Geoderma Regional最新文献

{"title":"Mapping soil fertility properties in central Ethiopia at 100 m spatial resolution","authors":"Musefa A. Redi ,&nbsp;Gerard B.M. Heuvelink ,&nbsp;Johan G.B. Leenaars","doi":"10.1016/j.geodrs.2025.e00952","DOIUrl":"10.1016/j.geodrs.2025.e00952","url":null,"abstract":"<div><div>Accurate soil property maps are essential for effective soil nutrient management. In Ethiopia, fertilizer applications often ignored spatial variability in soil properties, leading to inefficiencies. This study employed digital soil mapping to generate three-dimensional (3D) maps of five key soil fertility properties—total nitrogen (TotalN), extractable phosphorus (OlsenP), exchangeable potassium (ExchK), pH-H₂O (pH), and organic carbon (OC)—at 100 m resolution across central Ethiopia. The objectives were to (1) develop maps at six depth intervals while assessing prediction uncertainty; (2) evaluate the integration of topsoil data with soil profile data for model training; and (3) compare the maps with Africa-SoilGrids, SoilGrids, and iSDAsoil maps. We used two datasets: soil profile (1,379 profiles with 4,179 layers) and topsoil (13,724 locations), harmonized with transfer functions. Quantile regression forest was used to generate maps with 90 % prediction intervals. Models were calibrated with 80 % of the dataset and 194 covariates, including depth, and evaluated with the remaining 20 %. Integrating topsoil data with the soil profile dataset improved prediction accuracy for the five soil fertility properties in the topsoil (0–20 cm), demonstrating near-zero bias, reduced root mean squared error, and a higher model efficiency coefficient (MEC), compared to only using the soil profile dataset. It also enhanced uncertainty quantification for pH, OlsenP, TotalN, and ExchK in the topsoil. However, these benefits diminished with depth, with slight improvements in the subsoil (20–50 cm) but none in the deeper layers (50–200 cm) where pH and OC predictions were even slightly biased. Among the combined dataset models, the highest performance was for pH (MEC = 0.80), while the lowest was for OlsenP (MEC = 0.13). The maps generated from the combined dataset models showed MEC improvements of 27 % to over 1,000 % compared to SoilGrids, Africa-SoilGrids, and iSDAsoil. Additionally, the prediction intervals were also a realistic representation of the prediction uncertainty, with prediction interval coverage probability (PICP) values close to their ideal value. This markedly outperformed SoilGrids and iSDAsoil, which had unrealistically low PICP values. We conclude that the 100 m resolution 3D maps from this study offer satisfactory accuracy and realistic uncertainty quantification, making them the currently best available resource for developing location-specific fertilizer recommendations in central Ethiopia.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"41 ","pages":"Article e00952"},"PeriodicalIF":3.1,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil conductance classification for crop performance assessment using electromagnetic induction and geospatial techniques in coastal region of Indian Sundarbans","authors":"Manoj Kumar Nanda ,&nbsp;Sukanta Kumar Sarangi ,&nbsp;Mark Glover ,&nbsp;Debolina Sarkar ,&nbsp;Argha Ghosh ,&nbsp;Momsona Mondal ,&nbsp;Jorge Pena-Arancibia ,&nbsp;Mohammed Mainuddin","doi":"10.1016/j.geodrs.2025.e00951","DOIUrl":"10.1016/j.geodrs.2025.e00951","url":null,"abstract":"<div><div>Sustainable crop production in the coastal zone of the Indian Sundarbans presents a significant challenge due to seasonal salinity build-up, particularly during the post-monsoon season. The measurement of apparent electrical conductivity (ECa) of soil using electromagnetic induction (EM) technique has emerged as a popular method for rapidly assessing soil salinity, serving as a proxy for traditional cost and labour-intensive laboratory analysis methods. This study investigated two test sites, Bijoynagar (9.24 ha) and Sonagaon (9.69 ha), to assess the spatial pattern of ECa at four depths of exploration (DOE)- 30 cm, 50 cm, 80 cm, and 160 cm below the surface using the DualEM-1HS. The measured ECa data were interpolated using Ordinary Kriging (OK) to get contiguous grid layers of ECa at respective depths which are subsequently classified into six Soil Conductance Units (SCUs) using K-means clustering technique. The Bijoynagar site, where mung beans and a few other vegetables were cultivated in the rice fallow during the survey recorded lower ECa than the Sonagaon site. The major part of the Sonagaon site was laid fallow during the survey, with patches of summer rice grown sporadically. The coefficient of variation of ECa within each SCU was most pronounced at the surface level (up to 30 cm depth), which was often influenced by agricultural practices such as tillage and irrigation. Strong correlations were observed between the laboratory-measured electrical conductivity of soil-water suspensions (ECe) and the cluster numbers, as evidenced by a high Spearman Rank Correlation coefficient (0.905). The ECa of the crop rhizospheric layer (surface to 50 cm depth) exhibited the highest correlation coefficients for mung bean stover yield, biomass yield, and rice grain yield. Spearman rank correlations between cluster numbers and the yield of summer rice and mung beans grown in different SCUs were also significant at the 5 % level. The investigation of the electromagnetic induction approach for assessing apparent soil conductivity has been crucial in understanding local fluctuation of soil salinity and its impact on performance of the two major crops grown in the Sundarbans. The improved EM survey involving hand-held GPS and Android application ‘GeoTracker’ followed by geostatistical analysis, and clustering in open-source GIS platform customized in this study offers a robust package of practices that enabled quick, precise and effective classification of land into Soil Conductance Units for site specific crop management in the coastal saline region of Indian Sundarbans.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"41 ","pages":"Article e00951"},"PeriodicalIF":3.1,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes in soil organic carbon and phosphorus status under three different land use systems in a tropical Ultisol","authors":"M.D.P. Nayanarangani ,&nbsp;U.W.A. Vitharana ,&nbsp;D. Kumaragamage ,&nbsp;N.J. Casson","doi":"10.1016/j.geodrs.2025.e00950","DOIUrl":"10.1016/j.geodrs.2025.e00950","url":null,"abstract":"<div><div>Anthropogenic land use systems and their management practices influence carbon (C) accumulation and storage and phosphorus (P) dynamics in soils. However, information on changes in soil organic C (SOC) reserves and P status in intensive annual cropping versus commercial perennial cropping systems is limited. This study examined the impact of long-term annual (vegetable) and perennial (tea) cultivation on the soil P and SOC status of a Tropical Ultisol compared to replanted forest land use. Surface (0–15 cm) soil samples obtained from forest- (25 ha), tea- (20 ha), and vegetable- (30 ha) lands within a micro-catchment were analyzed for available P (Mehlich 3-P), P fractions, SOC, permanganate oxidizable C (POxC, representing active SOC), and pH. Soils under long-term vegetable and tea with frequent applications of fertilizers had 78-fold and 7-fold greater available P (356.3 and 33.0 mg kg⁻¹, respectively) than forest (4.6 mg kg⁻¹) soils. Moreover, vegetable-grown soils had greater P concentrations in labile, moderately labile, and recalcitrant fractions than tea-grown and forest soils. Active C fraction in tea-grown soils (899 mg kg-1) was 2-fold than that of vegetable-grown soils (484 mg kg⁻¹), but similar to forest soils (804 mg kg⁻¹). The SOC in tea-grown and forest soils were similar (6.05 % and 5.84 %, respectively), but significantly higher than in vegetable-grown soil (4.50 %). Thus, soils from intensive annual cropping systems showed substantial P accumulations and lower SOC quantity and quality than perennial cropping systems, warranting better nutrient and SOC management and soil conservation measures to prevent further soil deterioration with annual cropping.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"41 ","pages":"Article e00950"},"PeriodicalIF":3.1,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143684806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of parent material and land use on abiotic N2O production following NH2OH and NO2− addition","authors":"Suyun Li ,&nbsp;Cai Gan ,&nbsp;Danni Cai ,&nbsp;Jiani Ma ,&nbsp;Gaochao Cai ,&nbsp;Shurong Liu","doi":"10.1016/j.geodrs.2025.e00944","DOIUrl":"10.1016/j.geodrs.2025.e00944","url":null,"abstract":"<div><div>Abiotic pathways, closely linked to soil physicochemical characteristics shaped by parent material and land management practice, may significantly contribute to nitrous oxide (N₂O) emissions. However, the mechanisms by which parent materials and land use types influence abiotic N₂O production from hydroxylamine (NH₂OH) and nitrite (NO₂⁻) remain unclear. This study analyzed fifteen acidic soils representing three parent materials and five land use categories. Our results indicated that while land use had minimal effect, parent material did show significant influence on abiotic N₂O production, particularly noticeable after NH₂OH application (<em>P</em> &lt; 0.05). Soils derived from Quaternary red clay exhibited the highest abiotic N₂O production (2.55 μg N₂O-N g⁻¹ soil), approximately fivefold greater than granite-derived soils. This increase correlated with the higher manganese (Mn) content in Quaternary red clay soils, which enhanced abiotic N₂O production through NH₂OH decomposition. Additionally, the conversion ratios of NH₂OH to N₂O were substantially different among the soil parent materials, varying from 56.6 % in Quaternary red clay to 12.7 % in granite and 40.8 % in late Pleistocene sediment. The isotopic site preference (SP) values of N₂O were within the expected ranges that typify both ammonia oxidation and chemodenitrification processes, with NH₂OH and NO₂⁻ addition yielding SP values of 25–30 ‰ and around 20 ‰, respectively. These findings underscore the pivotal role of parent material in regulating abiotic N₂O production, particularly through NH₂OH decomposition, and highlight the importance of soil properties in mediating abiotic N₂O emissions.