Higher Soil Organic Carbon Research Articles

Assessing spatiotemporal variations of soil organic carbon and its vulnerability to climate change: a bottom-up machine learning approach

Soil organic carbon (SOC) is a crucial component of the terrestrial carbon cycle and essential for agricultural productivity. Quantifying its sensitivity to future climate change is vital for sustaining agricultural practices and mitigating greenhouse gas emissions. However, this remains a challenge as long-term SOC data are scarce and substantial uncertainties regarding future climate scenarios. This study presents a bottom-up machine learning framework to assess the spatiotemporal variations of SOC and its vulnerability to climate change in the Jinghe River Basin, a typical loess hilly and gully watershed. Firstly, the long-term (2000-2023) dynamics of SOC was estimated by integrating in-situ measurements with machine learning techniques. Results show that the high SOC values are primarily distributed in the farmland of the mountain-loess transition zone, while the low-value areas are mainly found in the loess region. During the study period, the SOC content exhibited a slight increasing trend with a rate of 0.02 g kg⁻1 yr⁻1 (p = 0.449). The vulnerability of farmland surface SOC to future climate change was then evaluated by combining a robust machine learning model with the bottom-up framework. To this end, the study explored a wide range of possible future climates to identify critical climate thresholds and their spatial variation across the basin’s farmlands. Based on this analysis, this research found that the farmland in the northern basin is generally more susceptible to changing climate with even marginal rises in temperature could lead to severe loss in SOC. These results highlight the need for proactive climate adaptation strategies to safeguard SOC in vulnerable agricultural landscapes, ensuring soil health and resilience in the face of climate change.

Drivers of carbon stabilization and sequestration in Brazil’s black soils

Climate and land use are recognized as two of the main drivers of changes in soil organic carbon (SOC) on a global scale. Both factors play an important role in understanding SOC sequestration and mitigation of climate change. Particularly important, black soils are mineral soils with high SOC contents and high natural fertility and play an important role in national and global food and climate security. Here, we used a database of 90 black soils in Brazil − under different climate and land use conditions across the country − to test the hypothesis that C stock is richer in wetter climate conditions and that agricultural land use reduces C stock and the percentage of carbon saturation (PCS%). Climate data were obtained from the National Oceanic Atmospheric Administration (NOAA) and used to classify Thornthwaite’s climate. The land use information was obtained in the MapBiomas platform and was grouped into three major types: cropland, pasture, and native vegetation. The nonparametric Kruskal-Wallis test showed no differences for C stock, C/N ratio, and PCS% for both land use and climate. The low C/N ratio and the strong correlation between Ca2+, CEC, clay, and SOC suggest that organo-mineral interactions − which are stronger in soils with high-activity clays (e.g., Chernozems, Kastanozems, and Phaeozems) − promotes greater stabilization of the SOC and its long-term persistence and, thus being less sensitive to variations in climate and land use. Considering the total area of approximately 3.7 × 106 ha and the average value of C stock of 93.2 Mg/ha, the total SOC stored in Brazil’s black soils is in the order of 0.35 Gt, and the carbon stock stabilization potential is 0.25 Gt. Our results highlight the potential of Brazil’s black soils to promote carbon sequestration and climate change mitigation.

Developing a digital mapping of soil organic carbon on a national scale using Sentinel-2 and hybrid models at varying spatial resolutions

Mapping the spatial distribution of soil organic carbon (SOC) is crucial for monitoring soil health, understanding ecosystem functions, and contributing to global carbon cycling. However, few studies have directly compared the influence of hybrid models and individual models with varying spatial resolutions on SOC prediction at a national scale. In this study, by combining remote sensing data, we utilized the LUCAS 2018 soil dataset to evaluate the potential capacities of hybrid models for predicting SOC content at different spatial resolutions in Germany. The hybrid models PLSRK and RFK consisted of partial least square regression (PLSR) with residual original kriging (OK) models, and random forest (RF) models with residual OK models, respectively. Individual PLSR and RF models were used as reference models. All these models were applied to estimate SOC content at 10 m, 50 m, 100 m, and 200 m spatial resolutions. Sentinel-2 bands, band indices, and topography variables were as predictors. The results revealed that hybrid models had a more accurate prediction of SOC content with higher explanations and lower prediction errors compared with individual models. The RFK model at the spatial resolution of 100 m was the fittest model with R2 = 0.416, RMSE = 0.545, and RPIQ = 1.647, which enhanced 3.74% of explanation compared with the performance of RF model. The results also showed that hybrid models at a relatively coarse resolution (100 m) had better accuracy instead of those at high spatial resolution (10 m, 50 m). Sentinel-2 remote sensing data showed significant predictive capabilities for estimating SOC content. The predicted spatial distribution of SOC content revealed that the high SOC concentrated in the northwest grassland, central and southwestern mountains, and the Alps in Germany. Our study provided a benchmark SOC map in Germany for monitoring the changes resulting from land use and climate impacts, and we illustrated the accuracy of hybrid models and the effects of spatial resolutions on SOC predictions at a national scale.

