Soil & Tillage Research最新文献

Arable soils may play an important role in climate mitigation actions as soil management directly affects carbon (C) sequestration and mineralisation. To evaluate the C sequestration potential in hilly terrain it is essential that not only changes in vertical C fluxes (more C input and/or reduced mineralisation), but also lateral soil organic carbon (SOC) redistribution due to erosion processes are considered. Tillage has been identified as an important contributor to soil translocation processes and a modulator of SOC dynamics. Nevertheless, the focus of most studies dealing with SOC redistribution still lies on water erosion. Therefore, the aim of this study is to assess the impact of tillage erosion on C fluxes in the intensively cultivated loess region (200 ha) in the Czech Republic. The coupled water and tillage erosion and C turnover model SPEROS-C was used to analyse the effect of six decades of erosion/deposition upon C fluxes, whereas a specific focus was set on the importance of tillage erosion processes. The results indicate that tillage erosion (TIL) is an important driver of C dynamics in the study area, especially at slope shoulders where a substantial decline in SOC was modelled. Water erosion (WAT) is the most dominant process in the region. However, the model results reveal an increase in erosion-induced C sequestration potential by 37 % after 60 years of simulation when effect of TIL is considered. Moreover, it is interesting that TIL reduced the total sediment delivery from the monitoring site via a change in topsoil SOC patterns. In other words, tillage lowered water erosion-induced sediment transport. Overall, considering the overlooked impact of tillage erosion led to a substantial shift in the role of soil erosion on SOC dynamics. The climate mitigation measures based on adapted agricultural management to increase SOC sequestration are often in-line with soil conservation measures. Our results indicate that such an adaptation might be less effective as the erosion-induced C sink effect declines.

This study evaluates the temporal stability of X-ray fluorescence (XRF) models for predicting plant-available calcium (av-Ca) and potassium (av-K) in a tropical agricultural field under changing soil management. Understanding this stability is crucial for advancing XRF as a quick and clean tool for soil nutrient monitoring. XRF models were tested across six sampling periods (2015, 2019, 2020, and three in 2022); lime and potash rock powder were applied before 2022 samplings to assess the XRF models response to amendments, which altered the ratio of total to plant-available nutrients (T/A ratio). We evaluated a simple model (M15) calibrated using only samples acquired in 2015 (S15), and two time-specific models (M15+SS and SS models) that incorporate samples collected at each analysis period. All models showed temporal stability when the T/A ratio was consistent, with RMSE values of 3.15─6.95 mmol_c dm⁻³ (1.91 ≤ RPIQ ≤ 4.22) for av-Ca and 1.20─1.64 mmol_c dm⁻³ (1.86 ≤ RPIQ ≤ 2.55) for av-K. However, the application of lime and potash rock powder disrupted the T/A ratio for Ca and K, reducing all models accuracy, with M15’s RMSE increasing to 10.78─40.64 mmol_c dm⁻³ (0.33 ≤ RPIQ ≤ 1.23) for av-Ca and to 1.86─6.37 mmol_c dm⁻³ (0.48 ≤ RPIQ ≤ 1.64) for av-K. Although time-specific models improved accuracy compared to M15, they require frequent recalibration. Overall, XRF models can reliably predict plant-available Ca and K over time if soil management maintains a consistent T/A ratio. This study underscores the need to consider soil amendments when applying XRF models for nutrient monitoring and contributes to the theoretical basis for using XRF in agricultural management.

The bionic design of soil-engaging components has recently received much attention in conservation tillage and is extremely important for reducing tillage resistance and increasing implement passability in wet-adhesive rice paddy soil. In this paper, to reduce adhesion and resistance of rotary tillage in wet-adhesive soil, a novel imitating pangolin scale structure is first proposed, and the bionic non-smooth surface parameters affecting the soil adhesion effect is clarified. Afterwards, based on the JKR attached Bonding contact model, an accurate discrete element interaction model of the designed rotary tillage blade -wet adhesive soil is established, and the effect of spindle speed, bump size and bump distance on the tillage resistance and soil disturbance is analyzed using the proposed model. Finally, the proposed imitating pangolin scale structure is optimized to improve the anti-adhesive and drag reduction properties using response surface method, furthermore, the corresponding model validation experiments and field tests are also conducted. Results reveal that the relative errors between the simulated and experimental values of the bionic blade rotary torque and soil adhesion mass are only respectively 4.4 % and 8.3 %. In addition, the optimal parameter combinations of anti-adhesion and drag reduction are also determined: the spindle speed is 180 rpm, the bump width is 10.6 mm and the bump distance is 17.9 mm, respectively, at the time, the effect of soil breaking of the designed blade is reduced by 9.95 % compared to that of the traditional blades but the effect of anti-adhesion and drag reduction is improved by 18.81 %.

