Search Results (18,222)

Small-scale inland fisheries in the Amazon are critical for food security, yet their sustainability is increasingly threatened by overexploitation and environmental degradation. In data-limited contexts such as the northern Ecuadorian Amazon, the absence of continuous monitoring constrains the development of adaptive management strategies. This study develops an integrated socio-ecological baseline to support the establishment of fisheries agreements in five Indigenous communities of the Napo and Aguarico rivers. Through a participatory monitoring approach, we generated reproductive parameters (gonadosomatic index, fecundity, size at first maturity), population structure metrics, and length–weight relationships for key subsistence species across three hydrological phases. Reproductive investment exhibited marked seasonality, with peak gonadosomatic indices during rising waters in most species, identifying a critical period for protection. Life-history strategies ranged from high-fecundity periodic strategists to low-fecundity equilibrium species, implying differentiated vulnerability to harvesting. Community perceptions prioritized large migratory catfish and floodplain habitats, aligning with biological indicators of vulnerability. High performance in technical training demonstrated the feasibility of long-term local monitoring systems. By linking biological indicators with local ecological knowledge, this study proposes a pathway from baseline assessment to adaptive co-management. The framework presented here provides a transferable model for strengthening sustainability, governance, and food security in tropical small-scale fisheries facing persistent data limitations. Full article

Edible insects have emerged as a sustainable source of high-quality proteins, lipids, and carbohydrates (including chitin), as well as micronutrients such as minerals and vitamins, and diverse bioactive compounds, thereby making them promising ingredients for functional food applications. Their favourable nutritional profile and low environmental footprint make them attractive ingredients for next-generation food systems. However, processing and preservation remain critical challenges, particularly with respect to the stability of bioactive compounds, lipid oxidation, and protein functional properties such as solubility, emulsifying capacity, and water-holding capacity. This review critically examines recent advances in food processing technologies applied to edible insects, including drying, extraction, fermentation, and microencapsulation, with emphasis on their effects on bioactive compound retention and functional performance. The role of processing strategies in enhancing oxidative stability, protein solubility, emulsifying properties, and overall technological applicability is discussed, alongside safety, regulatory, and consumer acceptance considerations. Overall, this review highlights key technological pathways for the effective valorisation of insect-derived ingredients and outlines future directions for their integration into sustainable and functional food products. In contrast to previous reviews, this work provides a comparative and mechanism-oriented analysis of processing methods, highlighting inconsistencies across studies and identifying key technological trade-offs. Particular attention is given to the relationship between processing parameters and the stability of bioactive compounds. Full article

In contemporary debates on the United Nations Sustainable Development Goals, there is growing recognition that artificial intelligence (AI) may contribute meaningfully to SDG 2 (Zero Hunger), particularly by enhancing the efficiency of food aid distribution and resource allocation. However, such optimism must be critically situated within the broader institutional and ethical contexts in which AI operates. This study argues that the effectiveness of AI in conflict-affected settings is contingent not only on technical capacity but also on governance structures, ethical safeguards, and institutional trust, dimensions closely aligned with SDG 16 (Peace, Justice, and Strong Institutions). Using the Gaza Strip as a case study, this article demonstrates that AI-driven food assistance mechanisms may inadvertently reinforce structural vulnerabilities. Specifically, algorithmic targeting of aid risks deepening dependency, exacerbating digital exclusion, and weakening already fragile governance systems. The absence of robust data accountability frameworks further complicates these dynamics, raising concerns regarding transparency, fairness, and long-term sustainability. The findings caution against privileging technical efficiency at the expense of socio-political stability. Rather, they highlight that the sustainability of AI interventions in humanitarian contexts fundamentally depends on the credibility and legitimacy of institutions. Accordingly, this study proposes a conceptual model for AI in hunger relief and digital humanitarianism that integrates technical innovation with institutional accountability and social trust. This study presents a narrative review informed by structural searching that examines the influence of AI on food security interventions in fragile contexts. This analysis applies a combined ethical governance and sustainability lens to assess current applications and risks. This research advances a broader analytical framework that moves beyond purely technical interpretations of AI, emphasizing its role as a socio-political tool, through identifying five key pillars for sustainable AI governance: data sovereignty, algorithmic accountability, inclusive system design, community-led governance, and market integrity. Full article