Effect of Biostimulants and Nutrient Management on Soil Nutrients Level in Onion (Allium cepa L.)

During rabi season of 2021, a field experiment was conducted by embracing different organic manures, inorganic fertilizers and biostimulants (Pseudomonas fluorescens and Bacillus subtilis) over growth, yield, quality and persisting soil fertility of onion in the mineralized soils of Himachal Pradesh. The study was organized in thirteen treatments. The analysis revealed that lowest soil pH (6.94), electrical conductivity (0.186 dSm-1), highest soil organic carbon (0.85%), available nitrogen (257.79 kg/ha) and available phosphorus (26.14 kg/ha) were recorded with treatment T7 [75% RDF + 40 kg S/ha + Bacillus subtilis + FYM (250 q/ha)]. The highest available potassium was recorded in treatment T12 [100% RDF (125:75:60 kg/ha)] and highest available sulphur was recorded in treatment in T11 [100% RDF + 40 kg S/ha].

Differences in soil biological activity and soil organic matter status only in the topsoil of Ferralsols under five land uses (Allada, Benin)

Land use change on the Ferralsols of the Allada Plateau in southern Benin has led to a slight decline in soil organic carbon (SOC) stocks over the last two decades. However, as in many African landscapes, detailed characterisation and quantified data on the SOC stocks and soil biological activity under major land uses are still poorly understood. The aim of this study was to characterise the biological activity and organic matter status of Ferralsols (0–30 cm) under the five major land uses on the Allada Plateau, i.e., forests, tree plantations, young and adult palm groves, and croplands (pineapple, maize). Soil biological activity was assessed using the standardised litter decomposition method (Tea bag index) and soil respiration (during a 28-day soil incubation). Soil organic matter status was characterised by quantifying SOC pools: soil microbial biomass carbon (MB-C), potassium permanganate oxidisable carbon (POX-C), and SOC associated to soil particle-size fractions (e.g. particulate organic matter, POM, and SOC associated to the clay soil fraction). The results indicated that SOC pools and biological activity were lower in tree plantations than in forests. The standardised litter decomposition was also slower in tree plantations than in forest. In croplands and palm groves, SOC pools and soil microbial biomass and respiration were lower than in forests and tree plantations. This high level of biological activity in forests, and at a lesser level in tree plantations, was effective in accumulating carbon in C pools associated to the clay fraction. Agricultural land uses, such as croplands and palm groves decreased all the soil C pools even those associated to the clay fraction, except for POX-C. However, these land-use effects on SOC pools decreased strongly with depth. At 10–30 cm, the differences in SOC pools or soil respiration between the five land uses were no more noticeable. Our results indicated that the amount of organic inputs was an essential factor to sustain high soil biological activity and SOC stabilisation in the clay size fraction, but only in the topsoil. Maintaining forests in the landscape is a priority in order to preserve SOC stocks and soil biological activity, which neither monospecific tree plantations nor cultivation can do at the same level.

