Organic agriculture is becoming more popular because of its potential benefits for the environment and human health compared with traditional farming methods. Tomatoes, one of the most widely cultivated horticultural crops in the United States, are grown using both organic and conventional systems, which differ in their approaches to nutrient management, soil management, and plant protection. These differences can affect nutrient absorption and fruit quality. This study aimed to evaluate nutrient uptake and fruit quality of eight hybrid tomato cultivars grown under both organic and conventional production systems. The tomato cultivars showed significant differences in yield, fruit quality, and nutrient uptake in both systems. However, the two systems cannot be directly compared because of the many independent variables involved. Differences were observed in how the genotypes performed across systems. These findings highlight the importance of cultivar selection because different hybrids may respond uniquely to various production conditions. To improve fruit quality and nutrient use efficiency, producers should consider how specific cultivars perform under different production systems.

• 20 + years of data from 74 experiments reveal ski slope impacts on alpine hydrology. • Surface runoff is higher for ski slopes, indicating altered hydrological behaviour. • Random forest analysis shows surface runoff depends on multiple variables. • Key surface runoff drivers include land use, geology, soil, and topography. • Sustainable soil and land-use management can reduce ski slope runoff. This study investigates the surface runoff behaviour in 12 ski regions in the Eastern Alps based on data from 74 rainfall simulation experiments. The dataset includes information on hydrological responses, water storage, and infiltration. By applying a random forest regression model, surface runoff coefficients were linked to site-specific hydrological variables, providing insights into drivers of surface runoff. Results indicate higher surface runoff coefficients on ski slopes (0.57) compared to reference areas (0.07) within ski resorts that were not modified for skiing activities. Moreover, our findings suggest that geological variables are the strongest predictors of surface runoff on ski slopes. On ski slopes the surface runoff response is also influenced by a combination of hydrological variables, including mechanical disturbances from slope preparation and land use practices. For the reference areas, soil and land use variables play a more pronounced role. These findings underscore the importance of sustainable soil management and restoration strategies to mitigate the impacts of ski slope construction on runoff regimes and to maintain hydrological stability in Alpine regions.

Dataset of greenhouse gas fluxes and soil properties from a biochar application frequency and dosage experiment in an upland agroecosystem in Guizhou, China (2020-2023).

AGRO AI: A compact solution for modernizing the agriculture using NASA’s satellite data and artificial intelligence

Optimizing biochar rate and particle size for enhanced wheat yield and water productivity using response surface methodology

Soil management legacy drives the short-term response of the soil microbiome to compost application

Different land use types around megacities contribute contrasting heavy metal pollution and health risks in soil-leaf vegetable systems.

Biodegradable mulch film-enriched with biochar, chicken feather, and oyster shell powder for improved soil quality and crop productivity.

North African countries are increasingly facing climate change, natural resource degradation, and food crises. Algerian regions such as Laghouat are one of the hotspots where problems such as soil degradation, desertification, and water scarcity are experienced. Current agricultural production systems are not responding to future needs and are inadequate to address these problems. Agroecology emerges as a promising alternative that can respond to growing future needs by providing resilient and sustainable production systems. This study investigates the factors affecting farmers’ adaptation to agroecology in Laghouat, Algeria, using Elinor Ostrom’s Social Ecological Systems Framework (SESF). We apply our mixed-methods methodology in the field to systematically examine the complex relationships of the system, resource systems and, governance, and actors. Our findings suggest that the negative impacts of unsustainable agricultural practices, combined with climate change and misguided policies, are leading to a problematic trend that results in a system that is losing its resilience and sustainability and is becoming increasingly vulnerable. However, the study also highlights that farmer training, incentives to support the adoption of environmentally friendly practices, and strong social networks can significantly increase the transition to sustainable agroecology. These insights underline the need for integrated and collaborative strategies to achieve sustainable soil management, and hence more resilient agricultural system. • Agroecology can induce sustainable agricultural land management and improve soil health in a systematic manner. • Transdisciplinary approach helps understand SES by integrating social, ecological and economic aspects of soil and land use. • Participatory and site-specific methodology has been developed to implement Social Ecological Systems framework.

Valorization of wheat straw waste via low-temperature pyrolysis into non-alkaline coating materials for mitigating nitrogen loss from urea in saline-alkali soils.

