Search Results (9,564)

Saline soil represents an important reserve of cultivated land in China, yet poor soil conditions and low-nitrogen use efficiency constrain crop production. Biochar has been widely applied to improve soil properties; however, its interactive effects with nitrogen fertilization in saline soils remain unclear. A pot experiment using coastal saline soil collected from the northern Jiangsu province was conducted to evaluate the combined effects of biochar (0%, 4%, and 8% w·w⁻¹) and nitrogen fertilizer (0, 150, and 200 mg·kg⁻¹) on the growth performance, photosynthetic indices, yield, quality, and nitrogen use efficiency of water spinach (Ipomoea aquatica Forssk.). Moderate biochar application significantly improved vegetative growth of water spinach, as indicated by higher plant height, stem diameter, leaf area index, and SPAD values. In addition, biochar substantially enhanced photosynthetic performance, dry matter accumulation, and yield, whereas excessive biochar or nitrogen application generally inhibited plant performance. The combined application of 4% biochar with 150 mg·kg⁻¹ nitrogen consistently produced the highest yield and nitrogen partial factor productivity, while simultaneously increasing soluble protein, soluble sugar, and vitamin C contents and reducing nitrite accumulation. These research results demonstrated a clear synergistic interaction between biochar and nitrogen fertilization. In coastal saline soils, reducing the usage of nitrogen fertilizer moderately and adding approximately 4% of biochar is an effective strategy. Full article

Global sustainability challenges call for assessing the environmental impacts of agricultural production systems, which are crucial to meeting the nutritional demands of a growing global population. This study uses the PRISMA model and a checklist to provide a systematic literature review of LCA studies on durum wheat and legume cultivation; it highlights the impacts of monoculture cultivation with crop rotation on key environmental indicators. An analysis was conducted to examine the environmental burdens of these crops under conventional and organic systems and explored how using different functional units (mass- or area-based) influences the environmental outcomes. The results reveal that integrating legumes into crop rotations significantly enhances environmental sustainability by reducing reliance on synthetic nitrogen fertilizers through biological nitrogen fixation, resulting in substantial environmental benefits, reaching a reduction in GWP from 6 to 45% compared to monoculture durum wheat cultivation. Conventional agriculture achieves higher crop yields; however, its reliance on chemical inputs and substantial energy consumption results in greater overall environmental impact. Conversely, while organic farming has a lower impact per unit of land, its lower productivity results in higher emissions per unit of output. Full article

Accurate, high-resolution information on economic forest resources, here referring to fruit-tree plantations and economic tree crops, is essential for land-use planning and resource management in arid regions. Xinjiang, China—one of the country’s most important fruit-producing areas—exhibits highly fragmented and heterogeneous distributions of economic tree plantations, posing challenges for large-scale and long-term monitoring. In this study, we integrated multi-source remote sensing data by combining multi-temporal Sentinel-2 optical imagery with Sentinel-1 SAR backscatter and texture features to characterize the spatial and temporal distribution patterns of major economic tree plantations from 2019 to 2024. An optimized Random Forest classifier was applied across five key production regions (Aksu, Bazhou, Hotan, Kashgar, and Turpan–Hami). The mapping results achieved overall accuracies ranging from 0.85 to 0.97, with Kappa coefficients between 0.80 and 0.95. The results indicate that economic tree plantations are predominantly distributed along oasis corridors of the Tarim Basin and the alluvial plains on both sides of the Tianshan Mountains, forming belt- and patch-like spatial patterns. While the overall spatial configuration remained relatively stable during the study period, localized expansion was observed, mainly associated with walnut, jujube, and grape plantations. These findings provide insights into the spatial dynamics of economic tree plantations and support land-use optimization and agricultural planning in arid and semi-arid regions. Full article

Agrivoltaic systems, which integrate solar energy generation with agricultural production, offer a promising solution to optimize land use efficiency. This work presents a case study for the assessment of an agrivoltaic pilot project in a small-scale solar farm operated by SOLENIUM in San Diego (Cesar, Colombia), located in the Colombian tropical dry forest. The project evaluated environmental conditions, selected melon and watermelon as shade-tolerant crops, and assessed technical challenges, including mechanization constraints. Preliminary results indicated that agrivoltaic systems can maintain agricultural productivity while generating renewable energy, with photosynthetically active radiation measurements averaging 1342 μmol/m²/s in cultivation areas. This case study demonstrates the viability of agrivoltaic systems as a scalable model for sustainable rural development in the Colombian tropical dry forest. Full article

