Search Results (517)

The North China Plain is a core grain-producing region in China. Under the dual pressures of global warming and intensifying human activities, frequent agricultural droughts pose a serious threat to regional food security and sustainable agricultural development. Based on ERA5-Land root-zone soil-moisture data (1982–2022), this study constructed the Standardized Soil Moisture Index (SSMI) and applied an MMK trend test, Partial Wavelet Coherence (PWC), and sub-regional Pearson correlation to investigate drought evolution and driving mechanisms. Groundwater-level and effective-irrigated-area datasets were further incorporated to complement soil-moisture-based analysis and investigate the anthropogenic drivers behind drought variations. The results show that: (1) The regional-average SSMI showed a significant decreasing trend at a rate of −0.013 decade⁻¹ (p < 0.001), indicating the intensification of agricultural drought. Meanwhile, the SPEI presented a non-significant increasing trend of 0.145 × 10⁻² decade⁻¹ (p < 0.001), revealing the existence of hysteresis between the two drought types. Spring suffered the most severe drought, while drought is alleviated by precipitation replenishment in summer, which highlighted the association between seasonal differences and regional climatic characteristics. (2) Groundwater level (GW) is identified as the dominant explanatory factor for agricultural drought (POSC = 70.53%, AWC = 0.93), far exceeding precipitation (16.66%) and evapotranspiration (8.71%), which underscores the pivotal role of groundwater in regulating soil moisture. (3) The driving mechanisms of agricultural drought exhibit remarkable north–south differentiation: southern sub-regions are predominantly driven by meteorological factors, whereas northern sub-regions are closely associated with intensive groundwater irrigation. Anthropogenic groundwater over-extraction shows strong statistical associations with agricultural drought variability. Future work should combine groundwater dynamics, irrigation and crop phenology. These findings support refined drought early-warning and region-tailored mitigation for the North China Plain. Full article

Next-generation waste degradation and valorization technologies are increasingly developed as integrated platforms for pollutant removal, resource recovery, and circular manufacturing. This review critically evaluates degradation and valorization routes for liquid, organic solid, and inorganic/electronic waste streams from an engineering perspective. For liquid waste, advanced oxidation processes, photocatalysis, electrochemical oxidation, plasma treatment, and hybrid systems are assessed with emphasis on radical utilization, photon and electron efficiency, catalyst stability, byproduct formation, and reactor hydrodynamics. For organic solid waste, biological, thermochemical, catalytic, enzymatic, and mechanical pathways are compared for agricultural residues, textile waste, and industrial polymers, including fermentation, pyrolysis, hydrogenolysis, solvolysis, enzymatic depolymerization, and mechanical recycling. Their practical viability depends strongly on feed purity, product selectivity, monomer or fuel recovery, and the energy and separation requirements of downstream processing. For inorganic and electronic waste, hydrometallurgical, pyrometallurgical, biohydrometallurgical, and physical separation routes are examined for the recovery of critical metals, mineral phases, and non-metallic fractions. Industrially mature integrated flowsheets generally offer greater feed tolerance, whereas emerging selective routes provide improved recovery potential but remain constrained by reagent consumption, reaction rate, and scale. Across all waste classes, the review identifies reactor design, process intensification, reaction–separation integration, techno-economic analysis, and life-cycle assessment as essential tools for translating laboratory performance into scalable, economically competitive, and environmentally sustainable processes. Full article

Sustainable pasture management is essential for preserving ecosystem services and supporting livestock production in Mediterranean environments experiencing increasing land-use pressure and climate variability. This study evaluates grassland dynamics in South Lebanon between 2000 and 2024 using multi-temporal Landsat imagery integrated with Geographic Information Systems (GISs) and Random Forest classification. Historical Landsat surface reflectance products were processed using standardized preprocessing procedures, cross-sensor harmonization, and supervised classification. Classification accuracy was assessed using independent validation samples, yielding overall accuracy values ranging from 91.8% to 98.6% and Kappa coefficients between 0.918 and 0.975. Pasture areas were subsequently classified into dense and dispersed grasslands using quantitative NDVI thresholds. A pixel-based transition matrix was employed to quantify land-cover persistence, gains, losses, and conversions throughout the study period. The results reveal substantial spatial redistribution of grasslands associated with agricultural intensification and greenhouse expansion. FAO GIEWS NDVI and Vegetation Health Index products were incorporated only as regional environmental context. The resulting spatial database provides a robust framework for sustainable pasture planning, grazing management, and future land-use policy development in South Lebanon. Full article

