Search Results (3,413)

Climate extremes threaten the resilience of Eucalyptus plantations, yet hybridization with drought-tolerant species may enhance stress tolerance. This study analyzed xylem anatomical and functional drought responses in commercial Eucalyptus grandis (GG) clones and hybrids: E. grandis × camaldulensis (GC), E. grandis × tereticornis (GT), and E. grandis × urophylla (GU1, GU2). We evaluated vessel traits (water transport), fibers (mechanical support), and wood density (D) in stems and branches. Theoretical stem hydraulic conductivity (k_Stheo), vessel lumen fraction (F), vessel composition (S), and associations with previous hydraulic and growth data were assessed. While general drought responses occurred, GC had the most distinct xylem profile. This may explain it having the highest performance in different irrigation conditions. Red gum hybrids (GC, GT) maintained k_Stheo under drought, with stable F and a narrower vessel size, especially in branches. Conversely, GG and GU2 reduced F and S; and stem k_Stheo declined for a similar F in these clones, indicating vascular reconfiguration aligning the stem with the branch xylem. Almost all clones increased D under drought in any organ, with the highest increase in red gum hybrids. These results reveal diverse anatomical adjustments to drought among clones, partially explaining their growth responses. Full article

Effective flood management in agricultural fields has become increasingly important due to the rising frequency and intensity of rainfall events driven by climate change. This study investigates the applicability of urban flood analysis models—SWMM (1D) and K-Flood (2D)—to irrigated agricultural fields with artificial drainage systems. A case study was conducted in a rural area near the Sindae drainage station in Cheongju, South Korea, using rainfall data from an extreme weather event in 2017. The models simulated inland flooding and were validated against flood trace maps provided by the Ministry of the Interior and Safety (MOIS). Receiver Operating Characteristic (ROC) analysis showed a true positive rate of 0.565, a false positive rate of 0.21, and an overall accuracy of 0.731, indicating reasonable agreement with observed inundation. Scenario analyses were also conducted to assess the effectiveness of three improvement strategies: reducing the Manning coefficient, increasing pump station capacity, and widening drainage channels. Among them, increasing pump capacity most effectively reduced flood volume, while channel widening had the greatest impact on reducing flood extent. These findings demonstrate the potential of urban flood models for application in agricultural contexts and support data-driven planning for rural flood mitigation. Full article

Agricultural production in southern Angola faces challenges due to unsustainable practices, including inefficient use of water, fertilizers, and machinery, resulting in low yields and environmental degradation. Therefore, clear and measurable indicators are needed to guide farmers toward more sustainable practices. The scientific literature insufficiently addresses this issue, leaving a significant gap in the evaluation of key performance indicators (KPIs) that can guide good agricultural practices (GAPs) adapted to the context of southern Angola, with the goal of promoting a more resilient and sustainable agricultural sector. So, the objective of this study is to identify and assess KPIs capable of supporting the selection of GAPs suitable for maize, potato, and tomato cultivation in the context of southern Angolan agriculture. A systematic literature review (SLR) was conducted, screening 2720 articles and selecting 14 studies that met defined inclusion criteria. Five KPIs were identified as the most relevant: gross margin, net profit, water use efficiency, nitrogen use efficiency, and machine energy. These indicators were analyzed and standardized to evaluate their contribution to sustainability across different GAPs. Results show that organic fertilizers are the most sustainable option for maize, drip irrigation for potatoes, and crop rotation for tomatoes in southern Angola because of their efficiency in low-resource environments. A clear, simple, and effective representation of the KPIs was developed to be useful in communicating to farmers and policy makers on the selection of the best GAPs in the cultivation of different crops. The study proposes a validated KPI-based methodology for assessing sustainable agricultural practices in developing regions such as southern Angola, aiming to lead to greater self-sufficiency and economic stability in this sector. Full article