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"41 ","pages":"Article e00944"},"PeriodicalIF":3.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143632060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating terrestrial and orbital reflectance data improves the soil attribute modeling performance","authors":"Jean Jesus Macedo Novais ,&nbsp;Jorge Tadeu Fim Rosas ,&nbsp;Nícolas Augusto Rosin ,&nbsp;Uemeson José dos Santos ,&nbsp;Marilusa Pinto Coelho Lacerda ,&nbsp;José Alexandre Melo Demattê","doi":"10.1016/j.geodrs.2025.e00945","DOIUrl":"10.1016/j.geodrs.2025.e00945","url":null,"abstract":"<div><div>A comprehensive understanding of soil attributes is crucial for effective environmental management. Geotechnologies offer an alternative to traditional soil surveying methods. This study evaluated the potential of multispectral data from terrestrial and orbital sensors to predict soil attributes of Rhodic Ferralsols in Central Brazil using machine learning algorithms. Physicochemical and spectral attributes of 37 soil samples (0–20 cm depth) were collected and analyzed. Spectral signatures were extracted from visible to shortwave infrared using the ASTER, a satellite-based sensor providing multispectral data, for comparison to laboratory hyperspectral data from Fieldspec Pro 4, and resampled to ASTER bands. Random Forest (RF) and Multiple Linear Regression (MLR) modeled the soil attributes using the spectral libraries, individually and combined. Results showed similar spectral responses between the sensors, indicating that resampling hyperspectral data from terrestrial sensors can be a reliable reference for orbital data. Due to controlled conditions and reduced interference from moisture and atmosphere, the terrestrial sensor and combined approaches had a higher Pearson correlation with soil attributes than the orbital sensor. MLR with combined sensors effectively predicted soil attributes, achieving R² of 0.65 for clay and 0.69 for organic matter. RF showed lower performance, with R² of 0.32 for base saturation and 0.30 for Cation Exchange Capacity, attributed to limited datasets. Combining terrestrial and orbital sensors improves soil attribute modeling, nevertheless, it requires robust sampling, image processing, and sensors testing, datasets, and algorithms. This study highlights the potential of integrating multilevel remote sensing for efficient soil analysis and mapping, contributing to sustainable environmental management.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"41 ","pages":"Article e00945"},"PeriodicalIF":3.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143684807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The carbon credit conundrum: Which analytical method should be used for determining soil organic carbon content in South Africa?","authors":"Willie Herman Cloete,&nbsp;Gerhard du Preez,&nbsp;George Munnik Van Zijl","doi":"10.1016/j.geodrs.2025.e00947","DOIUrl":"10.1016/j.geodrs.2025.e00947","url":null,"abstract":"<div><div>Accurate quantification of soil organic carbon (SOC) content is essential for the assessment of carbon credits. In South Africa, the standard methodologies for carbon credit assessment does not specify which analytical method should be used for determining SOC content. The study aimed to determine which analytical method should be used for determining SOC content for the assessment of carbon credits. Secondly, it determined whether pedotransfer functions could be used for transferring SOC content values between methods. Two-hundred-and-twenty topsoil (0–30 cm) samples were collected and analysed for SOC content with the three analytical methods: Walkley-Black wet-oxidation (WB), total dry combustion (TDC) and loss-on-ignition (LOI). The study found that the TDC method should still be considered the preferred method for determining SOC content for the assessment of carbon credits in South Africa. The WB method should be avoided if a soil is expected to have a high SOC content, while the LOI method could still be used for determining SOM, however, this method should be avoided when determining SOC content. The study also reached the second aim by successfully creating pedotransfer functions between all three methods. However, only the WB and TDC methods had a very strong relationship (R² = 0.91) and showed that accuracy start to decrease significantly after 2.5 % SOC content. Therefore, the pedotransfer function (SOC_WB = −0.157 + 0.895 x SOC_TDC – 0.0149 x SOC_TDC²–0.000606 x SOC_TDC³) could be used for transferring SOC content values with SOC content up to 2.5 %.