Spatial variation of soil organic carbon density in the black soil region of Northeast China under the influence of erosion and deposition

Soil erosion of the Songnen typical Black Soil Region (BSR) in Northeast China where contains higher soil organic carbon is serious, resulting in soil organic carbon spatial redistribution. To study the spatial redistribution pattern of cropland SOC caused by erosion, 115 cropland sample points were selected in the Songnen typical BSR, and soil samples were collected along the entire soil profile. The soil organic carbon density (SOCD) of the soil layer and profile were calculated, and the carbon storage (CS) was calculated for the erosion and deposition areas. The average soil organic carbon density (SOCDav) of the 115 cropland soil profiles (1 m) ranged from 1.5 to 4.5 kg/m2, and the total soil organic carbon density (SOCDt) of the soil profile (1 m) ranged from 10 to 20 kg/m2. The SOCD of each soil layer (20 cm) decreased vertically in a logarithmical manner from the top, and was divided into four groups with thickness through systematic clustering, which were 30–60 cm, 60–100 cm, less than 300 cm and greater than 350 cm. The SOCDt in the area north of the Songhua River and the area west of Nen River (The Greater Khingan Mountains area) ranged from 2.5 to 59.3 kg/m2, with an average is 14.1 kg/m2, and the first sample point group (30–60 cm) was mainly located in this area which had an average slope of 3.2° and an average black soil thickness of 24.6 cm. The SOCDt in the area north of the Songhua River and the area east of the Nen River ranged from 11 to 90 kg/m2, with an average of 28.6 kg/m2, the third and the fourth sample point group (greater than 100 cm) were both mainly located in this area which had an average slope of 2° and an average black soil thickness of 61 cm. The SOCDt in the area south of the Songhua River ranged from 1.6 to 28.7 kg/m2, with an average of 13.8 kg/m2, and the second sample point group (60–100 cm) was mainly located in this area which had an average slope of 2.4° and an average black soil thickness of 58.7 cm. The results showed that soil erosion occurred on steeper slopes, resulting in thinner soil layers, whereas soil deposition occurred on lower grade slopes, resulting in thicker soil layers. Kriging interpolation in ArcGIS showed that the Cs in the erosion and deposition areas of the Songnen typical BSR was 459.7 and 1234.7 Tg, respectively, and the total Cs was 1.6944 Tg (1 Tg = 1012 g).

A Comparative Study of Long-Term Conventional and No-Tillage Practices on the Basis of Available Soil Nutrients, Soil Organic Carbon and Crop Productivity in Black Soils of Central India

Crop residue removal in conventional tillage (CT) can cause the depletion of soil nutrients (such as N, P, K) and organic carbon resulting in negative nutrient balance/depleted soil fertility. No-tillage (NT) is seen as a good substitute for CT in terms of preserving soil fertility and enhancing the soil productivity. The present study carried out in black soil of central India comprising of 2 tillage systems and 3 crop rotations to compared the effects of long-term conventional and no-tillage practices on available soil nutrients, soil organic carbon and crop yield differences in different cropping systems. Conventional tillage and No-till were factored into, soybean-wheat, maize-wheat and maize-gram systems. The long-term no-tillage treatment resulted in higher soil organic carbon (0.95%), available soil nitrogen (222.61 Kg ha-1), phosphorus (24.62 Kg ha-1) and potassium (583.63 Kg ha-1) contents at the 0–10 cm depth than the conventional tillage treatment. Crop productivity in terms of soybean grain equivalent yield (SGEY) was significantly higher in NT (41.42 quintal ha-1) compare to CT (35.36 quintal ha-1). The study proven that no-tillage is an effective strategy to improve soil fertility (organic carbon and available nutrients) and crop yield of different cropping systems in black soils of central India.

Residue retention and precision nitrogen management effects on soil physicochemical properties and productivity of maize-wheat-mungbean system in Indo-Gangetic Plains