Camellia oleifera, a woody oilseed species endemic to China, often experiences growth constraints due to seasonal drought. This study investigates the coordinated regulation of photosynthetic traits, stomatal behavior, and hormone responses during drought–rehydration cycles in two cultivars with contrasting drought resistance: ‘CL53’ (tolerant) and ‘CL40’ (sensitive). Photosynthetic inhibition resulted from both stomatal and non-stomatal limitations, with cultivar-specific differences. After 28 days of drought, the net photosynthetic rate (P_n) declined by 26.6% in CL53 and 32.6% in CL40. A stable intercellular CO₂ concentration (C_i) in CL53 indicated superior mesophyll integrity and antioxidant capacity. CL53 showed rapid P_n recovery and photosynthetic compensation post-rehydration, in contrast to CL40. Drought triggered extensive stomatal closure; >98% reopened upon rehydration, though the total stomatal pore area remained reduced. Abscisic acid (ABA) accumulation was greater in CL40, contributing to stomatal closure and P_n suppression. CL53 exhibited faster ABA degradation and gibberellin (GA₃) recovery, promoting photosynthetic restoration. ABA negatively correlated with P_n, transpiration rate (T_r), stomatal conductance (G_s), and C_i, but positively with stomatal limitation (L_s). Water use efficiency (WUE) displayed a parabolic response to ABA, differing by cultivar. This integrative analysis highlights a coordinated photosynthesis–stomata–hormone network underlying drought adaptation and informs selection strategies for drought-resilient cultivars and precision irrigation. Full article

This study investigates the effects of low nitrogen (N) and phosphorus (P) stress on the growth and yield of nine barley (Hordeum vulgare L.) genotypes (1267-2, 1749-1, 1149-3, 2017Y-2, 2017Y-16, 2017Y-17, 2017Y-18, 2017Y-19, and XBZ17-1-61), all of which are spring two-rowed hulled barley types from the Economic Crops and Beer Material Institute, Gansu Academy of Agricultural Sciences. Data were collected over two consecutive growing seasons (2021–2022) at Huangyang Town (altitude 1766 m, irrigated desert soil with 1.71% organic matter, 1.00 g·kg⁻¹ total N, 0.87 g·kg⁻¹ total P in 0–20 cm plough layer) to elucidate the correlation between stress tolerance traits and yield performance. Field experiments were conducted under two treatment conditions: no fertilization (NP0) and normal fertilization (180 kg·hm⁻² N and P, NP180). Growth indicators (plant height, spike length, spikelets per unit area, etc.) and quality indicators (proportion of plump/shrunken grains, 1000-grain weight, protein, starch content) were measured, and data were analyzed using correlation analysis, principal component analysis, and structural equation modeling. The results revealed that low N and P stress significantly impacted quality indicators, such as the proportion of plump and shrunken grains, while having a minimal effect on growth indicators like plant height and spike length. Notably, the number of spikelets per unit area emerged as a critical factor positively influencing yield. Among the tested genotypes, 1749-1, 1267-2, 1149-3, 2017Y-16, 2017Y-18, 2017Y-19, and XBZ17-1-61 exhibited superior yield performance under low N and P stress conditions, indicating their potential for breeding programs focused on stress resilience. Included among these, the 1749-1 line showed the best overall performance and consistent results across both years. Full article

Cultivated land quality is a key factor in ensuring sustainable agricultural development. Exploring differences in cultivated land quality under distinct cropping systems is essential for developing targeted improvement strategies. This study takes place in Shenyang City—located in the typical black soil region of Northeast China—as a case area to construct a cultivated land quality evaluation system comprising 13 indicators, including organic matter, effective soil layer thickness, and texture configuration. A minimum data set (MDS) was separately extracted for paddy and upland fields using principal component analysis (PCA) to conduct a comprehensive evaluation of cultivated land quality. Additionally, an obstacle degree model was employed to identify the limiting factors and quantify their impact. The results indicated the following. (1) Both MDSs consisted of seven indicators, among which five were common: ≥10 °C accumulated temperature, available phosphorus, arable layer thickness, irrigation capacity, and organic matter. Parent material and effective soil layer thickness were unique to paddy fields, while landform type and soil texture were unique to upland fields. (2) The cultivated land quality index (CQI) values at the sampling point level showed no significant difference between paddy (0.603) and upland (0.608) fields. However, their spatial distributions diverged significantly; paddy fields were dominated by high-grade land (Grades I and II) clustered in southern areas, whereas uplands were primarily of medium quality (Grades III and IV), with broader spatial coverage. (3) Major constraint factors for paddy fields were effective soil layer thickness (21.07%) and arable layer thickness (22.29%). For upland fields, the dominant constraints were arable layer thickness (27.57%), organic matter (25.40%), and ≥10 °C accumulated temperature (23.28%). Available phosphorus and ≥10 °C accumulated temperature were identified as shared constraint factors affecting quality classification in both systems. In summary, cultivated land quality under different cropping systems is influenced by distinct limiting factors. The construction of cropping-system-specific MDSs effectively improves the efficiency and accuracy of cultivated land quality assessment, offering theoretical and methodological support for land resource management in the black soil regions of China. Full article

