Soil Organic Matter Content Research Articles

Assessing pollution degree and human health risks from hazardous element distribution in soils near gold mines in a Colombian Andean region: Correlation with phytotoxicity biomarkers

The assessment of human health risk due to the presence of hazardous elements in the environment is now necessary for environmental management and legislative initiatives. This study aims to determine the contamination by As, Cd, Pb, and Cr in soils near gold mines in three municipalities located in the Andean region of Colombia. One of the main objectives of the study is to explore possible correlations between the Lifetime Cancer Risk (LCR) and phytotoxicity biomarkers using a simple and rapid-response plant model, radish (Raphanus sativus L.). In the municipality of Yalí, Puerto Berrío, and Buriticá, the hazardous elements concentrations ranged from 8.1 to 35.5, 1.7 to 892, and 5.8 to 49.8 for As, 0.1 to 4.6, 0.1 to 65.2, and 0.5 to 18.2 for Cd, 18.5 to 201.3, 13.0 to 1908, and 189 to 2345 for Pb, and 5.4 to 118.4, 65.4 to 301, and 5.4 to 102.3 for Cr, respectively. The results showed that the biomarkers intracellular H2O2 concentration, antioxidant activity, and radicle elongation exhibited significant (P < 0.05) variations associated with the concentration of hazardous elements in the soils. Significant correlations (P < 0.05, r > 0.58) were found between the biomarkers and the LCR for Cd, Pb, and Cr, but not for As. The results using biomarkers reveal that soil pH and organic matter content are important variables that control the bioavailability of these elements in the soil. The use of indicators like LCR alone has limitations and should be accompanied by the use of biomarkers that allow for a better understanding of the biological system's response to exposure to potentially toxic elements. The results obtained show the urgent need to implement public policies to minimize exposure to hazardous substances in areas near gold mining projects.

Effects of vegetation extreme degradation on soil hydrothermal processes in alpine wet meadow on the central Qinghai–Tibet Plateau

Ongoing climate warming and humidification have triggered a series of environmental responses, including vegetation succession, significant permafrost degradation, hydrological shifts, alterations in water resources, and increased frequency of freeze-thaw events. Notably, vegetation modulates the water cycle, regulates soil temperatures, and sustains permafrost stability. However, the extent to which the degradation of alpine vegetation impacts soil hydrothermal processes in permafrost regions is unclear. Therefore, we measured the soil moisture and temperature of the alpine wet meadow (AWM) and extremely degraded alpine wet meadow (EDAWM) ecosystems within the permafrost regions of the Qinghai–Tibet Plateau in situ. The objectives of this study were to explore the freeze-thaw cycles and hydrothermal dynamics within the active layer and to understand the mechanisms behind the effects of extreme alpine vegetation degradation. The results revealed that the AWM ecosystem had a longer soil freezing duration and a higher soil freezing rate than those of the EDAWM ecosystem. Additionally, the freezing index was higher in EDAWM than that in AWM, while differences in the thawing index were insignificant. The variance in the thaw-freeze ratios between the two ecosystems indicated that extreme vegetation degradation in AWM altered soil heat absorption and dissipation in the plant root zone and the deeper active layer. Moreover, EDAWM exhibited a decrease in soil bidirectional freezing processes, particularly from the permafrost table upwards. The extreme degradation in AWM changed soil physical properties and organic matter content, reducing ground temperatures in the active and permafrost layers of EDAWM, particularly during winter. The reduced heat transfer in EDAWM resulted in an active layer depth 9 cm shallower than that in AWM. Without vegetation cover, soil moisture in EDAWM was more prone to evaporation or deeper infiltration, leading to lower soil moisture content than that in AWM. Furthermore, an increase in soil moisture content decreased temperature in shallow soils in AWM but increased it in shallow soils in EDAWM. In summary, extreme vegetation degradation impaired air-heat exchange in AWM soil. These insights provide a scientific and theoretical basis for predicting permafrost evolution in the Qinghai–Tibet Plateau, highlighting the complex interactions among vegetation degradation, soil hydrothermal processes, and climatic factors.

“Hg distribution and accumulation in soil and vegetation in areas impacted by artisanal gold mining in the Southern Amazonian region of Madre de Dios, Peru.”