The hilly agroecosystems of north-western Maharashtra harbor rich agrobiodiversity, but agricultural intensification and widespread adoption of improved cultivars are accelerating the erosion of traditional crop landraces. However, comprehensive information on the current status of on-farm agrobiodiversity and the extent of ongoing genetic erosion in these tribal-dominated landscapes remains limited. This study assessed on-farm agri-horticultural diversity, landrace prevalence, genetic erosion, and indigenous conservation practices across Akole, Igatpuri, Shahada, and Dhadgaon. Field surveys, household interviews, and focus group discussions documented traditional crop landraces, wild edible species, and farmer-led conservation practices. Agrobiodiversity was evaluated using the Prevalence Index, Berger–Parker Index, Menhinick’s Diversity Index, and Shannon Diversity Index. More than 150 traditional landraces representing cereals, millets, pulses, oilseeds, vegetables, fruits, and legumes, together with over 35 wild edible plant species, were recorded. Hyacinth bean (PI = 10.00), mango (PI = 5.35), groundnut (PI = 5.25) and wheat (PI = 4.17) showed the highest prevalence in Akole–Igatpuri, whereas cowpea (PI = 2.50) and pigeonpea (PI = 2.33) predominated in Shahada–Dhadgaon. Shannon diversity values ranged from 0.69 to 3.01 and 1.01 to 2.17, indicating substantial variation in landrace diversity. Community seed banks and farmer-managed seed systems continue to support the conservation of locally adapted landraces despite ongoing varietal replacement. This study provides a comprehensive baseline for understanding the status of on-farm agrobiodiversity in north-western Maharashtra. It highlights the importance of integrating indigenous knowledge with community-based and policy-driven conservation strategies to strengthen the long-term resilience and sustainability of traditional farming systems. Full article

Precision agriculture (PA) has emerged as a data-driven approach for improving maize (Zea mays L.) production through the integration of remote sensing, Geographic Information Systems (GISs), Global Navigation Satellite Systems (GNSSs), the Internet of Things (IoT), and machine learning (ML). This systematic review evaluates the application of PA for yield optimisation and resource-use efficiency in maize production between 2020 and 2026. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, 464 records were identified from Scopus and Web of Science, of which 129 studies met the inclusion criteria. The reviewed literature comprised field experiments (28.6%), remote sensing and PA integration studies (25.5%), machine learning applications (19.4%), climate-informed PA strategies (23.4%), and soil degradation studies (3.1%). Remote sensing and integrated multi-technology systems were the most extensively investigated approaches, followed by ML-based models for yield prediction and crop monitoring. Overall, PA technologies enhanced maize productivity, nutrient-use efficiency, water-use efficiency, and yield prediction accuracy through site-specific management and data-driven decision support. Despite its considerable potential, the adoption of PA remains constrained by high implementation costs, technical complexity, and limited data availability. Collectively, these findings demonstrate that precision agriculture provides an effective framework for sustainable maize intensification by improving productivity, optimising resource-use efficiency, and strengthening resilience to climate variability. Full article

The intensification of poultry production in Poland generates enormous quantities of excreta and associated biomass. While these constitute valuable sources of macro- and micronutrients, inadequate waste management leads to environmental pollution, nutrient leaching, and ammonia emissions. This paper analyses the fertilising potential of avian excreta, the legal provisions governing their application, and modern management technologies within the context of the circular economy. The study addresses two global threats—antimicrobial resistance (AMR) and the eutrophication of aquatic ecosystems—evaluating mitigation strategies and advanced biotechnological processing methods. Industrial farming turns excreta into a reservoir of active antibiotics, leading to the contamination of soils, waters, and crops. As a preventative strategy to reduce reliance on veterinary antibiotics—thereby indirectly mitigating the environmental dissemination of AMR—the dietary application of phytobiotics is highlighted. To counteract eutrophication, supplementing feed with exogenous microbial phytase plays a pivotal role, improving phytate phosphorus absorption and reducing its excretion by up to 50%. Furthermore, anaerobic co-digestion with carbon-rich substrates enhances methane yield, while advanced recovery systems (struvite precipitation, electrodialysis, bioelectrochemical concentration, and membrane techniques) show significant potential for safer nutrient concentration. An integrated technological approach to waste processing constitutes the foundation of sustainable agricultural production. Full article

