Search Results (768)

Soil organic matter (SOM) is a key indicator of arable land quality and the global carbon cycle; accurate regional-scale SOM estimation is vitally significant for sustainable agricultural development and climate change research. This study evaluates a multisource data-fusion approach for improving cropland SOM prediction in Yucheng City, Shandong Province, China. We applied a Local Energy Weighted Discrete Wavelet Transform (LEW-DWT) to fuse multi-temporal Landsat 8 imagery (2014–2023). Quantitative analysis (e.g., Information Entropy and Average Gradient) demonstrated that LEW-DWT effectively preserved high-frequency spatial details and texture features of fragmented croplands better than traditional DWT and simple splicing methods. These were combined with 41 environmental predictors to construct composite Ev–Tn–Mm features (environmental variables, temporal NDVI features, and multi-temporal multispectral information). Random Forest (RF) and Convolutional Neural Network (CNN) models were trained and compared to assess the contribution of the fused data to SOM mapping. Key findings are: (1) Comparative analysis showed that the LEW-DWT fusion strategy achieved the lowest spectral distortion and highest spatial fidelity. Using the fused multitemporal dataset, the CNN attained the highest predictive performance for SOM (R² = 0.49). (2) Using the Ev–Tn–Mm features, the CNN achieved R² = 0.62, outperforming the RF model (R² = 0.53). Despite the limited sample size, the optimized shallow CNN architecture effectively extracted local spatial features while mitigating overfitting. (3) Variable importance analysis based on the RF model reveals that mean soil moisture is the primary single variable influencing the SOM, (relative importance 15.22%), with the NDVI phase among time-series features (1.80%) and the SWIR1 band among fused multispectral bands (1.38%). (4) By category, soil moisture-related variables contributed 45.84% of total importance, followed by climatic factors. The proposed multisource fusion framework offers a practical solution for regional SOM digital monitoring and can support precision agriculture and soil carbon management. Full article

FTIR spectroscopy, attenuated total reflection (ATR), and diffuse reflectance (DRIFT) modalities, along with ICP–AES spectroscopy and correlation analysis, including two-dimensional correlation spectroscopy (2DCOS), were used for the detailed analysis of Kastanozem (chestnut) soils. Microaggregates (20–200 μm) and macroaggregates (200–1000 μm) of characteristic horizons of uncultivated (fallow) and cultivated (arable land) chestnut soils of the same origin were physically fractionated by wet sieving. The combination of these molecular and atomic spectroscopy techniques in combination with correlation analysis was able to find direct correlations between matrix-forming anions and soil organic matter (SOM) of Kastanozems. Humic substances were separated from the corresponding soil samples to reveal SOM contributions more explicitly. Microaggregates of the size fractions of 20–40 μm and 40–60 μm bore the most comprehensive information for both techniques used. Most significant differences between land-use Kastanozem samples were observed in topsoil horizons (arable P versus light-colored humic AJ horizon), and for the next pair of horizons along the profile xerometamorphic BMK horizon to structural metamorphic BM horizon. These differences included carbonate matrix and SOM amounts and composition. Topsoil arable land showed significantly smaller amounts of total organic carbon and a decrease in the share of long-chain hydrocarbons compared to fallow, which has a more distinctive character compared to similar land-use samples of Chernozem. An increase in carbonate contents with soil depth was found for both land-use samples, while the amounts and composition of the silicate matrix remained largely unchanged within the depth profile. The heterospectral 2DCOS comparison of FTIR (between horizons and land-use samples), ICP–AES (between land-use samples), and FTIR–AES (for the same sample) showed the possibility of a more reliable attribution of FTIR absorption bands and revealed the differences in the macro- and micro-aggregate elemental and SOM composition of Kastanozems. Full article