Conventional nitrogen fertilization frequently results in soil degradation and environmental pollution. While the isolated effects of nitrogen reduction, organic amendments, or biochar have been explored, their synergistic interactions remain inadequately understood. This two-year field study in Yunnan, China, addressed this gap by evaluating the coupling effects of biochar (applied at 10, 15, and 20 t ha⁻¹) with three organic fertilizers (chicken manure, cattle manure, and earthworm castings) under a consistent 40% nitrogen reduction. The primary objective was to establish a technical pathway for synergistic fertilizer reduction, waste utilization, and sustainable soil management. Results demonstrated that the combination of earthworm castings and biochar (15 t ha⁻¹), designated as treatment F3B2, most significantly enhanced soil nutrient supply and microbial diversity. This treatment yielded the highest relative abundance of the top 10 bacterial genera and maximum bacterial Chao1 indices of 3028.06 and 3087.18 in the first and second years, representing increases of 10.13% and 18.50% compared to the control (CK), respectively. Agronomically, the F3B2 treatment increased tomato yield by 23.75% and vitamin C content by 14.65% in the second year. Furthermore, TOPSIS analysis consistently ranked F3B2 as the optimal integrated management strategy. This study provides a replicable paradigm for green and efficient production in protected vegetable cultivation systems. In conclusion, the integrated application of organic fertilizer and biochar under reduced nitrogen conditions synergistically optimizes soil health—particularly by enhancing the microbial community—and significantly promotes tomato growth, yield, and quality.

The quality of the soil is greatly influenced by soil management practices that either raise or decrease the criteria of soil quality. Therefore, it is crucial to monitor our soil to determine whether agricultural practices have a major positive or negative impact on it. The Havza district in Samsun, Turkey, which is a semi-humid climate region, experiences intensive agricultural land use, diverse soil-forming conditions, and increasing pressure from management practices, making it a vulnerable agroecosystem necessitating monitoring. Thus, this research was carried out to assess and predict the soil quality of this region. 217 soil samples were collected from the study area, and 33 soil quality parameters were selected and analyzed. The data were subjected to the Integrated Quality Index (IQI) and the Artificial Neural Network (ANN). This is to support sustainable land management, productivity, and long-term soil conservation under increasing human and climatic pressure. In addition, the Total Dataset (TDS) of soil parameters was subjected to Principal Component Analysis (PCA), and 13 soil quality parameters were chosen for the creation of a Minimum Dataset (MDS), and spatial distribution maps of the study area were created. The result showed that the Soil Quality Index (SQI) determined by IQI was similar to that predicted by ANN, with R2 values of 0.999, 0.970, and 0.987 for training, validation, and testing, respectively. The distribution maps show sporadic low-quality areas within the interior, with the lowest quality in the northern middle part of the study area. The overall soil quality was classified as medium quality. Also, the distribution maps provide valuable information for land management, ecosystem management, and the sustainability of agricultural farmlands.

The development processes of soil are influenced by temperature and precipitation; moreover, changes in soil properties are influenced by land use factors. This study aimed to identify the pattern of changes in climate over 40years (from 1985-2024) and, concomitantly, the spatial and temporal variabilities in the soil properties of Sylhet, a humid subtropical region of Bangladesh. Soil samples were taken from 8 unions of the Sylhet sadar upazila during 2024 and tested in the laboratory to determine the present status of different soil parameters. The temporal changes in soil properties were assessed by comparing the laboratory-analysed data with soil resource development institute-reported soil data from 2007. The annual maximum temperature during the last 20years of the study (2005-2024) increased by 0.42°C on average, and the hottest year was 2023. The total annual precipitation sharply decreased by 762.34mm compared with that in the first 20years (1985-2004), with continuous below-normal precipitation events (-1270.96mm to -104.32mm) from 2018-2023 and high interannual variability. In addition, this study revealed greater spatial variability in soils than temporal variability, which was influenced mainly by inherent soil characteristics such as texture and pH and assumed land management practices. Moderate temporal variability in soil organic carbon and other nutrient availability might be associated with changing climates. These findings on spatial and temporal changes in soil properties are expected to be helpful for guiding future soil and crop management in humid subtropical regions in a better way under changing climates.