Maize-based crop systems are promoted in large scale in South Asia because they are more sustainable and efficient than rice-based systems. In the present study, using two combinations of crop residue management practices (CRM) with four precision nitrogen (N) management (PNM) systems, we assessed the impacts on soil physicochemical characteristics [soil organic carbon (SOC), bulk density (BD), soil penetration resistance (PR)] and crop yields in 6 years old continuous zero tillage (ZT) practices under maize-wheat-mungbean cropping system in a sandy loam soil of northwestern India. The highest SOC (5.73 g/kg) was observed in Zero Tillage with Residue Retention (ZT + R) plots. Zero-tillage with residue retention (ZT + R) significantly reduced the bulk density over the zero-tillage with no residue retention (ZT-R) across the soil depth. The bulk density in ZT + R was 6.5 and 10.7% lower at 0–15 cm and 15–30 cm soil depth, respectively, than under ZT-R. The penetration resistance (PR) was significantly lower in ZT + R than in ZT-R across the soil depth. Soil organic carbon (SOC) in ZT + R was 7.4% higher at 0–15 cm depth and 11.9% higher at 15–30 cm depth than under ZT-R treatment. Among PNM treatments, the sequence of treatments in SOC content was 50%N + Green Seeker (GS) >33%N + GS > RDN > 70%N + GS. The system productivity (maize equivalent yield) under ZT + R in combination with 50%BN + GS was 15.0% higher than crops grown under ZT-R with RDN. The wheat equivalent yield under the ZT + R treatment is found to be higher (5.97) in the 50%BN + GS, which was 18% higher than the recommended dose of nitrogen treatment (5.04) and 28% higher than the 70%BN + GS treatment (4.68). Results demonstrated that plots with residue retention performed better, showing a 10% increase in system productivity. The study concludes that a ZT-based system with maize-based crop rotations (MWMb) with crop residue retention and precision nitrogen management can improve soil properties and system productivity in northwestern India.

Soil organic carbon and nitrogen in a carboniferous spoil heap as a function of vegetation type and reclamation treatment

AbstractEvaluating the impact of vegetation types and reclamation methods on soil organic carbon and nitrogen in carboniferous spoil heaps is critical for selecting the best vegetation type and reclamation method to improve ecosystem services in a changing climate. This paper presents the relationship between vegetation types (woodland, forbland, and grassland) and reclamation techniques (barren rock, topsoil application, succession, and cultivation) on soil organic carbon (SOC) and total nitrogen (TN) in developing soils on carboniferous rocks in coal mine heaps. Soil samples were collected from the litter layer (Oi + Oe) and the A horizons (0–10 cm). The results revealed that vegetation types and reclamation methods significantly affected SOC and TN stocks. Woodland exhibited higher SOC and TN in the Oi + Oe horizons than other vegetation types. Topsoil application and cultivation resulted in the highest SOC and TN stocks in the A horizons (0–10 cm) under woodland and forbland compared to succession on bare carboniferous rock. In grassland, there was no significant difference in SOC stock under topsoil application and cultivation; however, significantly higher TN stock was observed in the 0–10 cm areas with topsoil application compared to succession on bare carboniferous rock. Based on the results, topsoil application is recommended to improve SOC if the mining site is restored using woodland. Conversely, grassland exhibits a similar amount of SOC stock with or without topsoil application. Considering the difficulty of obtaining topsoil, we suggest that grasses are optimal for SOC stock in the studied mining sites, followed by forbs.

The influence of soil types and agricultural management practices on soil chemical properties and microbial dynamics

Soil provides essential nutrients for plant growth, but excess salts hinder development, making crops more vulnerable under climate change conditions. Soil microorganisms play a significant role in nutrient cycling. However, limited information is available on microbial behavior/community changes, and functional diversity in different soil types (normal, sodic, and highly sodic) and cropping systems [rice-wheat (RW); rice-wheat-mungbean (RWMb); maize-wheat-mungbean (MWMb)] and management practices in the north-western Indo-Gangetic Plains of India. We investigated the influence of different soil types on physical and chemical properties at the surface level (0–15 cm) in relation to soil microbial population, activities, and functional diversity, focusing on community-level physiological profiling (CLPP) under different agriculture systems. Seven treatment combinations of soil types, cropping systems, and management practices were evaluated. Soil pHs were found to be lower in zero-till (ZT)-based sodic soil than in conventional-till (CT) sodic soil. Soil organic carbon (SOC) (0.91 and 0.90%) content and available N (154.46 and 132.74 kg ha−1) were higher with the ZT-based system under normal (N) soils (ZT-RWMb-N and ZT-MWMb-N) than in CT-based normal soil (0.67 and 121.04 kg ha−1). Similarly, higher SOC and N (0.85 and 76.11 kg ha−1) were found under ZT management in sodic soils (S) than under CT management (0.73% and 121.05 kg ha−1). Substrate utilization (amino acids, amines, carbohydrates, carboxylic acids, phenolic compounds, and polymers) increased with the incubation period. During 0–120 h of incubation, the highest utilization of amino acids, amines, carboxylic acids, phenolic compounds, and polymers was observed for ZT-MWMb-S soils, while the lowest was recorded for ZT-MWMb-N soils. Under high salt conditions, soil enzymatic activities (dehydrogenase, acid phosphatase, alkaline phosphatase, etc.) declined significantly compared to normal soils, affecting soil chemical and physical conditions. Microbial population and enzyme activities decreased with increasing salt stress across all cropping systems. These findings suggest that adopting efficient crop management practices can help mitigate the adverse effects of soil salinity on microbial diversity and soil health, thereby enhancing sustainable agricultural productivity in salt-affected regions.

