Search Results (1,082)

Climate change negatively affects agriculture, causing desertification, salinisation, and drought. The biochar hydroinfiltrator (ES Patent No.: ES2793448 B2) is a device that increases the capture of rainwater or irrigation water for crops by increasing infiltration rates. Biochar, produced via biomass pyrolysis, has emerged as a promising agricultural amendment, as it helps to optimise moisture retention and improve soil structure, key aspects for boosting crop yields. There is growing interest in microorganisms’ plant-growth-promoting activity (PGP) by carrying out different activities considered growth promoters. The aim of the present study is to evaluate the use of a biochar hydroinfiltrator as a promoter of microbial activity when it is used in soil. Metagenomic analysis of soils with and without the device reveals that genera Bacillus and Sphingomonas became particularly enriched in soils with hydroinfiltrators. Also, in order to understand the interaction between the uses of biochar together with bacteria PGP, an in vitro test was carried out. Two microorganisms, previously selected for their characteristics as plant growth promoters, were inoculated in soils with and without biochar and they grew better after 15 to 30 days of inoculation, showing major CFU counts. This combined strategy—biochar hydroinfiltrator and PGP bacteria—offers an innovative, eco-friendly approach to sustainable agriculture, particularly under drought stress. Full article

This study investigates the delineation of management zones (MZs) to support site-specific crop management by simplifying within-field variability in irrigated (54.6 ha) and rainfed (7.9 ha) sorghum and soybean fields in Brazil. Historical yield, apparent soil electrical conductivity (ECa) at 0.75 m and 1.50 m, and terrain data were analyzed using multivariate statistics to define MZs. Two clustering methods—fuzzy c-means (FCM) and hierarchical clustering—were compared for variance reduction effectiveness. Rainfed areas showed greater spatial variability (yield CV 9–12%; ECa CV 20–27%) than irrigated fields (yield CV < 7%; ECa CV ~5%). Principal component analysis (PCA) identified subsoil ECa and elevation as key variables in irrigated fields, while surface ECa and topography influenced rainfed variability. FCM produced more homogeneous zones with fewer classes, especially in irrigated fields, whereas hierarchical clustering better detected outliers but required more zones for similar variance reduction. Yield correlated strongly with slope and moisture in rainfed systems. These results emphasize aligning MZ delineation with production system characteristics—enabling variable rate irrigation in irrigated fields and promoting moisture conservation in rainfed systems. FCM is recommended for operational efficiency, while hierarchical clustering offers higher precision in complex contexts. Full article

Integrated rice–crayfish (Oryza sativa–Procambarus clarkii) co-culture (RC) systems have gained prominence due to their economic benefits and ecological sustainability; however, the interactions between soil properties and microbial communities in such systems remain poorly understood. This study evaluated the effects of the RC systems on soil physicochemical characteristics and microbial dynamics in paddy fields of southern Henan Province, China, over the 2023 growing season and subsequent fallow period. Using a randomized complete design, rice monoculture (RM, as the control) and RC treatments were compared across replicated plots. Soil and water samples were collected post-harvest and pre-transplanting to assess soil properties, extracellular enzyme activity, and microbial community structure. Results showed that RC significantly enhanced soil moisture by up to 30.2%, increased soil porosity by 9.6%, and nearly tripled soil organic carbon compared to RM. The RC system consistently elevated nitrogen (N), phosphorus (P), and potassium (K) throughout both the rice growth and fallow stages, indicating improved nutrient availability and retention. Elevated extracellular enzyme activities linked to carbon, N, and P cycling were observed under RC, with enzymatic stoichiometry revealing increased microbial nutrient limitation intensity and a shift toward P limitation. Microbial community composition was significantly altered under RC, showing increased biomass, a higher fungi-to-bacteria ratio, and greater relative abundance of Gram-positive bacteria, reflecting enhanced soil biodiversity and ecosystem resilience. Further analyses using the Mantel test and Random Forest identified extracellular enzyme activities, PLFAs, soil moisture, and bulk density as major factors shaping microbial communities. Redundancy analysis (RDA) confirmed that total potassium (TK), vector length (VL), soil pH, and total nitrogen (TN) were the strongest environmental predictors of microbial variation, jointly explaining 74.57% of the total variation. Our findings indicated that RC improves soil physicochemical conditions and microbial function, thereby supporting sustainable nutrient cycling and offering a promising, environmentally sound strategy for enhancing productivity and soil health in rice-based agro-ecosystems. Full article

