialized personnel. The emergence of nanozymes and nanomaterials with enzyme-like catalytic activities has introduced a paradigm shift in biosensing, offering superior stability, cost-effectiveness, and tunable functionality compared to their natural counterparts. This review provides a comprehensive and systematic analysis of the latest advancements in nanozyme-mediated bacterial detection. It is structured around the primary signal transduction modalities: colorimetric, fluorescence, electrochemical, and surface-enhanced Raman scattering (SERS) analyses. For each approach, we outline the fundamental design principles, which commonly integrate a synergistic cascade of specific recognition, catalytic signal amplification, and signal readout, and present representative applications for detecting key pathogens like Staphylococcus aureus, Salmonella, and Listeria monocytogenes in complex samples. We evaluate and contrast the advantages, analytical performance, and appropriateness of these different platforms for various practical scenarios. Finally, we address current challenges, including achieving high specificity in complex matrices, precise modulation of nanozyme activity, and method standardization. Perspectives on future research directions aimed at developing next-generation, high-performance, and potentially portable bacterial detection systems are also provided. Full article

In the face of intensifying climate change, agricultural water security in semi-arid zones has emerged as a critical frontier for water governance. This study provides a systematic and critical analysis of the scientific literature to map current research frontiers and structural gaps. The methodology integrated the PRISMA 2020 protocol and a modified Methodi Ordinatio, spanning a search period from 2014 to 2026 across the Science Direct and SciELO databases. From an initial broad screening, 136 high-impact articles were selected based on rigorous inclusion and exclusion criteria. The findings reveal a significant fragmentation of knowledge, characterized by a high prevalence of small-scale studies (25 articles) and limited interdisciplinarity. Notably, a governance-centric approach is present in only 20% of the literature, while the Water–Energy–Food Nexus appears in just 6%, signaling a major disconnect in holistic management. Based on these results, this study identifies water governance and socioeconomic integration as the most pressing research gaps. Consequently, an integrated conceptual framework is proposed, built upon three pillars: Governance, Technology, and Environment (GET). This study concludes that advancing the frontiers of agricultural water security requires moving beyond isolated solutions toward a structured, systemic, and interdisciplinary integration. Full article

Background: Schools are widely recognized as key settings for promoting healthy eating behaviors and supporting childhood obesity prevention. In recent years, increasing attention has been devoted to experiential and interactive nutrition education strategies designed to actively engage children and adolescents in food-related learning processes. These approaches move beyond traditional didactic teaching and include practical and participatory formats, such as cooking activities, school gardening, digital or app-based learning tools, workshops and educational camps, and game-based learning interventions. Objective: This narrative review aims to provide an overview of experiential school-based nutrition education interventions, describing the main types of programs implemented in school settings and summarizing their reported effects on nutrition knowledge, attitudes, and eating behaviors among children and adolescents. Results: Across intervention studies and systematic reviews, hands-on and interactive educational models, including cooking classes, gardening programs, digital learning tools, workshops or camps, and board game-based interventions, frequently report improvements in nutrition knowledge, attitudes toward food, food-related skills, and self-efficacy. These programs seek to strengthen food literacy by combining experiential learning with educational content delivered within the school environment. Evidence regarding changes in dietary intake, diet quality, and anthropometric outcomes is more heterogeneous, with some studies reporting improvements in eating behaviors and others showing more modest or short-term effects. Program outcomes appear to be influenced by several contextual factors, including intervention duration, curriculum integration, teacher involvement, and the availability of resources supporting implementation. Conclusions: Experiential and interactive approaches represent an increasingly adopted strategy in school-based nutrition education. Their effectiveness appears to depend on the quality of implementation, the degree of integration within the school curriculum, and the broader educational context. Future research should further explore how different experiential formats can be optimally integrated into school systems to support the development of food literacy and sustainable healthy eating behaviors among children and adolescents. Full article