Effects of vermicompost and mineral fertilizers on soil properties, malt barley (Hordeum distichum L.) yield, and economic benefits

AbstractSoil fertility depletion has significantly reduced the yields of various crops in Ethiopia, mainly the yield of malt barley in the district. To address this issue, integrated applications of vermicompost and mineral nitrogen (N) fertilizers were tested. Therefore, this study aimed to evaluate the effects of vermicompost and mineral nitrogen fertilizers application on malt barley yield (Hordeum distichum L.), soil properties, and economic benefits. The experiment was arranged in a randomized complete block design with three replications. The treatments were nine in various combinations of vermicompost (VC) and N fertilizer (N): (69 kg N; 0.79 t VC + 58.65 kg N; 1.59 t VC + 48.30 kg N; 2.39 t VC + 37.95 kg N; 3.19 t VC + 27.60 kg N; 3.98 t VC + 17.25 kg N; 4.78 t VC + 6.90 kg N; 5.31 t VC ha−1 and control). The highest soil pH was recorded by applying 5.31 t of vermicompost ha−1 alone. The highest total nitrogen (0.34%), available phosphorus (15.58 mg kg−1), grain yield (4950 kg ha−1), and net benefit (4255.74 USD) were recorded from the application of 2.39 t VC plus 37.95 kg N, while the highest soil organic carbon (3.38%) and cation exchange capacity (26.17 cmol (+) kg−1) were recorded from 3.19 t VC plus 27.60 kg N ha−1 compared to the control. This study concludes that applying 2.39 t VC and 37.95 kg N ha−1 in combination improves soil fertility, malt barley yield, and economic benefits for smallholder farmers in the study district and adopts this in similar soil types and agroecologies.

Organic fertilisation enhances network complexity among bacteria, fungi, and protists by improving organic matter and phosphorus in acidic agricultural soils

Research has explored the impact of organic fertilisation on improving agroecosystem productivity and resilience, highlighting the significant contributions of protists in addition to bacteria and fungi. However, the interactions among bacteria, fungi and protists in organically fertilised soils remain largely unknown. In this study, soil samples were collected from four long-term fertilisation treatments: no fertilisation (Control), inorganic fertilisation (NPK), organic fertilisation (OM), and combined inorganic and organic fertilisation (NPKOM). The abundance and composition of bacteria, fungi, and protist communities, as well as co-occurrence networks, were analysed under different fertilisation treatments. Our results showed that the total abundance of bacteria, fungi, and protists increased by a minimum of 2.95, 3.47, and 0.66 times, respectively, after organic fertiliser application. Moreover, the application of organic fertilisers significantly altered the structures of soil microbial communities by enriching bacterial Proteobacteria and Actinobacteria, fungal Ascomycota, and protist Conosa. Changes in the total abundance of bacteria, fungi, and protists, and their community structures in soils with organic fertilisers were associated with increases in soil organic carbon and phosphorous. Additionally, microbial networks exhibited greater complexity in organically fertilised soils than in non-organically fertilised soils by possessing higher linkage density. The increased complexity may be attributed to potential interkingdom associations among bacteria, fungi, and protists in high soil organic carbon and phosphorus. These results highlight that the application of organic fertilisers has the potential to enhance the complexity of microbial coexistence in acidic agricultural soils.