Soil erosion is a major threat to the sustainable productivity of arable lands, making the accurate prediction of soil erodibility essential for effective soil conservation planning. Soil erodibility is strongly controlled by intrinsic soil properties that regulate aggregate resistance and detachment processes under erosive forces. In this study, machine learning (ML) models, including the Multi-layer Perceptron Regressor (MLP), Random Forest (RF), Decision Tree (DT), and Extreme Gradient Boosting (XGBoost), were applied to predict the soil erodibility factor (K-factor). A comprehensive set of soil properties, including soil texture, clay ratio (CR), organic matter (OM), aggregate stability (AS), mean weight diameter (MWD), dispersion ratio (DR), modified clay ratio (MCR), and critical level of organic matter (CLOM), was analyzed using 110 soil samples collected from the northern part of Adana Province, Türkiye. The observed K-factor was calculated using the RUSLE equation, and ML-based predictions were spatially mapped using Geographic Information Systems (GISs). The mean K-factor values for arable, forest, and horticultural land uses were 0.065, 0.071, and 0.109 t h MJ⁻¹ mm⁻¹, respectively. Among the tested models, XGBoost showed the best predictive performance, with the lowest MAE (0.0051) and RMSE (0.0110) and the highest R² (0.9458). Furthermore, the XGBoost algorithm identified the CR as the most influential variable, closely followed by clay and MCR content. These results highlight the potential of ML-based approaches to support erosion risk assessment and soil management strategies at the regional scale. Full article

Chemical soil properties contribute to the resilience of soil ecosystems. Healthy soils with optimal nutrient levels, balanced pH and good organic matter content are better able to withstand environmental stresses, such as drought, disease or pests. When comparing the chemical soil properties of temperate grassland and arable land, several differences can be observed due to differences in soil cover and management. Grasslands typically sequester more carbon, limit nitrogen leaching, and have lower nitrous oxide emissions and losses of phosphorus due to less soil disturbance and a more closed nutrient cycle. In contrast, arable land has higher nutrient losses through harvest, leaching, gaseous emissions and erosion due to regular tillage, frequent bare phases, and sequesters less carbon, typically due to higher mineralisation rates and lower nutrient returns. Monitoring and managing chemical soil properties, appropriate nutrient management, addition of organic matter such as organic fertilisers, inclusion of grassland phases and catch crops in crop rotations, incorporation of crop residues into the topsoil after harvest and further sustainable agricultural practices are essential to promote soil health. By optimising chemical soil properties, farmers and land managers can improve productivity, conserve natural resources and support the long-term sustainability of the soil ecosystem. Full article

Microalgal amendments can improve soil structure by regulating extracellular polymeric substances (EPSs). However, the mechanisms underlying this process in red soils (characterized by high clay content and susceptibility to acidification) under different farming practices remain unclear. This study examined how Chlorella vulgaris (C. vulgaris) amendment influences EPS composition to enhance soil aggregate stability under arable land and rice paddy farming. A five-month pot experiment using a completely randomized design was conducted to investigate the effects of Chlorella vulgaris amendment on soils cultivated with Pennisetum × sinese and rice, two economically important crops commonly grown in South China. At the end of the experiment, Chlorella vulgaris amendment substantially increased both the mean weight diameter (MWD) and geometric mean diameter (GMD) of soil aggregates under both farming systems. Excitation–emission matrix (EEM) fluorescence spectroscopy revealed distinct changes in soil EPS components between the two farming types. Under arable land farming, humic-like and protein-like EPSs were dominant in Chlorella vulgaris-amended treatments, with fluorescence intensities more than doubling compared to the control. Conversely, under rice paddy farming, soil fulvic acid was the main component and showed a moderate increase. Partial least squares path modeling (PLS-PM) demonstrated that protein-like and humic-like EPSs had the strongest direct effects on aggregate stability in arable land red soil, while fulvic acid was the key factor in rice paddy red soil. The present study demonstrates that Chlorella vulgaris amendment improves aggregate stability in red soils through farming-specific, EPS-mediated pathways, providing a quantitative framework for researchers and land managers seeking to apply microalgal amendments for red soil enhancement and sustainable land management. Full article