Restoring vegetation is an effective way to control regional erosion as well as reduce soil erodibility. However, it is not clear how the vegetation restoration duration affects soil erodibility and how it further influences soil erosion processes. Therefore, the soil physicochemical properties and comprehensive soil erodibility index (CSEI) at five sampling sites with 3, 20, 55, 80 and 100 years of vegetation restoration were investigated in this study. A simulated rainfall with intensities of 60, 90, and 120 mm h⁻¹ was conducted on three slopes with gradients of 10°, 20°, and 30° by using rare earth element oxides (Ho₂O₃ and Sm₂O₃) as tracers to quantify interrill and rill erosion. The results revealed a decreasing trend in both the CSEI and sediment concentration with increasing vegetation restoration duration. Compared to that at the site with 3 years of vegetation restoration, the CSEI at the sites with 20, 55, 80, and 100 years of restoration was reduced by 35.2 %, 39.7 %, 92.8 %, and 67.1 %, respectively. Interrill erosion dominated the hillslope erosion processes and contributed more than 76.9 % to the total erosion amount. By comparing the measured and estimated erosion rates using the equations provided by the Water Erosion Prediction Project (WEPP), significant prediction errors were found. Therefore, relationships among the CSEI, slope gradient and rainfall intensity were established for interrill and rill erosion rate estimation in vegetation restoration areas. This study provides a theoretical basis for evaluating the soil and water conservation benefits of vegetation restoration and for improving soil erosion prediction models within the context of vegetation restoration.

Understanding and controlling rhizospheric processes under abiotic stress is one of the key challenges in addressing food security amid the climate crisis. In this work, the impact of short-term drought and overwatering on soil organic matter (SOM) of Haplic Chernozem in the rhizosphere of Poa pratensis L. and in bulk soil was investigated. The vegetation experiment was conducted in a climatic chamber at soil moisture levels of 35, 80, and 200 % of the field capacity. UV-Vis and spectrofluorometry were used to describe the water-extractable organic matter (WEOM) characteristics and fluorofores signature, and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) to describe functional group composition of SOM. Composition and properties of SOM and WEOM of Chernozem significantly change after exposure to short-term water stress. Drought does not affect the composition of rhizosphere SOM except increasing the proportion of polysaccharides, but leads to the decrease in aromaticity and increase in molecular weight of humic-like components of rhizosphere WEOM. These findings reflect Poa adaptation to water deficiency and microbial activity suppression which results in accumulation of SOM intermediate decomposition products. On the contrary, bulk WEOM wasn't affected by drought but SOM became enriched with aromatic and oxidised components. Overwatering leads to equalisation of bulk and rhizospheric SOM composition due to a decrease in the proportion of aromatic and carboxylic components of bulk SOM and the accumulation of microbial products in both bulk and rhizospheric SOM. In general, rhizospheric WEOM undergoes relatively significant changes relative to the optimum water regime under moisture deficit, and bulk WEOM — under overwatering. The findings illustrate the involvement of the both WEOM and SOM in maintaining resilience of the soil-plant system as well as the difference in watering conditions impact on SOM in rhizosphere and bulk soil. SOM spectral data can be used for assessing the state of soil systems, such as changes in microbial activity and adaptation of the soil-plant system to abiotic stress. Our findings also illustrate the differences in the organic matter transformation of the Poa pratensis rhizosphere and the bulk Chernozem depending on environmental factors.