The role of ruminant urine and faeces in the recycling of nutrients by forages

This study addresses the effect of using animal excreta on the nutritional content of forages, focusing on macro- and micro-element concentrations (nitrogen; N, phosphorus; P, sulphur; S, copper; Cu, zinc; Zn, manganese; Mn, selenium; Se) from animal feed to excreta, soil, and plants. Data were collected from pot and field trials using separate applications of sheep or cattle urine and faeces. Key findings indicate that soil organic carbon (SOC) and the type of excreta significantly influences nutrient uptake by forages, with varied responses among the seven elements defined above. Although urine contributes fewer micronutrients compared to faeces (as applied at a natural volume/mass basis, respectively), it notably improves forage yield and micronutrient accumulation, thus potentially delivering positive consequences at the farm level regarding economic performance and soil fertility when swards upon clayey soil types receive said urine in temperate agro-climatic regions (i.e., South West England in the current context). In contrast, faeces application in isolation hinders Se and Mn uptake, once again potentially delivering unintended consequences such as micronutrient deficiencies in areas of high faeces deposition. As it is unlikely that (b)ovine grazing fields will receive either urine or faeces in isolation, we also explored combined applications of both excreta types which demonstrates synergistic effects on N, Cu, and Zn uptake, with either synergistic or dilution effects being observed for P and S, depending largely on SOC levels. Additionally, interactions between excreta types can result in dilution or antagonistic effects on Mn and Se uptake. Notably, high SOC combined with faeces reduces Mn and Se in forages, raising concerns for grazed ruminant systems under certain biotic situations, e.g., due to insufficient soil Se levels typically observed in UK pastures for livestock growth. These findings underscore the importance of considering SOC and excreta nutritional composition when designing forage management to optimize nutrient uptake. It should be noted that these findings have potential ramifications for broader studies of sustainable agriculture through system-scale analyses, as the granularity of results reported herein elucidate gaps in knowledge which could affect, both positively and negatively, the interpretation of model-based environmental impact assessments of cattle and sheep production (e.g., in the case of increased yields [beneficial] or the requirement of additional synthetic supplementation [detrimental]).

Estimating the uncertainties of satellite derived soil moisture at global scale

This study attempts to derive the uncertainty of the soil moisture estimation from passive microwave satellite mission at global scale. To do so, the approach is based on the sensitivity of the Soil Moisture and Ocean Salinity (SMOS) soil moisture retrieval quality to the land surface characteristics within its footprint (presence of forest, topography, open water bodies, sand, clay, bulk density and soil organic carbon content). First, we performed a global assessment of SMOS using in situ measurements from the International Soil Moisture Network (ISMN) as reference, with more than 1900 ISMN stations and 10 years of SMOS data. This assessment shows that the ubRMSD scores vary greatly between locations (with a mean of 0.074 m3m−3 and an interquartile range of 0.030 m3m−3). Second, the scores are analyzed for different surface conditions within the satellite footprint. The best agreement between the ground measurement and SMOS time series are obtained for low forest cover, low topographic complexity, and marginal presence of open water bodies within the SMOS footprint. Soil parameters also have an impact, with better scores for sandier soils with a high bulk-density and low soil organic carbon content. Finally, we propose to extrapolate the obtained relationships, using a multiple linear regression, in order to derive a global map of SMOS uncertainties based on surface conditions. This map of predicted uncertainties show a diverse range of ubRMSD values across the globe (with a mean of 0.076 m3m−3 and an interquartile range of 0.031 m3m−3) depending on the surface characteristics. At the ISMN site location, the predicted ubRMSD shows similar results than the comparison between SMOS and the in situ measurements. The map of predicted SMOS ubRMSD represents an upper bound estimate of the SMOS uncertainty, as it includes the uncertainties of the in situ sensor measurements and the scale mismatch. Further investigations will focus on the different components of this uncertainty budget to obtain a better assessment of the absolute uncertainties of SMOS soil moisture retrievals across the globe.

Performances of phosphate-solubilizing microorganisms on soil chemical properties under different soil characteristics: a meta-analysis