The aim of this study was to evaluate the agronomic performance and physicochemical characteristics of broccoli grown under different doses and sources of special phosphorus (P) fertilizers and their residual effect on the soil, in Cerrado mineiro. A randomized block design arranged in a split-plot scheme was employed, where three P sources—T1 = Conventional monoammonium phosphate (CMP); T2 = Polymerized monoammonium phosphate (PCMP); T3 = Granulated organomineral fertilizer (GOF)—along with four P₂O₅ rates—1–0 (No P); 2–50% (200 kg ha⁻¹ P₂O₅); 3–75% (300 kg ha⁻¹ P₂O₅); and 4–100% (400 kg ha⁻¹ P₂O₅)—were assessed. Evaluations included the number of leaves (NL), head fresh (HFM) and dry mass (HDM), yield (YLD), soil fertility at harvest, plant nutritional status, and the physicochemical quality of the harvested broccoli. It was observed that GOF provided the best agronomic performance (HFM, HDM and YLD) of the broccoli and the greatest residual effect in the soil compared to PCMP and CMP. The moisture, ash, protein, lipid, total titratable acid and ascorbic acid contents were not significantly (p < 0.05) affected by the fertilizers used, on the other hand, total soluble solids and hydrogen potential showed the highest and lowest values, respectively, with CMP. The best agronomic performance, the highest phosphorus content in the soil and plant and the best physical–chemical quality of the broccoli occurred at a dose of 100% (400 kg ha⁻¹ of P₂O₅) of the recommendation for the crop in all three fertilizers evaluated. Full article

Interrow management in vineyards significantly contributes to sustainable viticulture, particularly in water-scarce European regions. Grassy and herbaceous cover crops have been proven to enhance multiple regulating ecosystem services, including soil conservation, carbon sequestration, and improved water infiltration. However, the potential for water competition with vines necessitates region-specific approaches. This review aims to analyze the effects of different cover crop types and interrow tillage methods on water management and regulating ecosystem services, focusing on main European vineyard areas. The research involved a two-stage literature review by Google Scholar and Scopus, resulting in the identification of 67 relevant scientific publications, with 11 offering experimental data from European contexts. Selected studies were evaluated based on climate conditions, soil properties, slope characteristics, and interrow treatments. Findings highlight that the appropriate selection of cover crop species, sowing and mowing timing, and mulching practices can optimize vineyard resilience under climate stress. Practical recommendations are offered to help winegrowers adopt cost-effective and environmentally adaptive strategies, especially on sloped or shallow soils, where partial cover cropping is often the most beneficial for both yield and ecological balance. Cover crops and mulching reduce erosion, enhance vineyard soil moisture, relieve water stress consequences, and, as a result, these cover cropping techniques can improve yield and nutritional values of grapes (e.g., Brix, pH, K concentration), but effects vary; careful, site-specific, long-term management is essential for best results. Full article

Loess, a typical soil widely distributed in China, exhibits engineering properties that are highly sensitive to environmental changes, leading to increased erosion and the development of surface cracks. This article examines the influence of initial moisture content, dry density, and thickness on crack formation in compacted loess subjected to wet–dry cycles, using both laboratory experiments and numerical simulation analysis. It quantitatively analyzes the process of crack evolution using digital image processing technology. The experimental results indicate that wet–dry cycles can cause cumulative damage to the soil, significantly encouraging the initiation and expansion of secondary cracks. New cracks often branch out and extend along the existing crack network, demonstrating that the initial crack morphology has a controlling effect over the final crack distribution pattern. Numerical simulations based on MultiFracS software further revealed that soil samples with a thickness of 0.5 cm exhibited more pronounced surface cracking characteristics than those with a thickness of 2 cm, with thinner layers of soil tending to form a more complex network of cracks. The simulation results align closely with the indoor test data, confirming the reliability of the established model in predicting fracture dynamics. The study provides theoretical underpinnings and practical guidance for evaluating the stability of engineering slopes and for managing and mitigating fissure hazards in loess. Full article