DNA must be efficiently extracted from samples to accurately test the authenticity of food, particularly from processed matrices in which DNA integrity may be compromised. We systematically evaluated the efficiency of extracting DNA from dairy and blood products by four methods, namely SDS-CTAB, SDS-isopropanol precipitation, guanidine isothiocyanate magnetic beads, and a commercial kit. The guanidine isothiocyanate-magnetic bead method yields high quantities and purity of DNA; for example, the yield obtained from chicken blood samples was 318.34 ± 4.77 ng/µL, with an A260/A280 ratio ranging from 1.8 to 2.0. The processing time of this method was compared with the DNA Extraction Kit shorter by 40% and unlike methods such as the SDS-CTAB protocol, does not require the use of toxic reagents such as phenol or chloroform, meeting green chemistry requirements. Among the dairy and blood samples tested, it enables the extraction of DNA in quantities comparable to those obtained using commercial kits; moreover, the DNA yield achieved is 20–30% higher than that of these kits. Furthermore, this method is free from the limitations associated with protein contamination and amplification instability often encountered in protocols such as the CTAB-SDS and SDS-isopropanol methods. The magnetic bead approach was adaptable for complex matrices and demonstrated strong tolerance to coexisting contaminants, thereby improving extraction performance in challenging food samples. The magnetic bead surface functionalization and buffer systems could be improved to further increase their versatility. This method enables reliable DNA extraction and advanced technical support for DNA analysis. Full article

Food packaging constitutes a pivotal enabler within the contemporary food industry, requiring continuous innovation to address evolving challenges. Traditional packaging systems typically provide passive protection, which is inadequate for addressing dynamic microbial shifts and spoilage-induced microenvironmental instabilities. In contrast, corrective responsive food packaging (CRFP) takes a distinct approach through the integration of sensing capabilities and targeted active intervention. Upon detection of specific stimuli, CRFP systems precisely deliver bioactive agents to mitigate food deterioration. This review systematically summarizes recent advances in CRFP technology, offering a comprehensive overview of its core response mechanisms, functional materials, advanced carrier systems, and future research priorities. Special emphasis is given to (i) stimuli-responsive systems, including single-stimulus (pH, enzyme, humidity, temperature, and light) and multi-stimulus-responsive systems, detailing their triggering mechanisms and practical applications; and (ii) functional materials and carriers, exploring their synergistic effects for optimized bioactive release. This review aims to provide a structured framework for the design and implementation of CRFP, facilitating its translation from laboratory to industrial practice and contributing to the development of sustainable and efficient food preservation strategies. Full article

Pseudomonas fluorescens is a major psychrotrophic bacterium responsible for spoilage in refrigerated foods, particularly dairy products, where deterioration is driven by biofilm formation, quorum sensing (QS) regulation, and the secretion of thermostable lipases. Conventional control strategies reduce bacterial loads but often fail to prevent enzymatic spoilage. Plant-derived phenolic compounds have been widely reported as QS inhibitors and lipase modulators in various biological systems; however, evidence specifically addressing their effects on P. fluorescens regulatory networks and bacterial lipases remains limited. This review critically examines current knowledge on QS-mediated biofilm formation and lipase production in P. fluorescens and analyzes the reported inhibitory activity of phenolic compounds, with emphasis on oak (Quercus spp.)-derived metabolites. While flavonoids and phenolic acids such as quercetin, gallic acid, and p-coumaric acid have demonstrated QS inhibition and antilipolytic activity in other Pseudomonas species and pancreatic models, direct mechanistic validation in P. fluorescens lipases is scarce. Moreover, most studies rely on crude plant extracts without comprehensive metabolomic characterization, and the potential contribution of additional oak metabolites, including terpenoids, remains largely unexplored. Identifying these gaps is essential for advancing toward integrative approaches that combine enzymology, molecular modeling, and validation in food-relevant systems. Full article

Dioxins are highly persistent organic pollutants that exist in soil. Their hydrophobic and lipophilic characteristics facilitate long-term stability, posing high risks to the ecosystem and human health. They can be released by different sources, such as the incineration of waste materials, industrial activities, the production of pesticides, and natural or accidental events like forest fires. Dioxins accumulate in food chains and persist in the environment because dioxins are less volatile as well as chemically stable and can strongly bind to organic matter. The accumulation and persistence of dioxins in aquatic and terrestrial systems make them a significant threat to the environment, even at very low concentrations. This review explains the key sources of dioxin-contaminated soil, including industrial emissions and atmospheric deposition, and assesses the associated risks. The transport, places of contamination, and overall status of dioxins are also highlighted in this study. The review also examines the mechanisms of dioxin toxicity, focusing on their interference with hormonal functions and gene expression, as mediated through the aryl hydrocarbon receptor (AhR). This AhR activation leads to gene responses and causes immunotoxicity, endocrine disruption, and oxidative stress. Furthermore, various remediation strategies like biological, physical, and chemical remediation are discussed here as effective approaches for reducing ecological and health risks and promoting soil sustainability. Full article

