Search Results (22,578)

This paper develops a stochastic approach for designing and operating a hybrid renewable energy system (HRES) through stochastic co-optimization. A hybrid renewable energy system consisting of solar photovoltaic power, a battery, and a grid is considered as the energy source to supply irrigation demands. Wind generation is retained in the formulation as a candidate technology, and the optimization returns an effectively zero optimal wind capacity under the conditions examined. A multi-scenario approach addresses uncertainty in solar output and demand. The methodology optimizes HRES components for future uncertain climate scenarios. Irrigation demand has a strong daily cycle. For example, irrigation demand rises from 4–6 kW at night and early morning, reaching a maximum of 88 kW at hour 13. The PV system’s peak power matches the maximum irrigation demand. In total, the PV system provides around 430–440 kWh of energy. The grid imports 35–40 kWh of energy, yielding a PV-to-grid ratio of more than 10:1. Therefore, solar-dominant systems can reliably supply energy to support agricultural activities, particularly irrigation. This methodology can serve as a basis for sustainable irrigation planning under uncertainty. Full article

Sustainable agricultural planning requires predictive frameworks that can capture spatiotemporal variability, sustainability dynamics, and the potential outcomes of alternative management scenarios. The research proposes TSAFI-DT, a retrospectively validated, data-driven Digital Twin prototype integrating spatiotemporal data reconstruction, sustainability-state representation, hierarchical yield forecasting, counterfactual analysis, and scenario simulation. The framework operates on historical district-level APY observations and therefore represents a retrospective approximation of Digital Twin operation rather than a continuously synchronized cyber-physical agricultural Digital Twin. The Extended Regenerative Agriculture Index (eRAI) combines crop diversity, productivity–stability, land-use efficiency, and yield-trend information to characterize district-level sustainability states. A Bayesian-optimized XGBoost model is employed for one-step-ahead yield forecasting under temporal validation, while fixed-effects and synthetic-control analyses provide complementary associational and intervention-associated evidence. Evaluation using district-level groundnut data from India during 1997–2023 demonstrates that the proposed predictor achieves an RMSE of 0.171 t/ha and $R^2=0.92$, outperforming the evaluated baselines with statistically significant differences ($p<0.05$). The fully adjusted fixed-effects model identifies a positive association between higher sustainability states and yield, while retrospective Digital Twin replay demonstrates close temporal agreement between predicted and observed outcomes. Model-based scenario simulations indicate predicted yield increases of up to 12.4% under the evaluated sustainability-state perturbations; these estimates represent counterfactual sensitivity rather than guaranteed causal effects. TSAFI-DT provides a reproducible framework for sustainability-aware agricultural forecasting, comparative scenario exploration, and data-driven decision support. Full article

The global environmental crisis has reached a critical point, demanding immediate action to address the pollution threatening ecosystem health. Terms such as “low-carbon agriculture,” “bioeconomy,” and “ecosystem services” are gaining prominence, reflecting the growing social appeal for solutions that minimize the impact of human activities on the planet. In this context, buffer strips emerge as an effective strategy to combat contamination of water and land resources. This study comprehensively analyzes these vegetative strips strategically positioned between pollution sources and water bodies, highlighting their evolution, functions, and effectiveness in pollutant mitigation. Initially, buffer strips were designed to reduce soil erosion and preserve water quality in agricultural areas. However, subsequent studies have expanded their role to include biodiversity promotion, pollutant mitigation, and application in urban environments. This shift reflects a growing awareness of environmental issues and the urgency of sustainable solutions, underscoring the importance of vegetative strips in environmental management and the continuous need for research and innovation. Full article