The addition of phosphate-solubilizing microorganisms (PSM) as biofertilizers can improve the quality of soil properties. A meta-analysis study was conducted to analyze the effect of PSM on soil properties. This meta-analysis has analyzed 20 research articles published between 1990 and 2023, which have reported the influence of PSM on soil properties. The value of effect size (ES) Hedges'd of available-P is 3.047 (p<0.001), ES of available K is 2.102 (p<0.001), ES of soil nitrogen (N) is 1.706 (p<0.001), ES of pH is -2.738 (p<0.001), ES of soil organic carbon (SOC) is 1.087 (p=0.004), ES of N-NH4 is 0.636 (p= 0.013), ES of N-NO3 is 2.643 (p< 0.001), ES of phosphatase is 5.001 (p< 0.001), ES of alkaline phosphatase is 22.956 (p<0.001), and ES of acid phosphatase is 23.104 (p<0.001). The results showed that in terms of phosphate solubility, PSM is more effective on alkaline soils with high SOC content, very high P availability, and a sandy loam texture. PSM is more effective for K solubility on acidic soils, with very high SOC content, high P availability, and a loamy texture. PSM is effective in increasing soil N with acid soil characteristics, low SOC content, moderate available P content, and clay texture. According to this study, the Penicillium fungus ranks second in the fungal group in terms of phosphate solubilization capacity after the genus Azotobacter. The genus Peronospora showed the greatest potential in increasing soil N. In contrast, Burkholderia showed the greatest effectiveness in solubilizing K.

Mapping Key Soil Properties of Cropland in a Mountainous Region of Southwestern China

Soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), and total potassium (TK) are important indicators for evaluating soil fertility. Exploring the content and spatial distribution of these indicators is of great significance for optimizing cropland management measures and developing sustainable agriculture. Yunnan Province is one of the most important agricultural regions in southwestern China, characterized by large variations in the topography and an uneven distribution of soil fertility. In this study, the data of 8571 topsoil (0–20 cm) samples selected from Yunnan Province and a portion of related spatial data were used to carry out electronic mapping of the spatial distribution of soil sand content, clay content, silt content, SOC, TN, TP, TK content, and C:N ratio at 1 km resolution using the Random Forest (RF) model. The results indicated that the average measured contents of SOC, TN, TP, TK, and C:N ratio in the topsoil of Yunnan Province were 18.78 ± 0.09 g/kg, 1.78 ± 0.01 g/kg, 0.98 ± 0.01 g/kg, 13.89 ± 0.08 g/kg, and 10.56 ± 0.02, respectively. The spatial analysis showed that higher SOC was mainly distributed in northern and eastern Yunnan, and the spatial distribution pattern of TN and TP was similar to that of SOC. While higher TK was mainly distributed in southwestern Yunnan Province. There was a significant positive correlation between SOC and TN and TP contents with correlation coefficients of 0.889 and 0.463, however, there was a significant negative correlation between SOC and TK content with correlation coefficients of −0.060. It was also indicated that elevation, temperature, precipitation, clay content, sand content, and silt content were the most important factors affecting SOC, TN, TP, and TK content. The present study provided an understanding of soil nutrients characteristics and their affecting factors, which is helpful to optimize agricultural management practices and develop sustainable agriculture according to soil fertility.

Prediction of Soil Organic Carbon Content in Complex Vegetation Areas Based on CNN-LSTM Model

Synthesizing bare soil pictures in regions with complex vegetation is challenging, which hinders the accuracy of predicting soil organic carbon (SOC) in specific areas. An SOC prediction model was developed in this study by integrating the convolutional neural network and long and short-term memory network (CNN-LSTM) algorithms, taking into consideration soil-forming factors such as climate, vegetation, and topography in Hainan. Compared with common algorithmic models (random forest, CNN, LSTM), the SOC prediction model based on the CNN-LSTM algorithm achieved high accuracy (R2 = 0.69, RMSE = 6.06 g kg−1, RPIQ = 1.96). The model predicted that the SOC content ranged from 5.49 to 36.68 g kg−1, with Hainan in the central and southern parts of the region with high SOC values and the surrounding areas with low SOC values, and that the SOC was roughly distributed as follows: high in the mountainous areas and low in the flat areas. Among the four models, CNN-LSTM outperformed LSTM, CNN, and random forest models in terms of R2 accuracy by 11.3%, 23.2%, and 53.3%, respectively. The CNN-LSTM model demonstrates its applicability in predicting SOC content and shows great potential in complex areas where obtaining sample data is challenging and where SOC is influenced by multiple interacting factors. Furthermore, it shows significant potential for advancing the broader field of digital soil mapping.