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"41 ","pages":"Article e00947"},"PeriodicalIF":3.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Origin and rupture of a podzolized pedological system in the dissected coastal tablelands of the North coast of the state of Bahia","authors":"Alisson D. Diniz ,&nbsp;Jéssica Da M. Lima ,&nbsp;Célia R. Montes ,&nbsp;Junia K. Guimarães","doi":"10.1016/j.geodrs.2025.e00940","DOIUrl":"10.1016/j.geodrs.2025.e00940","url":null,"abstract":"<div><div>The North Coast of the State of Bahia is known for having a diversity of ecosystems and landscapes. However, these ecosystems, located on dunes, marine terraces and coastal tablelands, are very fragile and targeted by tourist developments in the region, making them even more vulnerable to environmental degradation. This fragility comes mainly from the sandy geomorphological surfaces and features, covered by pioneer plant formations. Research in the Coastal Tablelands has shown that the origin of sandy soils with low fertility and high erodibility, especially the Spodosols, is the result of a podzolization process of the lateritic soils in the Coastal Tablelands. However, there are areas where podzolization may have occurred in allochthonous and previously sandy surface formations, such as eolian and fluvial deposits. In addition, the dissection of the Coastal Tablelands has eroded the podzolized surfaces and exposed the Barreiras Formation facies that form soils as fragile as the Spodosols - the Inceptisols. Thus, the aim of this research was to characterize and identify the origin of a Quartzipsamment - Spodosol pedological transformation system, interrupted by a low-slope Inceptisols, in an area of Dissected Coastal Tablelands on the North Coast of Bahia. The construction of a toposequence, combined with geophysical studies and the collection of morphological, chemical and physical soil data, as well as fourier transform infrared (FTIR) analysis of the samples collected, produced data that supported discussions and interpretations on the pedogeomorphological evolution of the slope studied. Thus, the results indicated that the podzolization process occurred in allochthonous sandy deposits, given the high vertical lithological discontinuity presented in the profiles of the upper slope sector of the toposequence. On the other hand, the Quartzipsamment and Spodosol of this sector showed lateral links and a break with the low slope sector which, from the incision of the Coastal Tablelands, formed the Inceptisol on the lower slope over underlying facies of the Barreiras Formation.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"40 ","pages":"Article e00940"},"PeriodicalIF":3.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National baseline high-resolution mapping of soil organic carbon in Moroccan cropland areas","authors":"Abdelkrim Bouasria ,&nbsp;Yassine Bouslihim ,&nbsp;Rachid Mrabet ,&nbsp;Krishna Devkota","doi":"10.1016/j.geodrs.2025.e00941","DOIUrl":"10.1016/j.geodrs.2025.e00941","url":null,"abstract":"<div><div>Soil organic carbon (SOC) plays a critical role in enhancing soil fertility, improving water retention, and contributing to global carbon sequestration and thereby supporting climate action. In Morocco, previous SOC mapping efforts have relied largely on traditional methods that fall short in capturing SOC's spatial variability due to data quality, availability, and extrapolation errors. This study aims to create the first national baseline SOC map for cropland using digital soil mapping techniques. Three machine learning (ML) models—Random Forest (RF), XGBoost, and LightGBM were compared to assess SOC spatial variability at 250-m resolution in Moroccan croplands. Recursive Feature Elimination was used to optimize model performance by selecting the most relevant predictors from 83 environmental covariates, including soil properties, climatic and hydrological factors, vegetation indices, and anthropogenic activities. The models were calibrated and validated using 9926 georeferenced samples from 0 to 30 cm soil depth alongside environmental data. Validation results demonstrated satisfactory predictive performance of ML models in SOC prediction, with RF achieving the highest accuracy (R² = 0.41; RMSE = 0.43 %) and demonstrated low uncertainty, slightly outperforming XGBoost and LightGBM, which both achieved R² = 0.39 and RMSE = 0.43 %. On the other hand, the created SOM map for Moroccan croplands displayed limited alignment with the global SOC dataset (SoilGrids), suggesting that this later is less appropriate for capturing local soil properties. These findings establish a foundational baseline SOC map for Moroccan croplands, providing detailed insights into spatial variability. The results support the recent policies aiming development of sustainable agricultural strategies, soil conservation efforts, and climate change mitigation through improving the in-depth understanding of soil carbon dynamics at various scales.