Soil erosion remains a critical global concern, yet long-term catchment-scale assessments that explicitly link historical land-use transitions with erosion responses remain limited. This study evaluates how ±240 years record of historical and projected land-use changes influence soil erosion in the Myjava Basin by integrating parcel-level land-use reconstructions from 1787 to 2030 into a distributed USLE-2D framework. R, K, and parcel-based C and P factors were temporally standardized, and LS was derived using an ensemble of four widely applied algorithms. A PCA was applied to quantify the relative contribution of RUSLE factors across time, and all analyses were performed within a reproducible geospatial modelling environment. The results indicated a long-term decline in total erosion of ±78% at the landscape scale and ±60% within arable land from the 19th century to the present, driven mainly by a major reduction in arable land (from ±62% to ±37%) and expansion of forest and shrub vegetation. Despite this decline, persistent hotspots remain concentrated on steep upland slopes with high LS (>10%), while agricultural parcels experienced erosion rates 10–20 times higher than the basin-wide mean across all periods. PCA shows that LS and rainfall erosivity dominate erosion variability (PC loadings ±0.78–0.84), while C and P factors increase in influence in recent and projected periods, contributing up to ±40% of total explained variance. These findings demonstrate that long-term land-use transitions have substantially reduced basin-scale erosion risk. Full article

Weeds pose a significant threat to crop yields, both in quantitative and qualitative terms. Modern agriculture relies heavily on herbicides; however, their excessive use can lead to negative environmental impacts. As a result, recent research has increasingly focused on Integrated Weed Management (IWM), which employs multiple complementary strategies to control weeds in a holistic manner. Nevertheless, large-scale adoption of this approach requires a solid understanding of the underlying tactics. This systematic review analyses recent studies (2013–2022) on herbicide alternatives for weed control across major cropping systems in the EU-27 and the UK, providing an overview of current knowledge, the extent to which IWM tactics have been investigated, and the main gaps that help define future research priorities. The review relied on the IWMPRAISE framework, which classifies weed control tactics into five pillars (direct control, field and soil management, cultivar choice and crop establishment, diverse cropping systems, and monitoring and evaluation) and used Scopus as a scientific database. The search yielded a total of 666 entries, and the most represented pillars were Direct Control (193), Diverse Cropping System (183), and Field and Soil Management (172). The type of crop most frequently studied was arable crops (450), and the macro-area where the studies were mostly conducted was Southern Europe (268). The tactics with the highest number of entries were Tillage Type and Cultivation Depth (110), Cover Crops (82), and Biological Control (72), while those with the lowest numbers were Seed Vigor (2) and Sowing Depth (2). Overall, this review identifies research gaps and sets priorities to boost IWM adoption, leading policy and funding to expand sustainable weed management across Europe. Full article

Sustainable food production for a growing population requires farming practices that reduce chemical inputs while maintaining soil as a living, renewable foundation for productivity. This review synthesizes current advances in understanding how endophytic fungi (EFs) interact with the soil microbiome and contribute to the physicochemical and biological dimensions of soil health in arable ecosystems. We examine evidence showing that EFs enhance plant nutrition through phosphate solubilization, siderophore-mediated micronutrient acquisition, and improved nitrogen use efficiency while also modulating plant hormones and stress-responsive pathways. EFs further increase crop resilience to drought, salinity, and heat; suppress pathogens; and influence key soil properties including aggregation, organic matter turnover, and microbial network stability. Recent integration of multi-omics, metabolomics, and community-level analyses has shifted the field from descriptive surveys toward mechanistic insight, revealing how EFs regulate nutrient cycling and remodel rhizosphere communities toward disease-suppressive and nutrient-efficient states. A central contribution of this review is the linkage of EF-mediated plant functions with soil microbiome dynamics and soil structural processes framed within a translational pipeline encompassing strain selection, formulation, delivery, and field scale monitoring. We also highlight current challenges, including context-dependent performance, competition with native microbiota, and formulation and deployment constraints that limit consistent outcomes under field conditions. By bridging microbial ecology with agronomy, this review positions EFs as biocontrol agents, biofertilizers, and ecosystem engineers with strong potential for resilient, low-input, and climate-adaptive cropping systems. Full article