In the coastal plain region of the United States, conservation agriculture practices are being implemented to improve soil health, minimize environmental impacts, and improve farm profitability. Common practices include cover cropping and conservation tillage using strip tillage, minimal tillage, or no tillage. However, the soil response to specific combinations of conservation tillage and cover crop rotations remains poorly quantified. The objective of this research was to evaluate changes in soil properties from different combinations of conservation management. Four tillage systems – conventional, strip, minimal, and no tillage – and three winter cover rotations – fallow, winter cash crop, and high-biomass cover crop – were tested in a split-plot design. Bulk density, depth to a root-restrictive layer, soil carbon concentration, soil carbon stock, field-saturated hydraulic conductivity, and yield were measured over a seven-year period. Bulk density and field-saturated hydraulic conductivity showed greater temporal variation in the strip tillage and conventional tillage practices. Depth to root-restrictive layer was consistently highest in the strip and minimal tillage treatments, which both included implements designed to alleviate subsoil compaction. Treatments that combined conservation tillage with a winter cover (i.e., cash crops or high-biomass cover crops) had greater increases in soil carbon concentrations and carbon stock. Summer cash crop yield was significantly increased following the high-biomass cover crop treatment in 2 out of the 7 years. Altogether, soil carbon showed a more consistent response to conservation management than the other soil properties, which tended to show greater variability based on the time since disturbance (e.g., tillage). Conservation management practices therefore need to be consistently applied for multiple years in order to improve soil properties such as bulk density and saturated hydraulic conductivity.

Preventing water erosion is crucial for maintaining ecosystems and ensuring food security, necessitating a comprehensive understanding of the spatial and temporal patterns of water erosion and its underlying drivers. In the context of global warming, analyzing the impacts of land use dynamics and climate change on water erosion contributes to effective land management and sustainability of both industry and agriculture. This study aims to analyze the spatial distribution of water erosion in the western Songnen Plain from 1990 to 2020 using the Revised Universal Soil Loss Equation (RUSLE), with a focus on assessing the impacts of land use and climate on water erosion. The results revealed a 7.1 % increase in the area experiencing water erosion above light levels in the western Songnen Plain. The hotspots for water erosion were located in the southeast and northwest of the study area. The rapid expansion of farmland and land salinization, leading to reduced vegetation cover and soil property deterioration, were the main causes of intensified water erosion in the region before 2000. Although water erosion was slightly alleviated after 2000, the further expansion of farmland, the worsened water erosion intensity in alkaline land and frequent extreme weather still posed serious threats to water erosion in the study area. Water erosion was positively correlated with temperature and dry/wet alternation events, including frequency, duration, and severity. In addition, land use type was the main factor influencing the heterogeneous distribution of water erosion in the western Songnen Plain, whose interaction with dry/wet alternation events had the strongest explanatory power. Therefore, this study calls for the implementation of soil and water conservation measures to mitigate the impacts of land cultivation, salinization, and climate change on water erosion.

Cultivation of maize (Zea mays L.) can emit significant greenhouse gases (GHGs) due to root respiration, soil organic matter decomposition, and fertilizer losses in a tropical environment. Our objective was to examine the effect of tillage (conventional tillage [CT], minimum tillage [MT], and no-tillage [NT]), N fertilization rate (0, 90, and 120 kg N ha⁻¹), and manure application rate (0, 5, and 10 Mg ha⁻¹) on CO₂, N₂O, and CH₄ emissions under maize in two growing seasons (July-October 2018 and May-August 2019) in southwest Nigeria. We measured CO₂, N₂O, and CH₄ fluxes using the static chamber method and soil temperature and water content weekly, global warming potential (GWP), maize yield, and greenhouse gas intensity (GHGI). The CO₂ and N₂O fluxes peaked immediately following planting, fertilization, and intense precipitation, with most fluxes concentrated at 2–6 wk after planting. The CH₄ flux showed little change throughout the duration of the study. Cumulative CO₂ and N₂O fluxes were greater for CT and MT than NT, but cumulative CH₄ flux was greater for MT than CT and NT. Higher N fertilization rate increased N₂O and CH₄ fluxes. The GWP was greater for CT than MT and NT and greater for 90 than 0 kg N ha⁻¹. Maize yield was greater for MT than CT and NT and increased with higher N fertilization rate. The GHGI was lower for MT than CT and lower for 120 than 0 and 90 kg N ha⁻¹. Because of overall lower maize yield, MT with reduced N ferilization rate in split applications may be needed to reduce GHG emissions while sustaining yield in the sandy soils of southwest Nigeria.