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"40 ","pages":"Article e00941"},"PeriodicalIF":3.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using near-infrared spectroscopy as a cost-effective method to characterise soil and leaf properties in native forest","authors":"V.E. Álvarez ,&nbsp;J.A. Arias-Rios ,&nbsp;V. Guidalevich ,&nbsp;P. Marchelli ,&nbsp;P.A. Tittonell ,&nbsp;V.A. El Mujtar","doi":"10.1016/j.geodrs.2025.e00948","DOIUrl":"10.1016/j.geodrs.2025.e00948","url":null,"abstract":"<div><div>Forests conservation and sustainable management of forests require an understanding of ecological traits that influence carbon and nutrient turnover in forest ecosystems. This study evaluates the potential of Near Infrared Spectroscopy (NIRS) as a rapid, non-destructive and cost-effective tool for characterising soil and trees in natural forests and forest-frontier ecosystems. Soil samples were collected at four depths from three land uses (native forest, grazed grassland, and horticultural land), while leaf samples were obtained from two provenances of <em>Nothofagus alpina</em>. Spectra were used to classify samples, predict biological and chemical properties, estimate relatedness matrices for both soils and leaves and compared them with those obtained from genetic data. Principal component analysis separated soil samples from different land uses and depths as well as leaf samples from the two provenances. NIRS-based models showed high predictive accuracy for soil microbial biomass, biological activity and total carbon (R² = 0.80, 0.94, and 0.86, respectively), although leaf pigment estimation was less reliable (R² = 0.60–0.40). Correlations between genetic and NIRS relatedness matrices were low, highlighting that both methodologies are relevant for sample characterisation. These findings demonstrate that NIRS is a useful method for assessing soil ecological traits associated with nutrient cycling offering a practical and cost-efficient alternative for ecological monitoring in forest ecosystems. However, further methodological improvements are needed to enhance its accuracy, particularly for leaf traits characterisation. This study highlights the broader potential of NIRS for large-scale forest management, conservation strategies, and ecological research.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"40 ","pages":"Article e00948"},"PeriodicalIF":3.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-term effects of winter cover crops and summer cash crops on soil properties in Ultisol under no-tillage system in Southern Brazil","authors":"Gustavo Nogara de Siqueira ,&nbsp;Tadeu Luis Tiecher ,&nbsp;Lucas Aquino Alves ,&nbsp;Adriele Tassinari ,&nbsp;Douglas Luiz Grando ,&nbsp;Gerson Laerson Drescher ,&nbsp;Gustavo Brunetto ,&nbsp;Rafael Ziani Goulart ,&nbsp;Vinicio Bordignon ,&nbsp;Tales Tiecher","doi":"10.1016/j.geodrs.2025.e00935","DOIUrl":"10.1016/j.geodrs.2025.e00935","url":null,"abstract":"<div><div>Growing winter cover crops in rotation with summer cash crops in a no-tillage (NT) system improves soil's physical and chemical properties. However, the short-term effects of cover crops on sandy soils in subtropical climates remain poorly understood. A two-year study investigated how winter cover crops and summer cash crops (corn - <em>Zea mays</em> and soybean - <em>Glycine Max</em>) affect Ultisol physical and chemical properties under NT in Southern Brazil. A corn and soybean production system was established with fallow and three winter cover crops: black oat (<em>Avena strigosa</em>), vetch (<em>Vicia sativa</em>), and forage radish (<em>Raphanus sativus</em>). The study analyzed crop yield and selected soil physical properties (soil density, total porosity, macroporosity, microporosity and water infiltration rate) and chemical properties (soil water pH; Ca–Mg–K saturation; Al saturation; exchangeable Ca and Mg; available P and K; effective CEC; CEC_pH7.0; and potential acidity). Cover crops did not affect corn and soybean yields in relation to the fallow system. Soil macroporosity in the 0–10 cm layer was 34 % greater in soybean subplots than in corn subplots. Corn cultivation resulted in higher soil pH_H2O, Ca–Mg–K saturation, and lower Al saturation in the 20–40 cm layer compared to soybean, indicating lower soil acidification. Winter cover crops, especially forage radish, reduced soil acidification, and increased soil Ca and K contents, whereas winter fallowing increased soil acidity by 86 % and reduced overall soil fertility. These results indicate that cover crops play a key role in no-tillage production systems, improving soil fertility and reducing soil acidity.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"40 ","pages":"Article e00935"},"PeriodicalIF":3.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}