Black soybean is a high-value alternative crop that can offset declining yellow soybean prices in Thailand. Currently, “Sukhothai3” is the only commercial variety produced through conventional breeding over the past three decades. Its low first-pod height (FPH) limits mechanized harvesting and reduces production efficiency. Recently developed elite RILs have shown improved FPH, grain yield, and protein content (34.88–41.22%), but their yield stability and adaptability across environments remain unevaluated. This information is essential for establishing an effective bi-directional seed rotation system while maintaining seed quality, quantity, and genetic purity. This study evaluated five black soybean RILs across eleven trial environments in the major production zones of Northeast Thailand, where the tropical savanna climate poses significant constraints on crop production. Field experiments used a randomized complete block design with four replications per location. Yield stability and adaptability were assessed using AMMI1 and GGE biplot analyses. BSCM41 emerged as the most stable and widely adaptable genotype, consistently outperforming the commercial check across environments and seasons. It exhibited adequate FPH for mechanized harvesting (>10 cm), rapid vegetative development, and short growth duration (88–91 days), reducing exposure to late-season heat stress and excessive rainfall. Higher seeds per pod, greater 100-seed weight, and a superior harvest index further support yield formation under marginal conditions. BSCM41 maintained high yields in both dry and rainy seasons (1524.73 and 1633.26 kg/ha, respectively), meeting the requirements for an efficient bi-directional seed rotation system. These findings can inform future breeding strategies and production management in comparable tropical environments. Full article

This study reports novel bilayer active packaging films based on corona-treated low-density polyethylene (LDPE) coated with gelatin/glycerol (Gel/Gl) incorporating eugenol@natural zeolite (EG@NZ) or carvacrol@natural zeolite (CV@NZ) nanohybrids. All Gel-based films demonstrated oxygen transmission rates below the instrument detection limit (<0.008 cc O₂/m²/day), overcoming the poor oxygen barrier of LDPE (1530 cc O₂/m²/day). CV@NZ films exhibited strong diffusible antimicrobial activity against Staphylococcus aureus (18–20 mm inhibition zones) and effectively reduced microbial growth in fresh ham during refrigerated storage (TVC < 3 log CFU/g for 28 days). The bilayer design enables recyclability through removal of the water-soluble Gel layer, allowing recovery of the LDPE substrate. Overall, the developed films combine improved oxygen barrier properties, tunable bioactivity, and compatibility with conventional processing methods. Full article

This review synthesizes recent regional applications of satellite, unmanned aerial vehicle (UAV), and hyperspectral/spectroradiometric remote sensing for vegetation cover discrimination, including crop and natural vegetation discrimination, plant disease and pest detection, and yield assessment. The reviewed evidence demonstrates complementary rather than universally superior capabilities among sensing platforms. Satellite observations provide repeated large-area monitoring but remain constrained by spatial resolution, cloud interference, and spectral mixing, whereas UAVs offer very-high-resolution and flexible field-scale observations at the expense of spatial coverage and greater acquisition and processing requirements. Hyperspectral and spectroradiometric approaches provide detailed spectral information for distinguishing subtle vegetation differences, but are limited by data complexity and operational scalability. The quantitative results reported in the reviewed studies illustrate this variability: satellite-based crop discrimination achieved approximately 90% overall accuracy with QuickBird and 81% overall accuracy (κ = 0.74) with Sentinel-2 at a 10 m resolution, while a UAV hyperspectral vegetation classification study achieved 94.5% accuracy. However, these values are not directly comparable because the vegetation targets, sensors, acquisition conditions, and analytical methods differed among studies. Recent evidence also indicates that the phenological timing, spectral band selection, spatial resolution, and representative training data strongly influence the discrimination performance, while the transfer of disease detection models from controlled experiments to operational field conditions remains a major challenge. By integrating evidence from satellite, UAV, and ground-based spectroradiometric approaches, this review provides a comprehensive framework for understanding the complementary capabilities of these technologies for vegetation cover discrimination and highlights their importance for improving vegetation monitoring, precision agriculture, and sustainable ecosystem management. Full article