The subject of this research is the exploration of the potential of remote sensing and Geographic Information Systems (GIS) for basin-scale spatio-temporal monitoring of drought and its impacts in the Ukrina River Basin, Bosnia and Herzegovina (BH), during the last decade (2015–2024). The aim is to integrate meteorological, hydrological, agricultural, and socio-economic drought signals and to delineate areas of long-term drought exposure. Meteorological drought was evaluated using CHIRPS precipitation and the Standardized Precipitation Index (SPI) calculated at 1-, 3-, 6-, and 12- month accumulation scales using Gamma fitting and a fixed long term reference period; hydrological drought was examined using available water-level records complemented by the Standardized Water Level Index (SWLI) and supported by correspondence with standardized ERA5-Land runoff anomalies; agricultural drought was mapped using remote sensing indices—the Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI)—calculated from MODIS satellite data; and socio-economic effects were assessed using municipal crop-production statistics (2015–2019). The results indicate that drought conditions were most pronounced in 2015, 2017, 2021, and especially 2022, showing consistent agreement between precipitation deficits, hydrological responses, and vegetation stress, while 2016, 2018–2020, 2023, and 2024 were generally more favorable. As a key novelty, a persistent drought-prone zone was delineated by intersecting drought-affected areas across major episodes, providing a basin-scale identification of chronic drought hotspots for a river basin in BH. The persistent zone covers 40.02% of the basin and spans nine cities and municipalities, with >93% located in Prnjavor, Derventa, Stanari, and Teslić. Hotspots are concentrated mainly in lowlands below 400 m a.s.l., with a statistically significant concentration across lower elevation classes, indicating higher long-term exposure in the central and northern valley sectors, and land use overlay further highlights high relative exposure of productive land. Overall, the integrated remote sensing and GIS framework strengthens drought monitoring by providing spatially explicit and repeatable evidence to support targeted adaptation planning and drought-risk management. Full article

Camellia oleifera, a woody oil crop unique to China, plays a crucial role in alleviating the global pressure of edible oil supply and maintaining ecological security. However, it remains challenging to accurately forecast Camellia oleifera yield in complex landscapes using only remote sensing data. The aim of this study is to develop an interpretable deep learning model, namely Shapley Additive Explanations–guided Attention–long short-term memory (SALSTM), for estimating Camellia oleifera yield by integrating an improved spectral bloom index and environmental parameters. The study area is located in Hengyang City in Hunan Province. Sentinel-2 imagery, meteorological observation from 2019 to 2023, and topographic data were collected. First, an improved spectral bloom index (ISBI) was constructed as a proxy for flowering density, while average temperature, precipitation, accumulated temperature, and wind speed were selected to represent environmental regulation variables. Second, a SALSTM model was designed to capture temporal dynamics from multi-source inputs, in which the LSTM module extracts time-dependent information and an attention mechanism assigns time-step-wise weights. Feature-level importance derived from SHAP analysis was incorporated as a guiding prior to inform attention distribution across variable dimensions, thereby enhancing model transparency. Third, model performance was evaluated using root mean square error (RMSE) and coefficient of determination (R²). The result show that the constructed SALSTM model achieved strong predictive performance in predicting Camellia oleifera yield in Hengyang City (RMSE = 0.5738 t/ha, R² = 0.7943). Feature importance analysis results reveal that ISBI weight > 0.26, followed by average temperature and precipitation from flowering to fruit stages, these features are closely associated with C. oleifera yield. Spatially, high-yield zones were mainly concentrated in the central–southern hilly regions throughout 2019–2023, In contrast, low-yield zones were predominantly distributed in the northern and western mountainous areas. Temporally, yield hotspots exhibited a gradual increasing while low-yield zones showed mild fluctuations. This framework provides an effective and transferable approach for remote sensing-based yield estimation of flowering and fruit-bearing crops in complex landscapes. Full article