Climate change imposes severe constraints on global food security, yet evidence on how crops respond to climate change in irrigation-dominated systems remains limited compared with rainfed agriculture. Building on this gap, we investigated how asymmetric climate shocks influence rice production in a major irrigated setting, using Egypt’s Nile Delta as a case study. Drawing on annual data for 1961–2022, we estimated a nonlinear autoregressive distributed lag (NARDL) model in which harvested area, fertilizer use, and seasonal temperature and precipitation jointly determine rice output, with structural-break tests used to inform model specification and the historical interpretation of major water and agricultural policy reforms. Temperature and precipitation are decomposed into cumulative positive and negative partial sums to isolate the effects of warming versus cooling and of rainfall surpluses versus deficits. The results showed a stable long-run cointegrating relationship with pronounced asymmetries. Autumn temperature shocks were most strongly associated with production variation, with cooling shocks more damaging than warming shocks were beneficial, while precipitation effects were asymmetric in the opposite direction: production gains associated with above average rainfall years exceeded the losses associated with below average rainfall years, consistent with irrigation buffering rainfall shortfalls. This finding does not rule out drainage-related losses from extreme, short-duration rainfall events, which the annual precipitation total used here cannot separately identify. Land expansion and fertilizer intensification remain positively associated with rice output, yet they only partially offset climate-induced losses, underscoring the limits of input-based adaptation amid increasing climatic volatility. Overall, the findings suggest that irrigation systems face distinct climate risks often obscured in symmetric models, highlighting adaptation priorities in drainage and storage, sustainable use of marginal lands, and season-specific climate services for irrigated rice regions. Full article

Drought is a complex and periodic issue that has a significant impact on agriculture and water resources, particularly in semi-arid areas. This study evaluated meteorological and agricultural drought conditions in the Thanjavur district by combining rainfall data with remote-sensing methods. Meteorological drought was analyzed using 33 years of rainfall data and the Standardized Precipitation Index (SPI) (1992–2024) using 20 rainfall stations for the data available between 1992 and 2024. The spatial variation in rainfall was analyzed using Kriging interpolation in GIS. Agricultural droughts were analyzed using the Normalized Difference Vegetation Index (NDVI) and Vegetation Con0dition Index (VCI) using multi-temporal Landsat satellite images (Landsat 5 and Landsat 8). Land Use and Land Cover (LULC) classification was included to determine drought vulnerability across different land types. The NDVI and VCI indices showed an intensification of agricultural drought in 2010. The results demonstrated temporal and spatial differences in drought conditions for the years 1992, 1997, 2004, 2009, 2014, 2019, and 2024 and indicated that the region experienced periodic severe drought conditions of 3%, 3%, 3%, 8%, 19%, 9%, and 11% in the study area, respectively. During the drought period, the vegetation indices showed a strong sensitivity of agricultural areas to changes in rainfall, and low NDVI and VCI values indicated increased vegetation stress. Meteorological and agricultural droughts were integrated using the Analytical Hierarchy Process (AHP) method by combining various indicators to analyze the drought condition across the Thanjavur district. The multiple criteria decision-making (MCDM) method uses pairwise comparisons of various factors, such as giving high importance to SPI and rainfall, followed by vegetation indices and LULC. The consistency ratio validated the reliability of the weighting term. This method shows that combining meteorological and remote sensing indicators advances a robust framework for monitoring and assessing droughts. Conceptual droughts illustrate how meteorological droughts are associated with the development of agricultural droughts. The results of this study can be adopted for effective drought management, irrigation planning, and sustainable agricultural practices in this region. Full article

Agricultural intensification has weakened natural pest regulation by reducing habitat resources for natural enemies and limiting plant-mediated resistance. Here, we conducted field experiments during 2024–2025 to evaluate the combined effects of Cnidium monnieri field-margin planting and maize seeds coated with the endophytic fungal strains YC (Beauveria bassiana) and PL (Purpureocillium lilacinum) on predator conservation, pest suppression, and biological control in maize agroecosystems. Compared with natural grass margins, C. monnieri significantly increased predator abundance, species richness, and Shannon diversity, particularly of ladybirds, minute pirate bugs, and spiders (p < 0.05). Gut-content analysis detected C. monnieri DNA in ladybirds collected 10–40 m from field margins, confirming predator resource use and spillover into maize fields. Importantly, endophytic fungus-coated seeds did not reduce predator abundance or diversity. Moreover, combining C. monnieri with endophytic fungi enhanced pest suppression and achieved control efficacy comparable to imidacloprid (p > 0.05). These findings demonstrate that integrating functional plants with endophytic fungi simultaneously strengthens top-down biological control and endophyte-associated bottom-up pest suppression, providing an effective and environmentally sustainable strategy for pest management in maize. Full article