To improve the identification of drought-affected areas in winter wheat, this paper proposes a lightweight network called MF-FusionNet based on multimodal fusion of RGB images and vegetation indices (NDVI and EVI). A multimodal dataset covering various drought levels in winter wheat was constructed. To enable deep fusion of modalities, a Lightweight Multimodal Fusion Block (LMFB) was designed, and a Dual-Coordinate Attention Feature Extraction module (DCAFE) was introduced to enhance semantic feature representation and improve drought region identification. To address differences in scale and semantics across network layers, a Cross-Stage Feature Fusion Strategy (CFFS) was proposed to integrate multi-level features and enhance overall performance. The effectiveness of each module was validated through ablation experiments. Compared to traditional single-modal methods, MF-FusionNet achieved higher accuracy, recall, and F1-score—improved by 1.35%, 1.43%, and 1.29%, respectively—reaching 96.71%, 96.71%, and 96.64%. A basis for real-time monitoring and precise irrigation management under winter wheat drought stress was provided by this study. Full article

Field bindweed (Convolvulus arvensis L.) is a competitive herbaceous perennial weed that reduces productivity in irrigated pastures. Grazing might reduce competition by field bindweed when it begins growth in the spring, thereby encouraging encroachment by desirable grass species during the summer. To test this hypothesis, a two-year study was conducted in two adjacent, privately owned, irrigated, warm-season perennial grass pastures (replicates) that were heavily infested with field bindweed. Study sites were near Tucumcari, NM, USA. The fields were grazed with exclosures to evaluate ungrazed management. Aboveground biomass of field bindweed, other weeds, and perennial grass were measured, and field bindweed plants were counted in May of 2018 and 2019. There was no difference between years for any variable. Other weed biomass and field bindweed biomass and plant numbers were reduced (p < 0.05) by grazing (61.68 vs. 41.67 g bindweed biomass m⁻² for ungrazed and grazed management, respectively, and 108.5 and 56.8 bindweed plants m⁻² for ungrazed and grazed management, respectively). Otherwise, perennial grass production was unaffected by either year or management. These results indicate that grazing can be an effective tool to reduce field bindweed competition in warm-season perennial grass pastures. Full article

Traditional intensive agricultural system impedes ecological functions, such as nutrient cycling and biodiversity conservation, resulting in excessive nitrogen discharge, CH₄ emission, and ecosystem service losses. To enhance critical ecosystem services and mitigate environmental externalities in paddy fields, we developed a multi-objective agricultural system (MIA system), which combines two eco-functional units: paddy wetlands and Beitang (irrigation water collection pond). Pilot study results demonstrated that the MIA system enhanced biodiversity and inhibited pest outbreak, with only a marginal reduction in rice production compared with the control. Additionally, the paddy wetland effectively removed nitrogen, with removal rates of total nitrogen and dissolved inorganic nitrogen ranging from 0.06 to 0.65 g N m⁻² d⁻¹ and from 0.02 to 0.22 g N m⁻² d⁻¹, respectively. Continuous water flow in the paddy wetland reduced the CH₄ emission by 84.4% compared with the static water conditions. Furthermore, a simulation experiment indicated that tide flow was more effective in mitigating CH₄ emission, with a 68.3% reduction compared with the drying–wetting cycle treatment. The emergy evaluation demonstrated that the MIA system outperformed the ordinary paddy field when considering both critical ecosystem services and environmental externalities. The MIA system exhibited higher emergy self-sufficiency ratio, emergy yield ratio, and emergy sustainable index, along with a lower environmental load ratio. Additionally, the system required minimal transformation, thus a modest investment. By presenting the case of the MIA system, we provide a theoretical foundation for comprehensive management and assessment of agricultural ecosystems, highlighting its significant potential for widespread application. Full article