Agrivoltaics (AV) has emerged as an integrated land-use innovation capable of simultaneously addressing food, energy, and water challenges, yet its systemic implications for farming system sustainability remain insufficiently synthesized. This review adopts a farming system dynamics perspective to examine how AV systems reorganize biophysical, ecological, and socio-economic interactions across agroecosystems. Drawing upon agroecological principles, pathways of sustainable intensification and ecological intensification, and resource-loop strategies in circular economy, we identify the key elements and cause-and-effect relationships that shape AV system performance. Evidence indicates that the co-location of photovoltaics (PV) structures and crop cultivation generates new system properties, altered light distribution, moderated microclimates, redistributed soil moisture, and diversified production functions that influence productivity, resource-use efficiency, ecological services, and farm resilience. Using causal loop analysis, we conceptualize four central feedback dynamics: (i) PV–crop trade-offs and spatial-sharing relationships; (ii) microclimate modifications and crop physiological responses; (iii) ecological performance and landscape-level interactions; and (iv) circularity loops connecting resource conservation, renewable-energy substitution, soil processes, and material flows. This feedback collectively determines eco-efficiency outcomes, including enhanced land-equivalent productivity, improved water-use efficiency, strengthened regulating services, and reductions in external energy dependence. At the farming-system scale, AV diversifies income streams and stabilizes yields under climatic variability, whereas at the landscape scale, it fosters multifunctionality by supporting regenerative resource flows and ecological resilience. Building on these insights, we propose an integrated framework that links agroecological elements with dynamic feedback structures to guide context-specific AV design, management, and governance. This system-oriented synthesis provides a foundation for future research and policy efforts aimed at optimizing AV as a circular, resilient, and sustainable farming system innovation. Full article

Coconut milk-based Filipino foods provide a favorable environment for microbial growth and are highly susceptible to spoilage. Traditionally, spoilage in such foods has been assessed through subjective sensory evaluation, a method that often lacks consistency and accuracy. The present study introduces an electronic nose system employing Support Vector Machine (SVM) algorithms to objectively and quantitatively determine spoilage in coconut milk-based Filipino foods, including Bicol Express, Ginataang Langka, Laing, Bilo-bilo, Maja Blanca, and Ginumis. The developed system integrates six MQ gas sensors connected to an Arduino Nano and a Raspberry Pi 4B to detect and process volatile organic compounds emitted from the foods. The SVM algorithm was selected for its effectiveness in high-dimensional spaces and its ability to construct a binary classifier capable of distinguishing between spoiled and fresh samples. Dimensionality reduction in sensor data was achieved using Principal Component Analysis, which further enhanced classifier performance. System evaluation results demonstrated a high classification accuracy of approximately 98.95%, indicating the robustness of the proposed approach. The utilization of this technology offers significant benefits, not only for individuals with impaired olfactory function but also for the food industry, providing a reliable tool for food quality control and safety. Moreover, the outcomes suggest broader applicability to other perishable food products, with potential contributions to improved global food safety and storage practices. Full article

This study was designed to evaluate and explore the ecosystem-based adaptation practices for climate resilience with evidence from smallholder farmers’ perceptions of co-benefits and adoption decisions in Mabalane district, Mozambique. Ecosystem-based adaptation practice emerged as a sustainable approach to enhance rainfed smallholder farmers’ climate resilience while delivering multiple social, economic and environmental co-benefits. This study evaluated and explored the perceived co-benefits from adopting ecosystem-based adaptation practices and examined how they shape adoption decisions among the rainfed smallholder farmers. A mixed-method approach was employed, combining a household survey of 360 farm household heads, key informant interviews and focus group discussions. The main findings of the study revealed mixed cropping (83.9%), integrated crop-livestock (57.2%), and mulch tillage (51.1%) as the most adopted practices, as well as smallholder farmers perceiving multiple ecological and socio-economical co-benefits from adopting ecosystem-based adaptation practices. Although the study confirmed statistically significant relationships between ecosystem-based adaptation practices and the perceived co-benefits, none of the perceived co-benefits were significantly associated with an increase in the number of the adopted practices. Therefore, it is concluded that adoption decisions among smallholder farmers are not shaped by perceived ancillary benefits from ecosystem-based adaptation practices alone, but a combination of enabling conditions and resources endowments. Full article