Lateritic soils in tropical regions feature cohesive textures and high specific resistance, driving up energy demands for tillage and harvesting machinery. However, current equipment designs lack discrete element models that account for soil moisture variations, and the microscopic effects of water content on lateritic soil deformation remain poorly understood. This study aims to calibrate and validate discrete element method (DEM) models of lateritic soil at varying moisture contents of 20.51%, 22.39%, 24.53%, 26.28%, and 28.04% by integrating the Hertz–Mindlin contact mechanics with bonding and JKR cohesion models. Key parameters in the simulations were calibrated through systematic experimentation. Using Plackett–Burman design, critical factors significantly affecting axial compressive force—including surface energy, normal bond stiffness, and tangential bond stiffness—were identified. Subsequently, Box–Behnken response surface methodology was employed to optimize these parameters by minimizing deviations between simulated and experimental maximum axial compressive forces under each moisture condition. The calibrated models demonstrated high fidelity, with average relative errors of 4.53%, 3.36%, 3.05%, 3.32%, and 7.60% for uniaxial compression simulations across the five moisture levels. Stress–strain analysis under axial loading revealed that at a given surface displacement, both fracture dimensions and stress transfer rates decreased progressively with increasing moisture content. These findings elucidate the moisture-dependent micromechanical behavior of lateritic soil and provide critical data support for DEM-based design optimization of soil-engaging agricultural implements in tropical environments. Full article

Understanding the impacts of the spatial non-stationarity of environmental factors on surface soil moisture (SSM) in different seasons is crucial for effective environmental management. Yet, our knowledge of this phenomenon remains limited. This study introduces an interpretable machine learning framework that combines the SHapley Additive exPlanations (SHAP) method with two-step clustering to unravel the spatial drivers of SSM across Iran. Due to the limited availability of in situ SSM data, the performance of three global SSM datasets—SMAP, MERRA-2, and CFSv2—from 2015 to 2023 was evaluated using agrometeorological stations. SMAP outperformed the others, showing the highest median correlation and the lowest Root Mean Square Error (RMSE). Using SMAP, we estimated SSM across 609 catchments employing the Random Forest (RF) algorithm. The RF model yielded R² values of 0.89, 0.83, 0.70, and 0.75 for winter, spring, summer, and autumn, respectively, with corresponding RMSE values of 0.076, 0.081, 0.098, and 0.061 m³/m³. SHAP analysis revealed that climatic factors primarily drive SSM in winter and autumn, while vegetation and soil characteristics are more influential in spring and summer. The clustering results showed that Iran’s catchments can be grouped into five categories based on the SHAP method coefficients, highlighting regional differences in SSM controls. Full article

A system of field protective forest belts (FPFBs) was created in the middle of the 20th century in Southern Dobrudzha (Northern Bulgaria) to reduce wind erosion, improve soil moisture storage, and increase agricultural crop yields. Since 2020, prolonged climatic drought during growing seasons and the advanced age of trees have adversely impacted the health status of planted species and resulted in the decline and dieback of the FPFBs. Physiologically stressed trees have become less able to resist pests, such as insects and diseases. In this work, an original new methodology for the integrated assessment of the condition of FPFBs and their protective capacity is presented. The presented methods include the assessment of structural and functional characteristics, as well as the health status of the dominant tree species. Five indicators were identified that, to the greatest extent, present the ability of forest belts to perform their protective functions. Each indicator was evaluated separately, and then an overlay analysis was applied to generate an integrated assessment of the condition of individual forest belts. Three groups of FPFBs were differentiated according to their condition: in good condition, in moderate condition, and in bad condition. The methodology was successfully tested in Southern Dobrudzha, but it could be applied to other regions in Bulgaria where FPFBs were planted, regardless of their location, composition, origin, and age. This methodological approach could be transferred to other countries after adapting to their geo-ecological and agroforest specifics. The methodological approach is an informative and useful tool to support decision-making about FPFB management, as well as the proactive planning of necessary forestry activities for the reconstruction of degraded belts. Full article