India faces large, persistent yield gaps across eight major crops—wheat, rice, maize, soybean, pulses, mustard, cotton, and sugarcane—that collectively limit food security and rural income. This review synthesises evidence from over 100 peer-reviewed studies (1990–2024) to provide the first comprehensive, multi-crop, agro-climatically resolved yield gap analysis for India. Applying the three-tier framework of potential yield ($Y_p$), attainable yield ($Y_a$), and farmer yield ($Y_f$), exploitable yield gaps are quantified at national and agro-climatic zone level, ranked limiting factors are identified, and projected climate change impacts are assessed. Yield gaps range from 20 to 35% in irrigated rice of the north-western Indo-Gangetic Plain to 60–75% in rainfed cotton and pulses of the semi-arid tropics. Yield gaps of blackgram across 20 major districts average 515 kg ha⁻¹, driven by moisture stress, biotic pressure, and management constraints. Nitrogen management, irrigation access, variety adoption, and sowing-date optimisation collectively explain 80–85% of exploitable gaps, while nitrogen and irrigation alone account for 40–58%. Closing 50% of exploitable yield gaps could add approximately 100 million tonnes of food grain annually without expanding cultivated area, directly supporting Sustainable Development Goal (SDG 2). However, climate change is projected to widen yield gaps of rainfed rice by 15–30% by the 2040s under Representative Concentration Pathway (RCP) 8.5. Beyond this crop-by-crop synthesis, the review proposes a constraint-transition framework in which the dominant type of limiting factor shifts predictably from biophysical (water, climate) in the largest-gap rainfed systems to agronomic management (nitrogen, sowing date, variety) at intermediate gap levels and to institutional and socioeconomic constraints (credit, extension, land tenure, gender) as gaps narrow in the best-resourced irrigated systems, thus offering a conceptual lens for prioritising interventions by development stage rather than by crop alone. Full article

Romanian agricultural landscapes have undergone substantial transformation between 2000 and 2024, driven by agricultural modernization, market integration, and uneven regional development. This study assesses the opportunities and risks associated with these changes within a landscape-scale sustainability framework. Using 24 indicators describing land use, crop structure, productivity, mechanization, irrigation, input use, and socio-economic characteristics, we combined paired-sample t-tests, Principal Component Analysis (PCA), and cluster analysis to examine temporal and spatial patterns of agricultural transformation across Romanian counties. The results reveal significant increases in arable land, mechanization, labour productivity, and cereal yields, accompanied by declining agricultural employment and growing crop specialization. PCA identified six key dimensions of transformation, highlighting increasing differentiation between intensive, productivity-oriented systems and traditional agricultural structures. Cluster analysis revealed nine distinct agricultural typologies and increasing spatial polarization between highly modernized, input-intensive lowland systems and persistent grassland-based mountain agroecosystems. The comparison between 2000 and 2024 indicates stronger specialization, technological intensification, and territorial differentiation of agricultural systems. These changes create opportunities through improved labour productivity and efficiency, while also reflecting increasing landscape simplification and evolving agri-environmental management patterns. The findings emphasize the need for regionally differentiated policies that support agricultural competitiveness, territorial cohesion, and sustainable rural development. Full article

Agroecological approaches are increasingly recognized as sustainable alternatives to conventional weed management practices. This review examines the role of soybean, potato, and winter wheat as key crops within agroecological systems for effective weed suppression. Four management strategies—crop rotation, post-harvest mulching, optimized planting density (for soybean and potato), and varietal mixtures (for winter wheat)—are evaluated for their influence on weed dynamics and overall system performance. The synthesis of current studies indicates that these practices can significantly reduce weed pressure while enhancing soil health, biodiversity, and the provision of key ecosystem services, including provisioning, regulating, and supporting functions. In addition, these approaches contribute to improved crop productivity and reduced reliance on chemical inputs. Agroecological strategies also support pest regulation, water-use efficiency, and climate resilience, promoting more sustainable and resource-efficient agricultural systems. Despite these benefits, challenges related to farmer adoption, labor requirements, and limited policy support remain. Overall, this review highlights the potential of integrated agroecological practices to achieve sustainable agricultural intensification while balancing ecological sustainability with economic viability. Further research and supportive policy frameworks are needed to facilitate the wider implementation of these approaches across diverse agroecosystems. Full article