Soil fertility quality is a key indicator of soil productivity and sustainable agricultural development. The Zhangye Oasis, a major Maize seed production base in northwestern China, has experienced significant impacts from intensive human activities on soil conditions. In this study, fuzzy mathematics and structural equation modeling (SEM) were employed to evaluate the fertility characteristics of farmland soils (0–20 cm) in this typical oasis region. Our results showed that the mean values of soil organic matter (SOM), available nitrogen (AN), available phosphorus (AP), available potassium (AK), and pH in Zhangye Oasis farmland were 17.98 g·kg⁻¹, 75.04 mg·kg⁻¹, 22.22 mg·kg⁻¹, 206.81 mg·kg⁻¹, and 8.25, respectively. SOM and AN exhibited pronounced spatial heterogeneity, particularly in farmlands near the oasis margins, where nutrient contents were relatively low. The mean soil fertility quality index (SFI) was 0.64, corresponding to Grade VI farmland quality at the national level. Soil fertility showed moderate spatial autocorrelation, decreasing from southeast to northwest. Significant differences (p < 0.05) were observed among soil types, with wind-sand soil (SFI = 0.48) exhibiting the lowest fertility. The SFI followed the following order: no obvious obstacle (0.67) > saline–alkali (0.59) > irrigated improved (0.57) > sandy farmland (0.48). Continuous Maize cropping reduced SFI by 26.32% compared with the Other—Oilseed crops/Grazing cropping system. Overall, the oasis farmland exhibited relatively low soil fertility, dominated by Grade VI–VII levels. Improving the fertility of continuously Maize-cropped and irrigation-improved farmlands within the constraints of local water resources is crucial for ensuring sustainable agricultural production in the Zhangye Oasis. Full article

Freshwater contamination has become a critical global challenge, driven by industrialization, urbanization, agriculture and climate change, threatening safe drinking water and sustainable development. This review synthesizes peer-reviewed literature identified through targeted searches of major bibliographic databases, including Scopus, Web of Science Core Collection and PubMed, with Google Scholar used as supplementary search tool, using contaminant- and technology-specific keywords. Conventional treatment processes, including coagulation–flocculation, sedimentation, filtration, adsorption, activated carbon, ion exchange and chemical disinfection, are critically evaluated alongside advanced technologies such as membrane filtration, reverse osmosis, nanofiltration, advanced oxidation processes (including photocatalysis), electrochemical treatment and nanotechnology-based systems, with emphasis on mechanisms, removal efficiency and operational limitations. Evidence indicates that adsorption-based technologies (GAC/PAC) achieve up to 97% removal of long-chain PFAS following advanced regeneration, coagulation–sedimentation removes up to 95% of microplastics, and precipitation-based processes achieve 70–99% removal of heavy metals, yet no single technology addresses the full contaminant spectrum across varying water quality conditions. Integrated multi-barrier systems combining conventional and advanced technologies therefore provide the most effective and sustainable approach for producing safe drinking water. The review also examines emerging trends, including smart water treatment systems, advanced functional materials, renewable energy integration, and circular water management and identifies key research gaps and priorities for cost-effective, energy-efficient and resilient purification technologies essential to global water security and supporting the achievement of Sustainable Development Goal 6 (Clean Water and Sanitation). Full article

Biological nitrogen fixation (BNF) is a key nitrogen source in paddy soils, yet its spatial variability remains poorly understood. In this study, we conducted a 90-day ¹⁵N₂ labeling experiment using soils from seven paddy fields in Zhejiang Province, China, to quantify total nitrogen fixation and fixed-N accumulation in soil layers and plant tissues and to characterize bacterial communities using the 16S rRNA gene sequencing method. Total BNF varied from 3.73 ± 0.39 to 9.95 ± 0.88 kg N ha⁻¹, with ZH4 showing an almost 2.7-fold greater BNF rate than ZH7, the site with the lowest BNF rate. Our results indicated that the subsurface layer (1–15 cm) was the predominant BNF zone, with a 6.5-fold greater soil N fixed rate and the strongest site dependent variation. Available molybdenum and organic matter were strongly correlated with total BNF (r = 0.879, p < 0.009), while bulk density and available manganese showed strong positive associations. Redundancy analysis showed that organic matter and available manganese jointly explained 60.1% of bacterial community variation. In comparison, the second model explained 64.4% of community variation and identified plant-fixed nitrogen as a significant explanatory variable. Overall, these findings indicate that bioavailability of micronutrients and subsurface processes influence BNF more strongly than microbial diversity alone. Full article