Soil fertility plays a crucial role in crop productivity, particularly in cocoa cultivation, which is highly dependent on soil quality that directly influences both productivity and sustainability. Understanding how to achieve and maintain soil fertility on cocoa farms is fundamental to sustaining higher yields. Cocoa production in Ghana and Togo remains low, at 350–600 kg/ha, compared to the potential yield of over 1–3 tons per hectare. Given the growing demand for cocoa and limited arable land, adequate soil nutrients are essential to optimise productivity. Soil fertility indices (SFIs) have been widely used as soil metrics by integrating multiple physical, chemical, and biological soil properties. In this study, standard analytical methods were employed to evaluate the SFI through laboratory analyses of 49 surface soil samples collected at a depth of 0–30 cm with an auger. Eleven soil chemical indicators were analysed: pH (water), organic matter (OM), potassium (K), calcium (Ca), magnesium (Mg), available phosphorus (P), total nitrogen (N), cation exchange capacity (CEC), electrical conductivity (EC), and carbon-to-nitrogen ratio (C/N). Principal component analysis, followed by normalisation, was used to select a minimum dataset, which was then integrated into an additive SFI. Results indicated that N, Ca, Mg, CEC, and pH were within the optimal range for most surveyed locations (96%, 94%, 92%, 73%, and 63%, respectively), while OM and C/N were within the optimal range in approximately half of the study area. Available P, K, and C/N were highly deficient in 100%, 67%, and 96% of surveyed locations, respectively. Soil fertility varied significantly among locations (p = 0.007) and was generally low, ranging from 0.15 to 0.66. Only 20% of the soils in the study area were classified as adequately fertile for cocoa cultivation. Therefore, it is necessary to restore soil nutrient balance, especially the critically low levels of K and P, through appropriate management practices that improve fertility over time and help close the yield gap. Full article

In precision agriculture, the delineation of Management Zones (MZs) is essential for optimizing input use efficiency and site-specific nutrient management. MZs are established based on spatial variability derived from remote sensing data—such as Normalized Difference Vegetation Index (NDVI) from satellite or UAV-based imagery—and yield maps collected during harvest. However, the microbial community composition of the soil is often overlooked in MZ delineation. To address this gap, we investigated the soil bacterial community structure across different MZs in an arable field. The zones were delineated using NDVI data, soil profiles were described, and bulk soil samples were collected. Soil physicochemical parameters were analyzed in parallel with 16S rRNA gene amplicon sequencing to characterize bacterial community composition and diversity. The results demonstrated that soil texture and soil organic matter content were the primary drivers influencing bacterial community structure across the field. Moreover, patterns in microbial composition aligned closely with MZ delineations, indicating that microbial profiles could aid in better understanding and supporting the nutrient management practices. Our findings suggest that soil microbiological data can enhance the stability and biological relevance of MZ definitions, thereby improving resource allocation, soil health management, and overall sustainability in precision farming systems. Full article

Rice (Oryza sativa L.) is one of the most important crops globally. However, its production faces significant challenges due to climate change, reduced arable land, and increased demand. In this context, the present study conducted a systematic literature review (SLR) on technological advances in rice production in Latin America. Recognized scientific databases were consulted, and rigorous inclusion and exclusion criteria were applied to synthesize current knowledge on the subject. The results show that the main innovations include genetically improving varieties with greater resistance to biotic and abiotic stresses; implementing advanced water management techniques, such as intermittent irrigation; and applying biofertilizers and organic amendments to improve soil fertility. Additionally, precision agriculture tools, such as remote sensing and artificial intelligence-based modeling, have optimized crop monitoring and input efficiency. Brazil, Mexico, and Colombia are the main generators of rice production technologies in the region. Despite the progress made, challenges remain regarding the adoption of these innovations by producers, highlighting the need for comprehensive policies to facilitate technology transfer. This review establishes a foundation for researchers and policymakers interested in the sustainable development of rice production in Latin America. Full article