This study employs k-means clustering to analyze local organizations responsible for land improvement in Greece, identifying four distinct groups with consistent geographic patterns but divergent financial and operational characteristics. By integrating unsupervised machine learning with spatial analysis, the research offers a novel perspective on irrigation water pricing and cost recovery. The findings reveal that organizations located on islands, despite high water costs due to limited rainfall and geographic isolation, tend to achieve relatively strong financial performance, indicating the presence of adaptive mechanisms that could inform broader policy strategies. In contrast, organizations managing extensive irrigable land or large volumes of water frequently show poor cost recovery, challenging assumptions about economies of scale and revealing inefficiencies in pricing or governance structures. The spatial coherence of the clusters underscores the importance of geography in shaping institutional outcomes, reaffirming that environmental and locational factors can offer greater explanatory power than algorithmic models alone. This highlights the need for water management policies that move beyond uniform national strategies and instead reflect regional climatic, infrastructural, and economic variability. The study suggests several policy directions, including targeted infrastructure investment, locally calibrated water pricing models, and performance benchmarking based on successful organizational practices. Although grounded in the Greek context, the methodology and insights are transferable to other European and Mediterranean regions facing similar water governance challenges. Recognizing the limitations of the current analysis—including gaps in data consistency and the exclusion of socio-environmental indicators—the study advocates for future research incorporating broader variables and international comparative approaches. Ultimately, it supports a hybrid policy framework that combines data-driven analysis with spatial intelligence to promote sustainability, equity, and financial viability in agricultural water management. Full article

Understanding the carbon emission efficiency (CEE) of maize production and its determinants is critical to supporting China’s dual-carbon goals and advancing sustainable agriculture. This study employs a super-efficiency slack-based measure model (SBM) to evaluate the CEE of five major maize-producing regions in China from 2001 to 2022. Kernel density estimation and the Dagum Gini coefficient are used to analyze spatiotemporal disparities, while a geographically and temporally weighted regression (GTWR) model explores the underlying drivers. Results indicate that the national average maize CEE was 0.86, exhibiting a “W-shaped” fluctuation with turning points in 2009 and 2016. From 2001 to 2015, the Southwestern Mountainous Region led with an average efficiency of 0.76. Post-2015, the Northern Spring Maize Region emerged as the most efficient area, reaching 0.90. Efficiency levels have generally become more concentrated across regions, though the Southern Hilly and Northwest Irrigated Regions showed higher volatility. Inter-regional differences were the primary source of overall CEE disparity, with an average annual contribution of 46.66%, largely driven by the efficiency gap between the Northwest Irrigated Region and other areas. Spatial heterogeneity was evident in the impact of key factors. Agricultural mechanization, cropping structure, and environmental regulation exhibited region-specific effects. Rural economic development and agricultural fiscal support were positively associated with CEE, while urbanization had a negative correlation. These findings provide a theoretical foundation and policy reference for region-specific emission reduction strategies and the green transition of maize production in China. Full article

Remote sensing tools have been proposed to assist with rice crop monitoring but have been developed and validated on ponded rice. This two-year study was conducted on a commercial rice farm with irrigation automation technology aimed to (i) understand how canopy reflectance differs between high-yielding ponded and aerobic rice, (ii) validate the feasibility of using the squared simplified canopy chlorophyll content index (SCCCI²) for N uptake estimates, and (iii) explore the SCCCI² and similar chlorophyll-sensitive indices for grain quality monitoring. Multispectral images were collected from an unmanned aerial vehicle during both rice-growing seasons. Above-ground biomass and nitrogen (N) uptake were measured at panicle initiation (PI). The performance of single-vegetation-index models in estimating rice N uptake, as previously published, was assessed. Yield and grain quality were determined at harvest. Results showed that canopy reflectance in the visible and near-infrared regions differed between aerobic and ponded rice early in the growing season. Chlorophyll-sensitive indices showed lower values in aerobic rice than in the ponded rice at PI, despite having similar yields at harvest. The SCCCI² model (RMSE = 20.52, Bias = −6.21 Kg N ha⁻¹, and MAPE = 11.95%) outperformed other models assessed. The SCCCI², squared normalized difference red edge index, and chlorophyll green index correlated at PI with the percentage of cracked grain, immature grain, and quality score, suggesting that grain milling quality parameters could be associated with N uptake at PI. This study highlights canopy reflectance differences between high-yielding aerobic (averaging 15 Mg ha⁻¹) and ponded rice at key phenological stages and confirms the validity of a single-vegetation-index model based on the SCCCI² for N uptake estimates in ponded and non-ponded rice crops. Full article