Peganum harmala L. is a xerophytic medicinal and aromatic plant of considerable ethnopharmacological importance, characterized by a rich diversity of β-carboline alkaloids, phenolic compounds, and essential oil constituents. Despite increasing scientific interest, current knowledge remains fragmented across phytochemistry, essential oils, extraction technologies, biological activities, and safety assessments. This review provides an integrated overview of the essential oil composition, extraction methods, analytical characterization, biological properties, toxicological considerations, and emerging applications of P. harmala. Particular emphasis is given to organ-specific chemical variability, geographical and environmental influences on volatile profiles, and the importance of standardized chemical characterization for reliable bioactivity evaluation. Conventional extraction methods, including hydrodistillation and steam distillation, are critically compared with emerging green technologies such as ultrasound-assisted, microwave-assisted, and supercritical CO₂ extraction. Advanced analytical tools, including GC-MS, LC-MS/MS, NMR, and chemometric approaches, are highlighted for comprehensive phytochemical profiling. Reported biological activities include antimicrobial, antifungal, antioxidant, anti-inflammatory, antidiabetic, anticancer, and agricultural effects, although their translation requires rigorous chemical standardization, mechanistic validation, and safety evaluation. Overall, this review emphasizes that the sustainable development of P. harmala should rely on quality-by-design strategies integrating botanical authentication, chemotyping, green extraction, and regulatory-oriented toxicological assessment. Full article

Material and energy flow models (MFEMs) are widely used to support life cycle assessment (LCA) and sustainability analyses; however, increasing system complexity often results in models that are difficult to structure, reuse, and adapt across analytical perspectives. This study proposes a structured design pattern framework for MFEMs aimed at improving model consistency, modularity, reusability, and multi-perspective applicability. A mixed-method research approach was applied, combining targeted literature review, practitioner questionnaires, expert interviews, and modelling experience to identify recurring modelling challenges and formalize reusable modelling solutions. The framework was evaluated through comparative case studies in mining, agricultural, and industrial systems. Results demonstrate improvements in structural clarity, model reusability, and the integration of environmental, economic, and social assessment perspectives within a single modelling environment. The findings further highlight the relevance of modular and reusable modelling structures for digital LCA, circular economy applications, and emerging sustainability assessment environments. Overall, the proposed framework contributes to advancing more interoperable, transparent, and digitally enabled material and energy flow modelling practices. Full article

Poultry feather waste, one of the major by-products of the poultry industry, represents an underutilized protein-rich biomass with significant potential for sustainable valorization within the circular bioeconomy. This narrative review examines recent advances in the use of poultry feathers as a renewable source of keratin for the development of keratin-based biomaterials. A structured literature search of original research articles published between 2015 and 2026 resulted in a final primary evidence map of 524 records, which was used to evaluate current knowledge on poultry feather management, keratin structure and properties, extraction technologies, and the development of feather-derived biomaterials. The reviewed literature indicates that keratin recovery can convert feather waste into higher-value materials, although its environmental performance depends on the extraction route, energy and chemical requirements, and comparison with established feather-management pathways. Recent advances highlight the potential of feather-derived keratin for biodegradable films, composites, hydrogels, coatings, packaging, biomedical, agricultural, and environmental applications. However, challenges remain regarding scalable extraction technologies, material performance, process standardization, and industrial implementation. This review provides a comprehensive overview of current research and identifies future directions for integrating poultry feather valorization into circular bioeconomy strategies, supporting resource efficiency and the development of sustainable bio-based materials. Full article