The agricultural and livestock sectors of Latin America produce a large number of residues that could be converted into energy through bioenergy production processes. However, the bioenergy sector still faces several limitations across the region, including fragmented logistics systems, weak coordination among institutions, and limited integration of environmental, digital, and compliance-related performance indicators. This review systematically analyses residue-based bioenergy value chains in Latin America between 2015 and 2025 using the PRISMA methodology to evaluate selected peer-reviewed studies and regional reports indexed in Scopus, ScienceDirect, SpringerLink, and IEEE Xplore, and institutional repositories. The final synthesis included 37 studies and institutional contributions, which were further disaggregated into 208 country–residue observations for the regional and feedstock distribution analysis. The review identified three main research gap categories: the limited integration of collection and logistics systems, the insufficient treatment of uncertainty, circularity, and traceability within optimization models, and the weak incorporation of governance and institutional coordination into bioenergy value-chain design. The analysis includes biogas, biomethane and related residue-based systems, with attention to supply-chain optimization, policy alignment, methane mitigation metrics, and traceability requirements. Results indicate that although technologies such as biomass pretreatment, process intensification, and upgrading processes continue to improve conversion performance, most studies still focus mainly on technical feasibility and biomass potential. Less attention is given to governance constraints, uncertainty analysis, and monitoring systems capable of supporting regulatory compliance. This research introduced the Sustainable Bioenergy Chain Management Framework (SBCMF) to respond to these limitations and bring together different aspects of bioenergy management within one analytical structure. The framework combines supply-chain optimization under spatial and temporal constraints, circular economy valorisation, methane-related climate performance, and digital traceability, while also linking techno-economic system design with governance and monitoring requirements. In this way, it can help support the development of more transparent and low-carbon bioenergy systems across Latin America. Full article

Understanding long-term changes in agricultural landscapes is essential for assessing the sustainability of land-use systems and guiding agro-environmental policy. This study analyzes three decades of landscape simplification and natural habitat complexity (1990–2018) across three spatial scales—Europe, Spain, and Extremadura—using CORINE Land Cover data and generalized additive models (GAMs). Four agricultural systems were examined: total agriculture, vineyards, olive groves, and rice fields. For each year and region, 1000 randomly selected 1 km buffers were used to quantify the proportions of focal crops and natural habitat as indicators of landscape simplification and complexity, respectively. Results showed that landscape simplification was widespread and statistically significant across most agricultural systems, particularly in Spanish vineyards (p = 3.02 × 10⁻⁵) and rice fields (p = 3.74 × 10⁻⁵). Temporal analyses indicated declining simplification trends in Europe and Spain (approximately −1.5%), whereas Extremadura exhibited increasing simplification (+1.5%) and a decline in landscape complexity after 2006. Landscape complexity showed fewer significant trends, with Europe and Spain displaying slight increases over time, whereas Extremadura shifted from initial complexity gains to a decline after 2006, indicating pressures from irrigation expansion and crop intensification. Overall, the results reveal marked spatial differences in agricultural landscape trajectories, demonstrating how intensification processes depend on crop type, regional context, and policy frameworks. This multi-scale analysis provides a quantitative basis for designing land-use policies that preserve ecological connectivity, promote diversification, and strengthen the long-term sustainability of agricultural landscapes. Full article

Pest pressure is a major constraint on crop production in Sub-Saharan Africa, where smallholder farmers rely heavily on synthetic pesticides with potential environmental and health risks. Ecological pest management practices (EPMs) have been proposed as sustainable alternatives, although field-based evidence is limited. This study evaluated pest and natural-enemy responses to EPMs in a cabbage–garden pea rotation system over six years (2020–2025) in Central Kenya. Four treatments were assessed: homemade botanical extracts (Botanicals), coriander intercropping (Intercrop), botanical extracts combined with coriander intercropping (Botanicals + Intercrop), and a control. In cabbage, ecological treatments often recorded lower aphid and diamondback moth abundance and damage than the Control, although these patterns were not consistently significant. Aphid cumulative abundance ranged from an Area Under Disease Progress Curve (AUDPC) of 128.0 under the Control to 47.5 under Botanicals + Intercrop, while DBM abundance ranged from 68.5 to 20.0. In garden pea, aphid damage ranged from an AUDPC of 39.3 under Intercrop to 25.1 under Botanicals + Intercrop, while cutworm damage ranged from 56.3 under Botanicals to 14.8 under Intercrop. Significant treatment effects were detected for selected pest responses. Shannon diversity differed significantly among the treatments in both crop phases. As such, responses were pest- and season-specific rather than uniformly suppressive. These findings identify companion cropping and botanical applications as promising components of EPM within the treatments evaluated. Comparison with conventional pesticide-based or farmer-practice management is however required before recommendations for substitution or wider adoption can be made. Full article