Understanding the interplay between plant leaf functional traits and plant and soil factors under different soil thicknesses is significant for quantifying the interaction between plant growth and the environment. However, in the context of ecological restoration of vegetation in mining areas, there has been a lot of research on trees, shrubs, and grasses, but the characteristics and correlations of leaf functional traits of vines have not been fully studied to a large extent. Here, we report the differences in leaf functional traits of six vine plants (Parthenocissus quinquefolia, Pueraria lobata, Hedera nepalensis, Campsis grandiflora, Mucuna sempervirens, and Parthenocissus tricuspidata) with distinct growth forms in different soil cover thicknesses (20 cm, 40 cm, and 60 cm). In addition, soil factor indicators under different soil cover thicknesses were measured to elucidate the linkages between leaf functional traits of vine plants and soil factors. We found that P. lobata showed a resource acquisition strategy, while H. nepalensis demonstrated a resource conservation strategy. C. grandiflora and P. tricuspidata shifted toward more conservative resource allocation strategies as the soil cover thickness increased, whereas M. sempervirens showed the opposite trend. In the plant trait–trait relationships, there were synergistic associations between specific leaf area (SLA) and leaf nitrogen content (LNC); leaf moisture content (LMC) and leaf nitrogen-to-phosphorus ratio (LN/P); and leaf specific dry weight (LSW), leaf succulence degree (LSD), and leaf dry matter content (LDMC). Trade-offs were observed between SLA and LSW, LSD, and LDMC; between leaf phosphorus content (LPC) and LN/P; and between LMC, LSW, and LDMC. In the plant trait–environment relationships, soil nutrients (pH, soil total phosphorus content (STP), and soil ammonium nitrogen content (SAN)) and soil enzyme activities (cellulase (CB), leucine aminopeptidase (LAP), enzyme C/N activity ratio, and enzyme N/P activity ratio) were identified as the primary drivers of variation in leaf functional traits. Interestingly, nitrogen deficiency constrained the growth of vine plants in the mining area. Our study revealed that the responses of leaf functional traits of different vines under different soil thicknesses have significant species specificity, and each vine shows different resource acquisition and conservation strategies. Furthermore, soil cover thickness primarily influences plant functional traits by directly affecting soil enzyme activities and nutrients. However, the pathways through which soil thickness impacts these traits differ among various functional traits. Our findings provide a theoretical basis and practical reference for selecting vine plants and optimizing soil cover techniques for ecological restoration in mining areas. Full article

In the context of efforts to reduce greenhouse gas emissions in the building sector, the reintegration of traditional earthen construction into modern architectural and renovation practices offers a sustainable alternative. To address the mechanical and water-resistance limitations of adobe bricks, the use of agricultural waste—such as rice husk—is increasingly being explored. This experimental study evaluates the effects of rice husk addition on the mechanical, hygrothermal, and acoustic properties of adobe bricks. Two soil types—one siliceous and one calcareous—were combined with 1, 2, and 3 wt% rice husk to produce bio-based earthen bricks. The influence of rice husk was found to depend strongly on the soils’ mineralogical and granulometric characteristics. The most significant improvements were in hygrothermal performance: at 3 wt%, thermal conductivity was reduced by up to 35% for calcareous soil and 20% for siliceous soil, indicating enhanced insulation. Specific heat capacity also increased with husk content, suggesting better thermal inertia. The moisture buffering capacity, already high in raw soils, is further improved due to increased surface porosity. Mechanically, rice husk incorporation had mixed effects: a modest increase in compressive strength was observed in siliceous soil at 1 wt%, while calcareous soil showed slight improvement at 3 wt%. Acoustic performance remained low across all samples, with minimal gains attributed to limited macro-porosity. These findings highlight the importance of soil composition in optimizing rice husk dosage and suggest promising potential for rice husk-stabilized adobe bricks, especially in thermally demanding environments. Full article

Kiwifruit is a high-value subtropical crop with significant nutritional and economic importance, but its cultivation faces growing challenges due to climate change, particularly in Caucasus. This study aims to study the impact of abiotic stressors such as temperature extremes, drought, and frost on the yield of the ‘Hayward’ cultivar over a 20-year period (from 2003 to 2022). Using a combination of agroclimatic data analysis, measurements of soluble solid content, and soil moisture assessments, this research identified key factors which limit kiwifruit cultivation productivity. The results revealed a high yield variability—68%, with the mean value declining by 16.6% every five years due to increasing aridity and heat stress. Extreme temperature rises of up to 30 °C caused yield losses of 79–89%, and the presence of frost led to declines of 71–94%. In addition, it is objectively proven that the vulnerability of kiwifruit is subject to climate-driven water imbalances. This highlights the need for adaptive strategy formation in the area of optimized irrigation for the sustainable cultivation of fruit in the subtropics. One of the study’s limitations was that it was organized around a single variety of kiwifruit (‘Hayward’). In view of the fact that there are significant differences in growth characteristics among kiwifruit varieties, future research should focus on overcoming this shortcoming. Full article