The Cherchen River Basin (CRB), a cryosphere-dependent endorheic basin in northwestern China, faces strong competition among agricultural, groundwater, and ecological water demands under pronounced seasonal runoff variability. This study integrates multi-source hydrological records, groundwater-resource assessment, sectoral water-use statistics, and groundwater-quality constraints to diagnose water-resource sustainability under 2020 reference-year conditions and develop an adaptive assessment-to-management framework. Total water supply was 471.85 million m³, of which surface water and groundwater contributed 77.3% and 22.6%, respectively. Agriculture accounted for 96.8% of socioeconomic water use, with an average irrigation application of 659 m³/mu and high-efficiency irrigation covering 41.1% of cropland. Groundwater abstraction reached 106.69 million m³, equivalent to approximately 72% of the estimated exploitable groundwater resource, indicating high groundwater dependence but not, by itself, long-term aquifer depletion. Annual gross water supply corresponded to approximately 47% of the estimated available water-resource base; because return flows were not consistently quantified, this value is treated as an annual water-resource utilization ratio rather than a formal WEI⁺. Benchmark calculations indicate that reducing mean irrigation application toward regional levels of 616–558 m³/mu could lower gross agricultural demand by approximately 27.8–65.4 million m³ yr⁻¹. Based on these diagnostics, we propose a four-stage framework comprising resource diagnosis, pressure identification, management prioritization, and adaptive implementation. Management measures beyond the irrigation benchmark scenarios are presented as policy options requiring monitoring and further hydrological, ecological, or economic evaluation rather than as predetermined outcomes. Full article

The transition toward sustainable agriculture requires innovative biostimulants that enhance crop performance while reducing reliance on synthetic agrochemical inputs, such as mineral fertilizers and chemical pesticides, including herbicides, insecticides, and fungicides. Microalgae have gained considerable attention as sustainable biostimulants due to their diverse biochemical composition, including primary metabolites, phenolic compounds, and phytohormones. This work examined how Chlorococcum sp. extract influences seed germination, early seedling development, pigment content, and biochemical composition of soybean (Glycine max L.). Biochemical characterization of the extract revealed it was rich in polyphenols and flavonoids. Seeds were treated with four concentrations (0.1–2 g L⁻¹) and compared to an untreated control. The extract significantly improved the final germination percentage, from 57% in the control to 70% (0.5 g L⁻¹) and 80% (1 and 2 g L⁻¹), with a similar trend observed for the seed vigor index. Radicle and hypocotyl lengths increased significantly. Results also showed that pigment levels increased, especially under the 0.5 g L⁻¹ treatment. Seedling biochemical parameters, including carbohydrates, proteins, reducing sugars, phenolic compounds, and DPPH radical-scavenging activity, increased under microalgal treatments. Overall, the findings highlight the potential of microalgae-derived biostimulants as renewable and environmentally friendly alternatives to conventional crop inputs, supporting more sustainable soybean production and contributing to the development of resilient and resource-efficient agricultural systems. Full article

Environmental nanomaterials (ENMs) are increasingly entering agroecosystems through industrial discharges, agricultural chemicals, nanotechnology, and atmospheric deposition. Consequently, a comprehensive understanding of their interactions with plants across growth stages is essential. This narrative review synthesizes current insights into nanomaterial uptake pathways, translocation dynamics, and intracellular trafficking from seed germination to reproductive maturity. It highlights the use of integrative multi-omics techniques, namely transcriptomics, proteomics, metabolomics, and epigenomics, to elucidate molecular reprogramming in response to ENMs exposure. The data indicates that nanomaterials can significantly affect seed vigor, root architecture, photosynthetic efficiency, and other yield-related traits through coordinated regulation of stress-responsive genes, antioxidant defense mechanisms, and phytohormonal signaling pathways. Furthermore, the review underscores the role of epigenetic modifications, including DNA methylation and histone remodeling, as critical regulatory layers that govern both transient and heritable plant responses to ENMs. Metabolomic remodeling, particularly the biosynthesis of secondary metabolites and redox-related pathways, represents the primary adaptive response linking molecular disturbances to phenotypic outcomes. This manuscript proposes a systems-level framework for evaluating nano–plant interactions, bridging nanoscale physicochemical properties with physiological and yield-level outcomes. Collectively, this integrative perspective aims to enhance mechanistic clarity, support the development of predictive and sustainable nanotechnology applications in agriculture, and identify critical gaps in long-term ecological and transgenerational assessments. Full article