Aflatoxin B₁ (AFB₁) is a highly stable mycotoxin that can persist during conventional food processing and therefore poses a serious risk to food and feed safety. In this study, two enzymes (CotA and Prx) were heterologously expressed in Bacillus subtilis, purified by Ni–NTA affinity chromatography, and evaluated for their ability to degrade AFB₁. Both enzymes exhibited remarkable thermostability and distinct catalytic optima. CotA exhibited its highest activity at 80 °C with an AFB₁ removal of 38.4%, whereas Prx showed its highest activity at 90 °C with a removal of 82.6%. The optimal pH values were near neutral, with CotA performing best at pH 7.0 and Prx at pH 7.5, and both reactions approached maximal conversion within approximately 10 h. When the two enzymes were combined, a clear cooperative effect was observed. The mixed system achieved 91.0% AFB₁ removal at 80 °C after 10 h, with the best degradation activity occurring at a CotA to Prx ratio of 1:3. At 50 °C, neither enzyme alone caused appreciable AFB₁ degradation, but the addition of hydrogen peroxide markedly enhanced catalytic activity. Both enzymes also retained substantial activity after boiling and autoclaving. In a maize flour model, the mixed-enzyme system showed strong AFB₁ degradation capacity, and peroxide-assisted treatment further improved activity. These results establish a thermostable and peroxide-responsive enzymatic platform for AFB₁ degradation and support future development of enzyme-based detoxification strategies for food and feed applications. Product identification and toxicological validation will be needed to confirm the safety of the treated products. Full article

The efficient on-demand generation of ClO₂ is critical for disinfection and food preservation. However, the development of safe and efficient strategies for gaseous ClO₂ production remains challenging. Herein, we report a stable and efficient electrochemical system for ClO₂ production based on rutile TiO₂ nanorod arrays (TiO₂ NAs). Electrochemical optimization suggests that a cathodic potential of −0.10 V (vs. Ag/AgCl) in an electrolyte solution of 1 M NaClO₃ with 5 M H₂SO₄ achieves the highest ClO₂ production efficiency. Mechanistic studies reveal that ClO₂ generation proceeds via an O₂-induced pathway, in which electrochemically generated H₂O₂ from 2-e⁻ O₂ reduction reacts in situ with ClO₃⁻ to form ClO₂, eliminating the need for external H₂O₂ storage and significantly improving operational safety. Furthermore, when decorated with RuO_x nanoparticles, TiO₂ NA cathodes achieve enhanced catalytic performance and excellent stability. In addition, the generated ClO₂ in the electrolyte solution can be delivered via gas pumping. This ClO₂ atmosphere exhibits antibacterial efficiencies exceeding 99% against Escherichia coli and Staphylococcus aureus, and significantly reduced weight loss and preserved fruit hardness in longan samples during 8 days of storage. Overall, this work presents a safe, efficient approach for ClO₂ generation with strong potential for practical disinfection in the food preservation field. Full article

Soil salinization impacts over one billion hectares, threatening global food security. Here, a salt-tolerant bacterial strain, Pseudomonas fluorescens G3, was isolated from the rhizosphere of maize (Jinongyu-719) growing in saline–alkali soils in Gansu Province, China. This strain demonstrated the ability to secrete indole-3-acetic acid (IAA), 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase, and extracellular polysaccharides. It also exhibited notable phosphate-solubilizing activity and robust siderophore production capabilities. Under salt stress conditions (200 mM NaCl), the P. fluorescens G3 strain significantly improved maize’s growth parameters, namely its plant height, root length, and dry weight. Further, it enhanced antioxidant enzyme activity while reducing the accumulation of malondialdehyde (MDA), mitigating stress-induced oxidative damage. In P. fluorescens G3-inoculated plants, leaf and root Na⁺ contents decreased by 34.90% and 33.91%, while their K⁺ contents increased by 40.20% and 33.47%, respectively. Inoculation with P. fluorescens G3 enhanced taxonomic richness (ACE, Chao1) and evenness (Shannon, Simpson) in the rhizosphere bacterial community, leading to a significantly greater relative abundance of several bacterial genera: Pseudomonas, Methylophaga, Enhygromyxa, Desulfuromonas, and Devosia. These shifts in the microbial community composition suggest a potential restructuring of functional profiles, possibly enhancing processes beneficial to plant salt tolerance, such as ion homeostasis and stress mitigation: the biosynthesis of cofactors and secondary metabolites; bacterial secretion and two-component systems; porphyrin metabolism; flagellar assembly; biofilm formation; and bacterial chemotaxis. Redundancy analysis revealed positive correlations between microbial composition at both the phylum and genus levels and the activity of stress resistance enzymes after treatment with Pseudomonas fluorescens. This study provides important theoretical foundations and microbial resources for utilizing microbial community regulation in saline–alkali soil bioremediation. Full article