Low salinity tolerance during germination and early seedling establishment limits large-scale cultivation of halophytes for forage, food, restoration, and conservation purposes. This study evaluates the potential of redox priming to enhance salt tolerance in the perennial C₄ halophyte grass Urochondra setulosa, which could be used as a revegetation and phytoremediation crop for coastal saline lands. Fresh seeds were found to be non-dormant with ~90% mean final germination (MFG) in distilled water. Redox priming, including hydrogen peroxide (H₂O₂), melatonin (MT), sodium nitroprusside (SNP; a nitric oxide donor), and ascorbic acid (AsA), significantly accelerated the germination rate index (GRI) and reduced mean germination time (MGT) without altering MFG under non-saline conditions. Salinity severely suppressed germination, as unprimed seeds reached only ~1% MFG with ~99% germination reduction (GR) and near-zero germination stress tolerance index (GSTI) at 200 mM NaCl. All priming treatments significantly improved MFG, GRI, and GSTI and decreased GR, with H₂O₂ priming showing the highest amelioration. Ungerminated seeds from all treatments recovered ~90% germination capacity in water, indicating enforced dormancy owing to osmotic constraints. Salinity did not impair growth in unprimed seedlings. However, MT priming uniquely enhanced total length, leaf area, and seedling vigor index (SVI) at 200 mM NaCl, while MT and SNP priming resulted in the highest chlorophyll and carotenoid contents. Multivariate analyses confirmed MT’s consistent superiority across traits under stress. Thus, H₂O₂ priming optimizes germination, while MT priming improves seedling vigor and offers a practical, targeted strategy to improve early-stage salinity tolerance in U. setulosa for coastal revegetation and sustainable saline agriculture. Full article

This study presents a drone-based method for assessing the condition of road markings from high-resolution imagery acquired by a UAV. A DJI Matrice 300 RTK (Real-Time Kinematic) equipped with a Zenmuse P1 camera (DJI, China) is flown over urban road corridors to capture images with centimeter-level ground sampling distance. In contrast to common approaches that rely on vehicle-mounted or street-view cameras, using a UAV reduces survey time and deployment effort while still providing views that are suitable for marking. The flight altitude, overlap, and corridor pattern are chosen to limit occlusions from traffic and building shadows while preserving the resolution required for condition assessment. From these images, the method locates individual markings, assigns a class to each marking, and estimates its level of deterioration. Candidate markings are first detected with YOLOv9 on the UAV imagery. The detections are cropped and segmented, which refines marking boundaries and thin structures. The condition is then estimated at the pixel level by modeling gray-level statistics with kernel density estimation (KDE) and a two-component Gaussian mixture model (GMM) to separate intact and distressed material. Subsequently, we compute a per-instance damage ratio that summarizes the proportion of degraded pixels within each marking. All results are georeferenced to map coordinates using a 3D reference model, allowing visualization on base maps and integration into road asset inventories. Experiments on unseen urban areas report detection performance (precision, recall, mean average precision) and segmentation performance (intersection over union), and analyze the stability of the damage ratio and processing time. The findings indicate that the drone-based method can identify road markings, estimate their condition, and attach each record to geographic space in a way that is useful for inspection scheduling and maintenance planning. Full article

Background/Objectives:Pyrus ussuriensis Maxim. has been cultivated in many regions worldwide. This plant is also regarded as a profitable fruit crop for the development of many food and functional products. There is limited research on the application of the LC-MS associated reaction method for screening active compounds. In this study, we developed an analytical technique employing an ultra-high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UHPLC-ESI-MS/MS) system. Methods: The metabolite annotation procedure was used to interpret and validate data analysis via spectral matching against public databases. Results: As a result, metabolites from P. ussuriensis water and EtOH extracts were identified, and their quantities were further evaluated. The established method was employed to determine antioxidant capacity using a pre-incubation UHPLC-2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, thereby identifying antioxidant ingredients. The antioxidative interference of active constituents was predicted by calculating the decrease in the peak areas of the chemical composition detected in chromatograms between treated and non-treated samples. Furthermore, drug-likeness was also assessed via pharmacokinetics (absorption, distribution, metabolism, and excretion: ADME) evaluation. Conclusions: The online UHPLC-MS-DPPH method would be a powerful tool for the rapid characterization of antioxidant ingredients in plant extracts. The current study highlights the value of P. ussuriensis for improved health benefits. Full article