The article is devoted to developing methodological approaches to multi-criteria resource optimization of technological solutions in Nature Use Projects, considering the growing shortage of water and energy resources, climate change, and post-war transformation of Ukraine’s agricultural sector. The need to transition from traditional technical and economic optimization models to integrated assessment approaches, which consider ecological, resource, and economic aspects of the project implementation effectiveness, is substantiated. The methodological basis of the study is a combination of Multi-Criteria Decision-Making and the Water-Energy-Food Nexus concept, enabling the necessary adaptive management and formalizing the process of project decision-making under multifactor uncertainty. A set of indicators of resource-ecological and economic efficiency is proposed, including indicators of productivity, weather and climate risk, resource use, environmental reliability, investment attractiveness, etc. A key feature of this approach is the transformation of resource-ecological indicators into a value form, ensuring their integration with economic indicators within a single optimization model. Based on a machine experiment for the conditions of the Kherson region, an assessment of the effectiveness of various irrigation regimes, which differ from the project irrigation regime in terms of watering and irrigation norms, in terms of their level of provision with water and energy resources, was carried out. It was determined that, under the studied conditions, in dry years (p = 70%), the permissible deficit threshold is approximately 30%, achieving a compromise between economic efficiency and environmental acceptability. Adaptive management of irrigation regimes has been shown to reduce the resource intensity of production without a significant loss of productivity. This creates a basis for revising outdated design standards, which focused on 100% satisfaction of water needs, in favor of adaptive models that account for the real resource potential of the territory. This approach transforms irrigation from a resource-intensive industry into a tool for sustainable territorial development, where the priority is the efficiency of each cubic meter of water and kilowatt-hour of energy used, rather than gross collection. It has been proven that the implementation of resource optimization as a basic principle of natural resource project management contributes to increasing the efficiency of natural capital use, minimizing ecological risks, and ensuring the sustainable development of the agricultural sector. The obtained results can be used to substantiate engineering solutions in projects for the restoration and modernization of water management and land reclamation systems in Ukraine. Full article

The valorization of dairy by-products, particularly whey, represents a key challenge and opportunity in sustainable food systems. This study aimed to evaluate the physicochemical and amino acid composition of milk and whey-derived products and to identify optimal whey–milk mixtures using integrated multivariate and desirability-based approaches. Ten model systems (M1–M10) were prepared with increasing whey content (7.5–75%), and their composition was analyzed using infrared spectroscopy and high-performance liquid chromatography. Multivariate analysis, including PCA and correlation heatmaps, revealed that protein, casein, TS, SNF, and amino acid fractions (ΣEAA and ΣBCAA) were the primary drivers of compositional variability, whereas lactose and acidity-related parameters contributed to secondary differentiation. Desirability function analysis was applied by integrating nutritional quality, functional balance, and sustainability score into a composite index. The results demonstrated that intermediate formulations achieved a more balanced profile compared with extreme compositions. Among all mixtures, the formulation containing 30% whey (M5) showed the highest overall desirability within the evaluated parameters, reflecting a favorable balance between compositional quality and whey utilization. These findings highlight the potential of integrated analytical approaches for the development of nutritionally optimized and resource-efficient dairy systems. Full article

The high consumption of citrus fruits generates large amounts of peel bioresidues, whose valorization represents an important strategy for sustainable agri-food systems. This study aimed to characterize the nutritional, chemical, and bioactive properties of flours obtained from orange (FL), tangerine (FT), lime (FLA), and lemon (FLO) peels, and to evaluate their potential as functional food ingredients. The flours were evaluated for proximate composition, organic acids, phenolic compounds, fatty acids, free sugars, and bioactive properties. Lime flour showed the highest protein, ash, dietary fiber, and total phenolic contents, with hesperidin identified as the predominant compound. The corresponding extracts exhibited relevant antioxidant, antimicrobial, antiproliferative, and nitric oxide (NO) production inhibitory activities, with lime flour presenting the strongest overall bioactive potential. Based on these results, lime flour was selected for application in a food model by partially replacing wheat flour (10% and 20%) in “Madalenas”, a traditional Portuguese muffin cake. The incorporation of lime flour improved product preservation compared with the control formulation and samples containing a synthetic preservative (potassium sorbate). These findings highlight the potential of citrus peel flours, particularly lime flour, as natural functional ingredients and sustainable alternatives for food formulations, contributing to waste valorization and circular economy approaches in the agri-food sector. Full article