Wheat processing generates large volumes of co-products, particularly wheat bran (WB) and wheat germ (WG), which remain underutilized despite their high content of dietary fiber, phenolic compounds, bioactive peptides, and lipophilic antioxidants. Although their composition and processing have been widely investigated, an integrated and application-oriented evaluation of these fractions remains limited. This review provides a structured and critical analysis of WB, raw and defatted WG, and wheat germ oil (WGO), linking composition, processing strategies, and functional performance within a unified framework. Conventional and emerging technologies, including enzymatic hydrolysis, fermentation, thermomechanical treatments, and supercritical CO₂ extraction, are discussed in terms of selectivity, impact on techno-functional properties, and scalability. An evidence-grading approach is introduced to distinguish bioactivities supported by chemical assays, cell-based models, animal studies, or human data, enabling a more rigorous interpretation of health-related effects. Across applications, these co-products have been incorporated into food systems and related sectors, primarily showing improvements in nutritional composition, oxidative stability, and product performance under experimental conditions. However, translation to an industrial scale remains constrained by techno-economic limitations, regulatory requirements, and stability challenges. This work highlights the need for integrated processing strategies aligned with industrial feasibility to support the development of sustainable cereal biorefineries. Full article

This paper investigates whether water-related climate stress predicts tail movements in food system assets and whether these spillovers vary across market regimes and investment horizons. Using daily data from January 2012 to January 2026, we examine the relationships among a water-risk proxy, agricultural commodities, agribusiness, and food supply-chain equities, and a fertilizer-related proxy. The analysis combines the cross-quantilogram with quantile spillover analysis in the frequency domain, allowing us to capture directional dependence in the tails of the distribution and short- and long-run connectedness. To account for structural change, we employ data-driven break detection and identify three major regimes: a pre-disruption period, a COVID-related adjustment phase, and a broader food system stress regime from early 2022 onward. The findings indicate that water-related climate stress has its strongest predictive power in the tails, especially for agribusiness and fertilizer-related assets, while the broad agricultural commodity basket is comparatively less sensitive. Lower-tail dependence is predominantly negative and often significant, whereas upper-tail dependence is generally positive, indicating asymmetric transmission under extreme market conditions. The spillover results further show that connectedness in the water–food system is mainly short-run, with agribusiness and fertilizer channels acting as the primary conduits of transmission. From a practical perspective, these findings suggest that investors and risk managers can use water-related market signals as early warning indicators of stress in food system assets, while policymakers can strengthen food system resilience through integrated water management, input market monitoring, and supply chain adaptation measures. The findings suggest that water-related climate stress is not merely an environmental constraint but a systemic source of food system risk with implications for resilience, risk monitoring, and integrated water-agriculture governance. Full article

The globalization of the food supply chain presents complex challenges for safety assurance within a highly fragmented regulatory landscape. This review synthesizes the frameworks of eight influential jurisdictions—including the European Union (EU), the United States, China, and Codex Alimentarius—to evaluate how legal mandates function as regulatory drivers that guide the evolution of analytical chemistry. By examining legislation on Maximum Residue Limits (MRLs), positive list systems, and method validation guidelines (e.g., SANTE), we demonstrate that strict preventive controls have established chromatography coupled with tandem mass spectrometry (LC/GC-MS/MS) as the universal standard for multi-residue screening. We show that global regulatory fragmentation is not merely an administrative artifact, but is rooted in divergent toxicological philosophies and localized dietary exposure models. This regulatory heterogeneity requires analytical laboratories to adopt a posture of “defensive technological redundancy,” forcing them to continuously optimize targeted methods against the strictest global default limits (e.g., 0.01 mg/kg). We establish that this continuous methodological escalation for ultra-trace quantification has reached practical and operational limits. Consequently, we conclude that the future of food safety testing must transition from static target-list compliance toward adaptable, non-targeted chemical profiling using High-Resolution Mass Spectrometry (HRMS), enabling laboratories to proactively address emerging contaminants, food fraud, and the complexities of modern food matrices. Full article