Increasing crop diversity and nitrogen (N) fertilizer application have been identified as effective strategies for enhancing productivity and soil organic carbon (SOC) storage in agroecosystems. However, the impact of these management practices on soil inorganic carbon (SIC) in agroecosystems remains unclear. At present, we evaluated the effects of maize/faba bean intercropping, N application rates, and inoculation rhizobia of faba bean on SIC in the top 20 cm of soil depth using a 13-year crop diversity field experiment. Our results showed that the soil total carbon (TC) content increased significantly by 5.9 % and 7.0 % compared to faba bean monoculture and maize monoculture, respectively, after 13 years of continuous intercropping. Intercropping increased the pedogenic carbonate (PIC) content by 36.7 %, resulting in an 8.9 % higher SIC content compared to faba bean monoculture. Additionally, intercropping significantly reduced the dissolution of lithogenic carbonate (LIC) by 17.5 %, leading to a 7.6 % higher SIC content compared to maize monoculture. The formation of PIC was associated with an increase in soil available cations especially Ca²⁺ in intercropping. The conservation of LIC was related to the higher soil available Mg²⁺ in intercropping than monoculture. Faba bean inoculated with rhizobia significantly decreased SIC content due to soil acidification after 13 years of continuous cropping. Intercropping also significantly increased SOC and C3-derived SOC content compared to maize monoculture and increased C4-derived SOC content compared with faba bean monoculture. Soil organic carbon showed a positive correlation with SIC across all cropping systems, and the SOC fractions could affect the neoformation of PIC and dissolution of LIC. Our results demonstrate that intercropping can increase SIC content, which further promotes soil carbon sequestration. This study highlights the significance of increasing crop diversity on cropland carbon sequestration and provides practical implications for mitigating carbon emissions.

Soil organic carbon (SOC) is not a single and uniform entity, therefore understanding SOC fractions, particularly particulate organic carbon (POC) and mineral-associated organic carbon (MAOC), offers valuable insights into SOC dynamics. However, traditional laboratory measurements of SOC fractions are labor-intensive and costly. Therefore, leveraging rapid and cost-effective soil spectroscopy holds significant promise for addressing this challenge. While previous studies have concentrated on predicting SOC fractions using mid-infrared (MIR) spectroscopy, the potential of visible and near-infrared (VNIR) spectroscopy remains relatively unexplored, especially for tropical soils. To fill this gap, we evaluated six machine learning approaches, including three global models (Cubist, random forest (RF), partial least squares regression (PLSR)) and three local models (memory-based learning fitted by applying partial least squares regression (MBL-PLSR) and Gaussian process local regressions (MBL-GPR), non-linear memory-based learning (N-MBL)), for predicting POC and MAOC (g C kg⁻¹ soil) based on a regional soil VNIR spectral library (224 samples) from lateritic red soil in the tropical region of Guangdong Province, China. We also assessed the impact of variable selection on improving model performance by iteratively evaluating and removing insignificant predictor variables to determine the optimal number of predictors. The results showed that: (1) MBL-PLSR and N-MBL demonstrated commendable predictive performance, attaining coefficients of determination (R²) of 0.73 and 0.72 for POC, and 0.53 and 0.55 for MAOC on the validation set, respectively, outperforming Cubist and PLSR; (2) variable selection simplified predictive models by identifying the best spectral bands, leading to improved predictive accuracy for both POC (R² increased from 0.68 to 0.73) and MAOC (R² increased from 0.49 to 0.55); (3) the overall predictive performance of VNIR spectroscopy was higher for POC (R² of 0.73) compared to MAOC (R² of 0.55), while MAOC could be predicted more accurately by subtracting POC predictions from SOC observations (R² of 0.73). The favorable predictive accuracy underscores VNIR spectroscopy's viability for POC predictions. Additionally, MAOC can be well predicted by subtracting the predicted POC from the measured SOC. The outcomes of this study offers valuable insights for predicting SOC fractions using VNIR spectroscopy.