ABSTRACT Enhancing sustainability in intensive vegetable production systems, such as raised-bed plasticulture with drip irrigation, requires precise nitrogen (N) management to balance productivity with environmental stewardship. Field experiments and 15N tracer studies demonstrated that conventional fertilizer practices in sandy soils were often associated with low recovery of applied N, indicating substantial inefficiencies when application rates and timing exceeded crop demand. Aligning N inputs more closely with crop requirements maintained adequate plant nutrition and favorable soil C:N ratios but did not result in measurable increases in soil organic matter, highlighting the need for complementary soil management practices in systems with inherently low organic carbon. To improve synchronization between N availability and crop uptake, controlled-release fertilizers were evaluated as alternatives to split-applied soluble urea. When applied at rates aligned with crop N requirements, controlled-release fertilizers improved nitrogen use efficiency, reduced labor requirements, and supported yield stability, particularly under warm-season production conditions characterized by rapid soil N turnover and elevated irrigation demand. Economic analyses indicated that, despite higher upfront fertilizer costs, controlled-release fertilizers improved net returns through labor savings and more consistent marketable yields. Collectively, these results support a nutrient management framework that integrates optimized fertilizer rates, improved fertilizer technologies, and complementary practices such as cover cropping. This approach offers a practical pathway for improving agronomic efficiency and economic viability while reducing the risk of N losses, and provides field-based evidence to inform extension, policy, and nutrient management programs focused on sustainable vegetable production.

Acidic soils (pH < 5.5) contain elevated levels of phytotoxic aluminum (Al3+) and iron (Fe2+/Fe3+); however, the mechanisms underlying plant adaptation to their coexistence remain poorly understood. Commelina communis, an invasive weed prevalent on acid soils of tea gardens, was exposed to Al (50 and 100 µM) and Fe (100 µM), individually and in combination (pH 4.0), for four weeks. Plant biomass remained unaffected under single or combined stress, accompanied by reciprocal reductions in foliar metal concentrations. However, chlorosis, reduced photosynthetic pigments, and altered photochemical parameters indicated exacerbated chloroplast damage under combined Al and Fe toxicity. Conversely, phenolic and anthocyanin contents in leaves and oxalate in roots peaked under dual stress, coinciding with significantly reduced stress markers. Histochemical analysis revealed that Al3+ and Fe2+ mutually inhibited binding to root tips, reducing membrane injury under co-treatment. Fourier-transform infrared (FTIR) spectroscopy of root tissues showed substantial decreases in cell wall-associated pectin and hemicellulose under Al stress, excess Fe and co-exposure, potentially limiting Al3+ and Fe2+/Fe3+ binding and mitigating rhizotoxic effects. Al treatment alone suppressed malate and citrate exudation, whereas Fe toxicity increased their release. In contrast, oxalate and phenolics exudation were enhanced by Al and Fe, with maximum excretion under combined exposure. These findings reveal two interaction patterns: additive toxicity affecting chloroplast function, and synergistic enhancement of internal and rhizosphere-based detoxification. Taken together, these findings explain the robust spread of C. communis in acid soils, provide a framework for future research on metal co-tolerance, and may inform acid soil management strategies and the development of stress-resilient cultivars.

Abstract Soil health is central to agroecological transitions, yet guidance for integrating it into agri-food system design and monitoring remains fragmented. Institutions increasingly use frameworks to define indicators, guide interventions, and report progress against climate, biodiversity, and food-security agendas. However, to our knowledge, there is no integrative soil health framework which coherently links biophysical diagnostics, socio-institutional enablers, and multiscale accountability. This leaves critical gaps in design, sequencing, and measurement of agroecological transitions. Here we review how soil health is operationalized within agroecology and agri-food systems and translate these patterns into an actionable programming guide. We reviewed 64 frameworks and extracted 652 indicators across 12 agroecological principles to build a framework-by-principle evidence matrix. Frameworks were classified by use-orientation (theory, practice, analysis), and indicator thematic profiles were analyzed using hierarchical clustering with adaptive branch detection. The major findings are as follows: (1) framework evolution exhibits four chronological waves with shifts from conceptual foundations to operational measurement and outcome reporting, alongside changes in global and regional agenda setting and a rising demand for comparable indicators; (2) clustering identified five soil health design domains separating biophysical and socio-economic principles and revealing stable micro-constellations beyond earlier pathway framing. These include soil management and input stewardship, soil-health assessment, agroecological and ecosystem-based, integrated landscape and livelihood, and policy- and outcome-based. These findings were translated into a sequenced, multi-domain programming architecture that operationalizes complementarity across diagnostics, stewardship implementation, ecosystem safeguards, landscape–livelihood embedding, and iterative learning, thereby closing the gaps between farm practices, governance mechanisms, and outcome monitoring for soil health.

From pollution to action: How soil extraction methods for potentially harmful elements influence human health risk estimates.