Intensive agriculture, ecosystem degradation, and declining soil quality highlight the urgent need for sustainable land use strategies. The cultivation of short-rotation woody crops (SRC), combined with fertilization using sewage sludge digestate (SSD), offers a promising approach to recycle nutrient-rich waste and promote soil organic carbon (SOC) accumulation. This study evaluated SOC concentrations, stocks and their spatial distribution in the 0–20 cm soil layer under SRC cultivation, with and without SSD fertilization, across contrasting soil types in Eastern Lithuania. The investigated soils included mineral (Luvisols (LV), Retisols (RT), Planosols (PL), Arenosols (AR)), organo-mineral (Gleysols (GL)), and organic soils (Histosols (HS)), representing textures from sand to peat and classified according to the World Reference Base for Soil Resources (WRB). Part I assessed baseline SOC variability in unproductive areas planted with hybrid poplars (Populus spp.) and hybrid aspen (Populus tremula × P. tremuloides) up to 20 years old. Part II examined SOC changes in three SRC fields of different ages (3–10 years), including unfertilized and SSD-fertilized stands. SOC concentrations increased consistently from mineral (1.14–1.80%) to organo-mineral (2.13–3.20%) and organic soils (6.37–17.53%). Heavier-textured soils accumulated more SOC than lighter soils, showing a strong positive correlation between SOC and soil texture (r = 0.82, p ≤ 0.01). SRC cultivation increased SOC across all soil types, while SSD fertilization further enhanced accumulation, with fertilized fields showing SOC increases of 0.50–1.07 percentage points and carbon stocks by 18.8–41.7 t ha⁻¹, compared with smaller increases in unfertilized fields. Spatial visualization of SOC further highlighted long-term accumulation patterns across soil types, confirming the trends observed under SRC cultivation and SSD fertilization. Full article

Wheat (Triticum aestivum L.) is a strategic food crop for arid, hot regions such as the Arabian Peninsula, the Middle East, and North Africa. In these areas, production is limited by extreme environmental and agronomic conditions, leading to heavy dependence on imported wheat. Irrigation is often essential for successful cultivation, but available water sources are frequently saline. This study evaluated the comparative effects of irrigation salinity and genotype on agronomic performance, physiological responses, and grain quality. Nine Syrian wheat genotypes and one French bread-making cultivar, Florence Aurora, were grown in sandy soil under three irrigation salinity levels (2.6, 10, and 15 dS m⁻¹) across two seasons at the International Center for Biosaline Agriculture (Dubai, UAE). Salinity strongly negatively impacted yield, which decreased by 61% from the control to 15 dS m⁻¹, along with key yield components such as thousand grain weight and total biomass. Physiological traits, including carbon isotope composition (δ¹³C) and Na concentrations in roots, shoots and grains, increased significantly with salinity, while chlorophyll content showed a modest decline. Effects on grain quality were relatively minor: total nitrogen concentration and most mineral levels increased slightly, mainly due to a passive concentration effect associated with reduced TGW. Genotypes varied significantly in yield, biomass, TGW, physiological traits, and grain quality. The highest-yielding genotypes under control conditions (ACSAD 981 and ACSAD 1147) also performed best under saline conditions, and no trade-off was observed between yield and grain quality parameters (TGW, nitrogen, zinc, and iron concentrations). Separate analyses conducted for control and saline treatments identified different drivers of genotypic variability. Under control conditions, chlorophyll content, closely linked with δ¹³C, was the best predictor of genotypic differences and was positively correlated with yield across genotypes. Under salinity stress, grain magnesium (Mg) concentration was the strongest predictor, followed by grain δ¹³C, with both traits positively correlated with yield. These findings highlight key physiological traits linked to salinity tolerance and offer insights into the mechanisms underlying genotypic variability under both optimal and saline irrigation conditions. Full article

Seed germination performance and storability are fundamental components of seed quality and critical for successful crop establishment. However, information on the impact of different crop production systems on the quality and storability of seed material is still limited. Therefore, the aim of this study was to compare the effects of different crop production systems (ecological, integrated, conventional, and monoculture) on seed germination and predisposition for storage. The research was carried out on four varieties of winter wheat. Seed material was produced within a two-year period, during which different weather conditions occurred. Four germination-related traits were assessed: germination capacity NS (%), total germination (TG%), time to reach 50% germination (t50) and the area under the germination curve (AUC). The results demonstrated that the cultivar, the cultivation system and the year of study had a significant impact on germination characteristics. The ecological system ensured the highest germination rate in fresh seeds. However, in the CD test, the conventional system demonstrated the highest levels of stress resistance and stability, suggesting the best storage potential. The significant system × variety interaction demonstrates the importance of accurate matching of the genotype to the growing conditions to ensure optimal seed quality. Furthermore, the data demonstrated a strong influence of climatic conditions in the year of production, which is crucial for seed vigor. Full article