The Advanced Scatterometer (ASCAT), Soil Moisture Active Passive (SMAP), and European Space Agency-Climate Change Initiative (ESA–CCI) soil moisture (SM) products are widely used in agricultural drought monitoring, water resource management, and climate analysis applications. However, the performance of these SM products varies significantly across regions and environmental conditions, due to in sensor characteristics, retrieval algorithms, and the lack of localized calibration. This study proposes a multi-source long short-term memory (MLSTM) for improving ASCAT, ESA–CCI, and SMAP SM products by combining in-situ SM measurements and four key auxiliary variables: precipitation (PRE), land surface temperature (LST), fractional vegetation cover (FVC), and evapotranspiration (ET). First, the in-situ measured data from four in-situ observation networks were corrected using the LSTM method to match the grid sizes of ASCAT (0.1°), ESA–CCI (0.25°), and SMAP (0.1°) SM products. The RPE, LST, FVC, and ET were used as inputs to the LSTM to obtain loss data against in-situ SM measurements. Second, the ASCAT, ESA–CCI, and SMAP SM datasets were used as inputs to the LSTM to generate loss data, which were subsequently corrected using LSTM-derived loss data based on in-situ SM measurements. When the mean squared error (MSE) loss values were minimized, the improvement for ASCAT, ESA–CCI, and SMAP products was considered the best. Finally, the improved ASCAT, ESA–CCI, and SMAP were produced and evaluated by the correlation coefficient (R), root mean square error (RMSE), and standard deviation (SD). The results showed that the RMSE values of the improved ASCAT, ESA–CCI, and SMAP products against the corrected in-situ SM data in the OZNET network were lower, i.e., 0.014 cm³/cm³, 0.019 cm³/cm³, and 0.034 cm³/cm³, respectively. Compared with the ESA–CCI and SMAP products, the ASCAT product was greatly improved, e.g., in the SNOTEL network, the Root Mean-Square Deviation (RMSD) values of 0.1049 cm³/cm³ (ASCAT) and 0.0662 cm³/cm³ (improved ASCAT). Overall, the MLSTM-based algorithm has the potential to improve the global satellite SM product. Full article

Arbuscular mycorrhizal (AM) fungi (AMF) form a symbiotic association with terrestrial plants and increase growth and productivity. The relationships between the growth of centipedegrass (CG) and AMF are not well understood. We monitored the growth and AM colonization of CG growing on the four slopes (north, east, south, and west) of a pasture, to obtain information on aspect differences in the soil chemical properties–grass–AMF association. Soil properties almost always varied between the slope aspects. The total soil N, C, EC, and moisture tended to be highest on the northern aspect, whereas the soil available P and pH tended to be highest on the western and southern aspects, respectively. Despite the aspect differences in the microclimate and soil properties, CG grew well in all aspects, showing similar dry matter weights (DMW) for the fouraspects. Furthermore, the AM colonization of CG, in any characteristic structures (internal hyphae, vesicles, and arbuscules), was not significantly different between the slope aspects on most measurement occasions, although the colonization usually varied between the seasons and years. There were no relationships between the DMW and AM characteristic structure colonization and between the DMW and soil chemical properties. However, the colonization of the arbuscules and vesicles of the CG had a correlation with some soil chemical properties. The results suggest that AM colonization on CG growing in a hill pasture did not differ between the slope aspects. This may be a factor contributing to the high adaptability of the grass to all slope aspects. Full article

Soil moisture (SM) is a key variable in agricultural ecosystems and is crucial for drought prevention and control management. However, SM is influenced by underlying surface and meteorological conditions, and it changes rapidly in time and space. To capture the changes in SM and improve the accuracy of short-term and medium-to-long-term predictions on a daily scale, an LSTMseq2seq model driven by both observational data and mechanism models was constructed. This framework combines historical meteorological elements and SM, as well as the SM change characteristics output by the VIC model, to predict SM over a 90-day period. The model was validated using SMAP SM. The proposed model can accurately predict the spatiotemporal variations in SM in Jiangxi Province. Compared with classical machine learning (ML) models, traditional LSTM models, and advanced transformer models, the LSTMseq2seq model achieved R² values of 0.949, 0.9322, 0.8839, 0.8042, and 0.7451 for the prediction of surface SM over 3 days, 7 days, 30 days, 60 days, and 90 days, respectively. The mean absolute error (MAE) ranged from 0.0118 m³/m³ to 0.0285 m³/m³. This study also analyzed the contributions of meteorological features and simulated future SM state changes to SM prediction from two perspectives: time importance and feature importance. The results indicated that meteorological and SM changes within a certain time range prior to the prediction have an impact on SM prediction. The dual-driven LSTMseq2seq model has unique advantages in predicting SM and is conducive to the integration of physical mechanism models with data-driven models for handling input features of different lengths, providing support for daily-scale SM time series prediction and drought dynamics prediction. Full article