Balanced fertilization with nitrogen (N), phosphorus (P), and potassium (K) plays a pivotal role in sustaining maize productivity and shaping soil-microbe interactions. However, the integrated effects of long-term fertilization on crop performance, soil nutrient dynamics, and rhizosphere bacterial communities in purple soils remain unclear. In a 10-year field experiment in purple soil, conducted under a randomized complete block design (RCBD) with three blocks, we evaluated the effects of different fertilization regimes on maize growth and yield, soil physicochemical properties, and bacterial community composition using 16S rRNA gene sequencing. Nitrogen-containing fertilizer treatments (NPK, NK, NP) markedly enhanced grain yield, shoot and root biomass, and root morphological traits compared with unfertilized (CK) and PK treatments, with balanced NPK fertilization delivering the highest performance. Fertilization significantly influenced soil nutrient availability, with NPK maintaining more stable nutrient levels over time. Microbial analyses revealed that rhizosphere communities were more responsive to fertilization than bulk soil communities, with N availability driving diversity shifts and community separation. Key taxa, including Variovorax, Microscillaceae, Lysobacter, and Dyadobacter, were enriched in N-fertilized soils and positively correlated with grain yield and N uptake. Collectively, these findings demonstrate that balanced NPK fertilization, particularly nitrogen input, enhances maize productivity by simultaneously improving soil fertility and fostering beneficial rhizosphere microbial assemblages, offering a basis of sustainable nutrient and microbiome management in purple soil.

Accurate digital mapping of soil classes remains essential for sustainable land management. The DSMART (Disaggregation and Harmonization of Soil Map Units through Resampled Classification Trees) algorithm is a probabilistic soil subgroup mapping technique that utilizes environmental covariates in conjunction with legacy soil data. The objective of this study is to disaggregate soil subgroups from existing 1:20,000 scale soil maps using DSMART in a topographically diverse region of Adana, Türkiye. A total of 231 legacy map units were harmonized and resampled to 20m resolution. A total of 40 soil profiles were collected using a conditioned Latin Hypercube Sampling (c-LHS) design. Predictors were derived from a 5-meter digital elevation model (DEM), and NDVI was derived from 20-meter Sentinel-2 images and legacy soil information. The DSMART algorithm was implemented in R using the "C5.0" decision tree model, producing multiple realizations and subgroup probability surfaces. The accuracy of the model was evaluated using Kappa statistics and Shannon entropy. The most prevalent subgroups, Typic Xerofluvent (Tx), Typic Calcixerept (Tc), and Typic Xerorthent (To), were reliably predicted, particularly in heterogeneous landscapes. Subgroups such as Fluventic Haploxerept (Fh) and Oxyaquic Xerofluvent (Ox) demonstrated elevated uncertainty, attributable to insufficient data representation. For instance, while Typic Calcixerept (Tc), Typic Xerofluvent (Tx), and Typic Xerorthent (To) achieved high accuracies of 96.4%, 90.9%, and 88.7% respectively, Ox exhibited the highest misclassification rate (~ 40%) and Fh could not be reliably predicted due to extremely limited samples. The most significant predictors were found to be elevation and curvature-based topographic indices. The overall model demonstrated an accuracy of 85.2%, and the probability surfaces exhibited smoother transitions in comparison to traditional polygon-based soil maps. The DSMART methodology facilitates the generation of detailed, probabilistic soil maps, thereby exceeding the precision of classical survey techniques by accounting for uncertainty and spatial heterogeneity. The findings of this study contribute to the development of soil management strategies for Mediterranean agricultural regions.

The interaction between vehicle tires and soil is important in various engineering and scientific fields, including agriculture and transportation. This study investigates the dynamics of the tire-soil contact area of an agricultural tire under varying vertical load and multiple passes. This study evaluated the effects of vertical load and tire passes on tire-soil contact area in a soil bin. Experiments were conducted with three vertical load levels (2, 3, and 4 kN) and 15 passes. An imaging system recorded the tire contact areas, and image processing techniques extracted the contact area from the images. Also, a mathematical equation was derived using the learning-based optimization algorithm to model the soil-tire interactions. The optimized model achieved acceptable accuracy and performance, with an R2 of 0.97 and prediction errors (RMSE of 0.0032 and MAE of 0.0027). The developed equation predicts the contact area as a function of vertical load and number of passes. The proposed closed-form model estimates contact pressure without directly measuring the contact area, thereby facilitating its analysis. It provides a framework for future research and practical applications in optimizing tire-soil interactions. Furthermore, this study analyzes tire-soil contact area dynamics, highlighting the importance of managing the initial passes to minimize soil. In conclusion, the proposed contact area measurement techniques and mathematical modeling can enhance understanding of tire-soil interaction theories and facilitate future experimental research in this field. Hence, helping improve soil management practices and vehicle design for off-road applications, ensuring efficiency and sustainability.