Understanding the distribution of water and salt in the crop’s root zone and predicting future soil degradation requires specific monitoring to establish guidelines for irrigation management and system performance. Two field experiments were conducted in the arid region of Southern Tunisia to assess soil water and salt dynamics under surface- and drip-irrigated carrots using HYDRUS 2D/3D simulations in the 2017–2018 and 2018–2019 crop seasons. The soil water contents and bulk soil electrical conductivities were measured at three distinct soil layers: 0–20 cm, 20–40 cm, and 40–60 cm, where TDR probes were located. Statistical indicators (nRMSE, IA, and PBIAS) suggest that HYDRUS 2D/3D is reliable in simulating field hydro-saline dynamics for irrigated carrots. The results obtained for the two crop seasons exhibit a strong correlation between the simulated and measured values for both soil water contents and electrical conductivities. The study also shows that HYDRUS 2D/3D allows more accurate simulations of soil water dynamics than soil salinity under these conditions. Overall, these results provide valuable insights for understanding the hydrological processes in arid regions and can help in improving the management of water resources in these areas. Full article

This article reports on a comparative case study that examined the ground rules used to facilitate a dialogic space in two discrete and diverse research studies: Year 5 & 6 children learning to code with ScratchMaths as part of their mathematics programmes, and crop farmers in rural east Africa developing their practice through various communications. The intention was to see if there were common actions or principles important for the establishment of ground rules in dialogic spaces in general. Understanding the nature of dialogic space has become increasingly important in many areas of education. STEM subjects, particularly when integrated, frequently involve collaborative interaction, and utilise a dialogical approach. Some initial aspects of ground rules were collaboratively identified, with both studies then independently analysed to identify emerging themes related to these ground rules. Several key elements emerged: developing the processes for interaction and communication; developing trust between participants; developing respectful dialogue; teacher roles; and facilitating collaborative work and the co-construction of meaning. The comparative case study suggested that these were important for other education work when establishing dialogic space. Full article

Accurate and stable mapping of crop types is fundamental to agricultural monitoring and food security. However, inter-annual phenological shifts driven by variations in air temperature, precipitation, and sowing dates introduce systematic changes in the spectral distributions associated with the same day of year (DOY). As a result, the “date–spectrum–class” mapping learned during training can become misaligned when applied to a new year, leading to increased misclassification and unstable performance. To tackle this problem, we develop TABS-Net (Temporal–Spectral Attentive Block with Space–Time Fusion Network). The core contributions of this study are summarized as follows: (1) we propose an end-to-end 3D CNN framework to jointly model spatial, temporal, and spectral information; (2) we design and embed CBAM3D modules into the backbone to emphasize informative bands and key time windows; and (3) we introduce DOY positional encoding and temporal jitter during training to explicitly align seasonal timing and simulate phenological shifts, thereby enhancing cross-year robustness. We conduct a comprehensive evaluation on a Cropland Data Layer (CDL) subset. Within a single year, TABS-Net delivers higher and more balanced overall accuracy, Macro-F1, and mIoU than strong baselines, including 2D stacking, 1D temporal convolution/LSTM, and transformer models. In cross-year experiments, we quantify temporal stability using inter-annual robustness (IAR); with both DOY encoding and temporal jitter enabled, the model attains IAR values close to one for major crop classes, effectively compensating for phenological misalignment and inter-annual variability. Ablation studies show that DOY encoding and temporal jitter are the primary contributors to improved inter-annual consistency, while CBAM3D reduces crop–crop and crop–background confusion by focusing on discriminative spectral regions such as the red-edge and near-infrared bands and on key growth stages. Overall, TABS-Net combines higher accuracy with stronger robustness across multiple years, offering a scalable and transferable solution for large-area, multi-year remote sensing crop mapping. Full article