The European Union produces about 58 million tons of grain maize annually, and although Slovakia contributes only a small share, grain maize is an important crop occupying 10.6% of the country’s arable land. A two-year pot experiment was conducted to evaluate the effects of vermicompost (Vc) dose and application timing, applied alone or in combination with mineral nitrogen fertilizer, on maize grain yield and selected grain-quality parameters. The spring pre-sowing Vc application at 170 kg ha⁻¹ total N proved appropriate. Increasing the Vc dose from 170 to 340 kg ha⁻¹ total N did not significantly influence grain yield, thousand kernel weight (TKW), or the contents of crude protein and starch. When soil was fertilized with Vc in autumn, the spring application of mineral N at 60 kg ha⁻¹ resulted in higher grain yield compared with the spring application of Vc at 170 kg ha⁻¹ total N. Application of Vc alone, regardless of dose or timing, did not affect starch content or TKW. The combined use of mineral and organic nitrogen sources appears to be the most effective strategy for maize nitrogen nutrition. Applying Vc in autumn or spring at 170 kg ha⁻¹ total N, followed by 60 kg ha⁻¹ mineral N in spring, created favorable conditions for achieving high grain yield and quality. Full article

Effective implementation of silvopastoralism, a key Nature-Based Solution for Europe’s climate goals, is hindered by a lack of decision-support tools clarifying trade-offs between efficiency and extent of carbon sequestration. To address this, we developed a multi-objective scenario analysis (4064 scenarios) to identify optimal strategies for silvopastoral expansion across the EU27 Mediterranean bioregion. We found an inverse relationship defining a clear trade-off: scenarios achieving the highest mean sequestration (up to 2.5 Mg CO₂ ha⁻¹ year⁻¹) are spatially limited, whereas those maximising total gains (approaching 10⁷ Mg CO₂ year⁻¹ in total) do so by incorporating vast areas, lowering mean rates. This trade-off is formalised by a Pareto front, from which we defined a best-balanced optimal scenario and three policy regimes (conservative, balanced, expansive). Progressing across the front involved shifting from converting primarily shrubby and sparsely vegetated lands to incorporating grasslands and mixed agro-systems. At the NUTS2 level, Spain and Greece emerged as hotspots. Notably, converting arable land was not a primary contributor to carbon gains, as the marginal carbon benefit on these productive soils is lower than on marginal lands due to their higher baseline soil carbon levels, indicating that large-scale implementation can focus on marginal lands to avoid conflicts with food security. While subject to uncertainties of the underlying land-use and carbon models, this analysis demonstrates that our framework enables policymakers to select spatially explicit strategies aligned with specific budget or sequestration goals. These insights can inform CAP eco-schemes and national LULUCF strategies. The resulting maps and code are freely available. Full article

The transfer price of land management rights, as a key component of deepening rural reform at the 20th National Congress, profoundly influences the direction of agricultural production. Analyzing the land transfer management rights price differences can provide a deep understanding of regional transfer patterns and promote efficient land transfer. This study employs the SES framework to investigate factors of land transfer price differences by integrating correlation regression with the Boosted Regression Tree model. The results showed that (1) resource units determine land transfer management rights prices, with agricultural output value and net arable land income serving as core determinants. (2) City W is in the nascent land market, where the resource systems (RS) exert stronger influence. Key drivers include the transportation accessibility index and the proportion of flexible land. Compared to County K, where the land market exhibits full competition, the primary drivers of price shift from the resource systems to the governance systems and actors. Land transfer participants and the number of rural economic organizations become the main factors. Within the same Eastern black soil region, the transfer price differed by several thousand yuan per hectare. This disparity stems from differences in the two driving structures, necessitating the precise implementation of land transfer policies. Full article

Soil health is vital for the stability of agricultural production and ecosystem functions. However, the rapid urbanization process and environmental pollution have led to a sharp reduction in available arable land and accelerated soil degradation. Meanwhile, human activities generate a large amount of waste, which needs to be treated for resource recovery to reduce its potential pollution risks to the environment. By upcycling waste to mimic pedogenesis, Technosols offer a sustainable platform for land rehabilitation, environmental remediation, carbon sequestration and greenhouse gases emission reduction. However, the wide range of waste sources and complex compositions pose challenges to the standardized construction of Technosols suitable for agricultural production. This review systematically examines the sources and characteristics of waste, current utilization status and challenges in Technosol construction, and puts forward suggestions for developing agriculture-oriented Technosols through waste-novel nanomaterial composites. Finally, critical research directions are proposed regarding the relationship between Technosol fabrication and farmland environmental effects, including the targeted design, nanomaterial-enhanced construction, ecological impact assessment, and economic efficiency of agricultural Technosols. Full article