The Po valley (northern Italy) is the leading European region for processing tomato (Solanum lycopersicum L.) production. Although historically characterized by abundant water availability, this area is now increasingly affected by drought risk. This study presents a two-year evaluation of regulated deficit irrigation (RDI) on processing tomatoes in northern Italy. In 2019 (Parma) and 2022 (Piacenza), full irrigation (IRR, restoring 100% crop evapotranspiration) and RDI (100% IRR until the color-breaking stage, followed by 50% IRR) strategies were compared within a completely randomized block design. Overall, RDI resulted in a 25% reduction in water use without compromising yield, which was maintained through unchanged plant fertility and fruit size compared to IRR. Remote sensing data from PlanetScope imagery confirmed the absence of water stress in RDI-treated plants. Furthermore, increased soluble solids and dry matter contents under RDI suggest a physiological adaptation of processing tomatoes to late-season water deficit. Remarkably, environmental and economic sustainability indicators—namely water productivity and yield quality—were enhanced under RDI management. This study validates a simple, sustainable, and readily applicable irrigation approach for tomato cultivation in the Po valley. Future research should refine this method by investigating plant physiological responses to optimize water use in this key agricultural region. Full article

Rizhao Reservoir, Shandong Province, China, as a key regional water supply hub, provides water for domestic, industrial, and agricultural uses in and around Rizhao City by intercepting runoff, which plays a central role in guaranteeing water supply security and supporting regional development. This study systematically collected 66 surface water samples to elucidate the hydrochemical characteristics within the reservoir area, identify the principal influencing factors, and clarify the sources of dissolved ions, aiming to enhance the understanding of the prevailing water quality conditions. A systematic analysis of hydrochemical facies, solute provenance, and governing processes in the study area’s surface water was conducted, employing an integrated mathematical and statistical approach, comprising Piper trilinear diagrams, correlation analysis, and ionic ratios. Meanwhile, the entropy weight-based water quality index (EWQI) and irrigation water quality evaluation methods were employed to assess the surface water quality in the study area quantitatively. Analytical results demonstrate that the surface water system within the study area is classified as freshwater with circumneutral to slightly alkaline properties, predominantly characterized by Ca-HCO₃ and Ca-Mg-SO₄-Cl hydrochemical facies. The evolution of solute composition is principally governed by rock–water interactions, whereas anthropogenic influences and cation exchange processes exert comparatively minor control. Dissolved ions mostly originate from silicate rock weathering, carbonate rock dissolution, and sulfate mineral dissolution processes. Potability assessment via the entropy-weighted water quality index (EWQI) classifies surface waters in the study area as Grade I (Excellent), indicating compliance with drinking water criteria under defined boundary conditions. Irrigation suitability analysis confirms minimal secondary soil salinization risk during controlled agricultural application, with all samples meeting standards for direct irrigation use. Full article

To explore the feasibility of integrated deficit water-biogas slurry irrigation under indirect subsurface drip irrigation, three deficit irrigation levels (60%FC, 70%FC, and 80%FC; FC represents field capacity) were established during the three growth stages of tomatoes. The results indicated that biogas slurry irrigation treatments increased the soil organic matter content in the root zone and water use efficiency (WUE) and reduced soil pH. As the degree of deficit increased, the plant height and stem diameter of tomatoes decreased significantly (p < 0.05), particularly during the seedling and flowering-fruiting stages. A mild deficit during the seedling stage was beneficial for subsequent plant growth, yielding maximum leaf area (6871.42 cm² plant⁻¹). Moderate deficit treatment at the seedling stage maximized yield, which was 19.79% higher than the control treatment in 2020 and 19.22% higher in 2021. The WUE of severe deficit treatment at the maturity stage increased by 26.6% (2020) and 31.04% (2021) compared to the control treatment. Comprehensive evaluation using TOPSIS combined with the weighted method revealed that severe deficit treatment at the maturity stage provided the best comprehensive benefits for tomatoes. In summary, deficit irrigation at different growth stages positively influenced tomato growth, quality, and soil environment in response to water-biogas slurry irrigation. Full article