Organic farming has gained increasing relevance worldwide due to its environmental benefits and its prominent role in sustainable food systems; however, the persistence of organic farms remains uneven across regions, particularly within the European Union. While the number of organic farms has grown overall in the EU, significant exits from organic production highlight the need to better understand the factors shaping farm survival, especially in newer Member States, where organic conversion and maintenance support schemes are often implemented through area-based CAP payments. This study aims to identify the structural and contextual determinants of short-term organic farm persistence in Hungary within a broader European context. Using farm-level data for the period 2020–2023, including Standard Output (SO) indicators, we applied a combined modelling framework based on Logistic Regression, Decision Trees, and Random Forest algorithms to assess the relative importance of economic, structural, and regional variables. The results show that organic farm persistence is primarily driven by structural characteristics such as farm size, economic scale, degree of conversion to organic farming and regional embeddedness, while production specialization and organizational features play a secondary, conditional role. The convergence of results across modelling approaches indicates that survival is shaped by hierarchical structural constraints rather than isolated management decisions. Our findings suggest that policy measures aiming to stabilize and expand the organic sector should move beyond uniform incentives, such as area-based payments, and should place greater emphasis on the structural conditions of farms and region-specific support mechanisms. Full article

Global population growth poses major challenges to agricultural systems, demanding more efficient strategies to secure food production. Conventional approaches have relied heavily on chemical inputs; however, their overuse disrupts ecosystems, threatens biodiversity, and undermines human and environmental health. To ensure sustainable productivity, it is essential to explore alternative approaches that leverage microbial functions to enhance plant growth and resilience. Bacteria are among the most abundant soil microorganisms, playing central roles in biogeochemical cycles and plant health. While well-studied phyla such as Pseudomonadota, Actinomycetota, and Bacillota have been widely applied as biofertilizers and biocontrol agents, members of the phylum Bacteroidota remain comparatively understudied despite being consistently abundant in plant-associated microbiomes. This review synthesizes current knowledge on Bacteroidota, highlighting their taxonomy, ecological diversity, contributions to nutrient cycling, and mechanisms that promote plant growth, as well as biotic and abiotic stress tolerance. We also discuss the limitations that hinder their application, particularly challenges in cultivation and isolation, and outline future research directions to harness their potential for sustainable agriculture. Full article

The precise and timely diagnosis of grapevine diseases is paramount for ensuring food security and mitigating economic losses within the viticulture sector. While existing deep learning models offer high accuracy, their computational intensity and hardware requirements often hinder their use in portable or low-power field systems. This study addresses this gap by proposing GrapeLeafNet, a lightweight convolutional neural network optimized for efficient feature extraction. GrapeLeafNet introduces a strategic hybrid approach that combines the low parameter efficiency of models like SqueezeNet with the rapid feature propagation advantages offered by shallow architectures such as AlexNet. By eliminating the sequential processing latency caused by SqueezeNet’s 18-layer deep structure and the excessive 61-million-parameter memory burden of AlexNet, this model establishes a critical balance between low latency and high accuracy through its optimized 7-layer architecture. Characterized by an original integration of standard convolutional layers, batch normalization, and max pooling, GrapeLeafNet achieves high computational efficiency with only 1.6 million parameters and a 6.26 MB memory footprint. This structural optimization enhances deep feature hierarchies, enabling the model to focus on distinctive pathological signs within complex leaf patterns and maximize classification sensitivity by filtering out irrelevant features. The evaluation was conducted using the Niphad Grape Leaf Disease (NGLD) dataset, incorporating data augmentation to mitigate inherent class imbalances. Additionally, data augmentation techniques were employed to mitigate inherent class imbalances within the dataset. Experimental results demonstrate that GrapeLeafNet achieved 97.06% accuracy and a 94.77% F1-score on the original dataset, outperforming recent benchmarks by 2.46%. Following augmentation, performance reached 98.29% accuracy and a 98.16% F1-score, representing a 6.16% higher F1-score than contemporary models. GrapeLeafNet exhibits high robustness against asymmetric class distributions and establishes a significant performance margin over existing architectures. Its lightweight nature, combined with superior accuracy and F1-score metrics, makes it an ideal candidate for integration into mobile devices and real-time agricultural monitoring systems. Full article