On-Site Determination of Soil Organic Carbon Content: A Photocatalytic Approach

This investigation presents a new approach for evaluating soil organic carbon (SOC) content in farming soils using a photocatalytic chemical oxygen demand (PeCOD) analyzer combined with geographic information system (GIS) technology for spatial analysis. Soil samples were collected at various sites throughout Canada and were analyzed using sieve analysis, followed by further SOC evaluation using three distinct techniques: loss on ignition (LOI), Walkley-Black, and PeCOD. The PeCOD system, which relies on the photochemical oxidation of organic carbon, showed an exciting correlation between its evaluations and SOC content, making it a prompt and reliable method to evaluate SOC. In this investigation, finer materials such as clayey soils (soil fractions of (<50 µm)) demonstrated high SOC content compared to coarser ones (soil fractions of (>75 µm)) and decreased SOC content with increased soil depth, generally below the 30 cm mark. It should be noted that this investigation revealed that other variables, such as land management practices, precipitation, and atmospheric temperature, have drastic effects on the formation and residence time of SOC. GIS georeferencing еnablеd mapping of the SOC distribution and identification of hotspot areas with high SOC content. The results of this study have implications for sustainable farming, climate change mitigation, and soil health operations by providing farmers with schemes that amplify carbon sequestration while simultaneously improving soil health.

Long-term organic farming impact on soil nutrient status and grain yield at the foothill of Himalayas

This study aimed to document the effects of the long-term organic farming (OF) on soil quality, agronomical parameters, crop productivity, and food grain yield compared to the conventional farming (CF) system. The crop used in this study is chickpea (Cicer arietinum), and the field was located at Pantnagar, India, in the foothills of Himalayas. The organic farming approach involved utilizing a blend of farmyard manure and vermicompost, combined with a biopesticide comprising neem oil and cow urine. Chickpea grain micronutrient analysis was done via atomic absorption spectrophotometry. It was found that the physicochemical properties of soil in the organic plot were improved compared to the conventional counterpart. At the post-harvesting stage, the organically managed field had higher soil organic carbon than the conventional field (OF-0.93± 0.05%, CF-0.75 ± 0.12%), higher available nitrogen (OF-317 ± 11 kg/ha, CF-240 ± 22 kg/ha), and more available phosphorus (OF-37.4 ± 1.3 kg/ha, CF-25.2 ± 2.5 kg/ha). The agronomical parameters of the chickpea crop were better under organic cultivation, with a significantly high nodule number, nodule dry weight, and grains per pod. Hence, the grain yield of the crop was better under organic cultivation, with the yield of 1,048 kg ha−1, whereas it was 896.5 kg ha−1 for conventional cultivation. The Fe and Zn contents of organically produced chickpea grains were almost double of their conventional counterpart. Therefore, organic cultivation led to better soil fertility, chickpea grain yield, and nutrient status of the crop. It will be beneficial for the nutritious and sustainable production of chickpeas in Himalayan regions.

Edaphic regulation of soil organic carbon fractions in the mattic layer across the Qinghai-Tibetan Plateau

The mattic layer is a main ecological function bearer of alpine meadow soils in the Qinghai-Tibet Plateau. It has high soil organic carbon (SOC) content with a variety of SOC fractions, which are thought to have different sensitivities to climate change. The effects of soil properties and climate on the SOC fractions in the mattic layer are not well understood. To address this, we analyzed the effects of environmental factors on two SOC fractions: particulate organic carbon (POC) and mineral-associated organic carbon (MAOC). A random forest model (RFM), partial correlation analysis, and structural equation model (SEM) were used to quantify the relative effects of soil and climatic factors on SOC fractions. We found that SOC and its fractions are primarily regulated by soil properties rather than climate. Partial correlation analysis and SEM revealed that climate indirectly affects SOC by influencing soil properties. Silt+Clay and exchangeable calcium (Caex) were found to be the strongest contributing factors of MAOC and POC, respectively. A distinct shift occurs in the mechanism underlying SOC stabilization with varying soil pH. In acidic and neutral environments, amorphous Al/Fe-(hydr) oxides contribute to the stability of MAOC, whereas free Al/Fe-(hydr) oxides promote SOC mineralization. Conversely, Caex positively influences the stabilization of both POC and MAOC throughout the pH range. These results can be extrapolated to predict SOC dynamics in future soil conditions affected by environmental change, especially for use in Earth system models.