Accurate prediction of food consumption is essential for strengthening regional food security planning, particularly in areas experiencing increasing food demand and environmental uncertainty. This study aims to predict food consumption patterns in Sukabumi Regency, West Java, Indonesia, using an integrated artificial intelligence approach. The research combines the Adaptive Neuro-Fuzzy Inference System (ANFIS) for forecasting food consumption trends with three machine learning classification algorithms—Support Vector Machine (SVM), Random Forest (RF), and Logistic Regression (LR)—to classify food consumption levels. Historical rice consumption data from 2014 to 2024 were used to train the forecasting model and generate projections up to 2030. The ANFIS training process was conducted with 100 epochs and an error tolerance of 0, resulting in a training error value of 0.182, indicating strong model learning capability. The comparison between predicted and actual consumption values showed a prediction accuracy of 95.2%, demonstrating the reliability of the model in capturing consumption patterns. Furthermore, food consumption levels were classified into three categories: low, medium, and high. The classification results revealed that Random Forest achieved the most consistent performance across cross-validation folds, while SVM and Logistic Regression experienced misclassification in the medium consumption category. In several evaluation scenarios, machine learning models achieved accuracy levels up to 99.75%, precision 99.76%, recall 99.75%, and F1-score 99.75%. The integration of ANFIS forecasting and machine learning classification provides a robust analytical framework for understanding food consumption dynamics and supports data-driven policy formulation aimed at strengthening regional food security in Sukabumi Regency. Full article

Background/Objectives: The human gastrointestinal tract is a dynamic and interactive micro-ecosystem, with its distinct microbial population residing in the gut. The healthy condition of the gut is integrated into the normal functioning of all physiological activities. The gut microbiome is critical for the functioning of metabolism via several gut-axis connections with different systems in the human body; thus, it affects the status of health and general well-being. The fundamental physiology and homeostatic shifts are associated with specific diseases caused by a disrupted balance in the diversity of the gut microbiome, which could be due to a condition of dysbiosis in a host, instigated by several reasons. Some studies have been conducted on the selective isolation of probiotic species from dairy and other food sources to obtain effective probiotic strains, which have been studied and used by dietary intake strategies to restore gut microbial diversity, which is disturbed by some disease/s. Methods: Our search strategy included specific keywords—gut, microbiota, microbiome, disease, dysbiosis, probiotic bacteria and yeast—and was based on a timeframe of 15 years in the web-based electronic databases of PubMed, Scopus, and Web of Science. Among the few hundred results, a secondary screening was conducted to select references on probiotics studied for disease management with preclinical evidence and some reports on clinically validated outcomes; we excluded the search results for screening fermented foods for taxonomy studies of isolated probiotics. Results: The summarised information using two figures and two tables has been presented in this article from the review of 137 selected references: >75% have been published in the last 10 years. Conclusions: Further advances in modelling and analysis of the gut microbiota are required to understand their influence on the occurrence of certain diseases; this approach will allow us to establish research strategies for filling knowledge gaps, inconsistencies in clinical evidence, or limitations in translating probiotic effects from experimental models to humans. Full article

The valorization of citrus peel residues represents an important strategy for promoting circular bioeconomy approaches in the agri-food sector. This study evaluated the biorefinery potential of ten citrus varieties cultivated in Bolívar Province, Ecuador, including mandarin (Citrus reticulata criolla, Citrus nobilis Loureiro, Citrus tangerina, Citrus unshiu), lemon (Citrus aurantifolia Swingle, Citrus limonia, Citrus limonum, Citrus latifolia), and grapefruit (Citrus paradisi, Citrus paradisi Macfad.), focusing on the extraction and characterization of essential oils from peel biomass. The residual biomass was characterized through proximate and elemental analyses to determine its physicochemical properties, and essential oils were extracted under two maceration times (8 and 12 h) to evaluate the influence of extraction conditions on yield. Chemical composition was determined by gas chromatography–mass spectrometry (GC-MS). The results revealed significant variability among varieties in moisture, ash, and volatile solids content. Citrus nobilis Loureiro showed the highest extraction yield, while grapefruit varieties exhibited the greatest increase in yield with extended maceration time. Limonene was identified as the predominant compound in all essential oils, reaching concentrations above 90% in grapefruit samples, and significant intervarietal differences in monoterpene profiles were observed. Extraction kinetics were evaluated using seven mathematical models, among which the Monod model showed the best fit to the experimental data (R² > 0.99), demonstrating strong predictive capability. These findings highlight the potential of citrus peel residues as sustainable sources of high-value essential oils and provide a quantitative framework for optimizing extraction processes within citrus biorefinery systems. Full article