Artisanal and small-scale gold mining (ASGM) is the primary global source of anthropogenic mercury (Hg) emissions. It has impacted the Amazon rainforest in the Peruvian region of Madre de Dios. However, few studies have investigated Hg's distribution in terrestrial ecosystems in this region. We studied Hg's distribution and its predictors in soil and native plant species from artisanal mining sites. Total Hg concentrations were determined in soil samples collected at different depths (0–5 cm and 5–30 cm) and plant samples (roots, shoots, leaves) from 19 native plant species collected in different land cover categories: naked soil (L1), gravel piles (L2), natural regeneration (L3), reforestation (L4), and primary forest (L5) in the mining sites. Hg levels in air were also studied using passive air samplers. The highest Hg concentrations in soil (average 0.276 and 0.210 mg kg−1 dw.) were found in the intact primary forest (L5) at 0–5 cm depth and in the plant rooting zones at 5–30 cm depth, respectively.Moreover, the highest Hg levels in plants (average 0.64 mg kg−1 dw) were found in foliage of intact primary forest (L5). The results suggest that the forest in these sites receives Hg from the atmosphere through leaf deposition and that Hg accumulates in the soil surrounding the roots. The Hg levels found in the plant leaves of the primary forest are the highest ever recorded in this region, exceeding values found in forests impacted by Hg pollution worldwide and raising concerns about the extent of the ASGM impact in this ecosystem. Correlations between Hg concentrations in soil, bioaccumulation in plant roots, and soil physical-chemical characteristics were determined. Linear regression models showed that the soil organic matter content (SOM), pH, and electrical conductivity (EC) predict the Hg distribution and accumulation in soil and bioaccumulation in root plants.

Uptake and Transport of Selenium in a Soil–Tea Plant–Tea Infusion System: A Study of Typical Tea Plantations in a Selenium-Rich Area of China

Selenium is an important indicator for the evaluation of tea quality. However, the relationship between selenium uptake by tea plants (Camellia sinensis) and soil properties, as well as selenium transport and distribution in a tea plantation soil–tea plant–tea infusion production system, remain unclear. In this study, 12 tea plantations situated in a typical selenium-rich area of China were selected, and the characteristics and crucial factors influencing the uptake and transport of selenium were analyzed using a plantation soil–tea plant–tea infusion production system. The soil total selenium content ranged from 1.12 to 6.67 mg kg−1, with an average of 2.57 mg kg−1. The average available selenium content was 53.56 µg kg−1, and the activation rate of soil selenium was 2.27%. Soil-available selenium was significantly positively correlated with total selenium, available potassium, and soil organic matter contents, and was significantly negatively correlated with soil pH. The selenium content in old leaves ranged from 0.29 to 2.73 mg kg−1, which met the standard for selenium-rich tea, whereas only 33% of young leaves met this standard. The selenium enrichment factor was highest in the fibrous root and lowest in the young leaves. The average selenium transport factors from fibrous roots to main roots, from main roots to main stems, from main stems to lateral stems, from lateral stems to young leaves, and from lateral stems to old leaves were 0.53, 0.92, 0.67, 0.97, and 2.30, respectively. The selenium concentration of tea infusion ranged from 1.88 to 12.49 μg L−1, and the average selenium dissolution rate was 22.62% after one brewing. This study identified critical factors that influence soil-selenium availability. The selenium content in tea plant organs is indicated to be strongly associated with the selenium content in the main roots.

Optimization Study of Soil Organic Matter Mapping Model in Complex Terrain Areas: A Case Study of Mingguang City, China

Traditional soil organic matter mapping is mostly polygonal drawing, which is even more difficult to accurately depict in complex terrain areas. The spatial distribution of soil organic matter is closely related to agricultural production, natural resources, environmental governance, and socio-economic development. Efficiently, economically, and accurately obtaining information on changes in soil organic matter in areas with diverse topography is an urgent problem to be solved. Mingguang City has a high research value because of its unique topography and natural landscape. To solve the problem of soil organic matter mapping in this area, this study will construct an excellent organic matter prediction model. Using 173 soil survey samples (123 for training and 50 for testing), the optimal feature variable subsets selected from 31 environmental variables through Pearson correlation, stepwise regression-variance inflation factor, and recursive feature elimination models based on different algorithms were employed. Each selected feature subset was then used to construct organic matter prediction models using multiple advanced machine learning algorithms. By comparing accuracy validation and model performance, the organic matter prediction model suitable for Mingguang City (RFE-RF_SVM) was obtained, that is, the prediction model of organic matter based on support vector machines with the feature variables screened by the feature recursive elimination algorithm of random forest with RMSE = 3.504, VSI = 0.036, and R-squared = 0.730. Furthermore, the analysis focused on assessing the significance of the predictive factors. The mapping results of this study show that the soil organic matter content in the central and northwestern parts of the study area is low, and the reasons for this situation are different. The central part is mainly caused by the change of land use and topography, while the northwestern part is caused by the loose soil structure caused by the parent material. The government can take targeted measures to improve the soil in the areas with poor organic matter.

Effects of different tillage and cropping systems on water repellency and hydraulic properties in a tropical Alfisol of southwestern Nigeria

This study examined the effects of growing intercrops (Sorghum, SOR (Sorghum bicolor L. Moench) in between rows of cowpea, COW (Vigna unguiculata) and soybean, SOY (Glyxine max L.Merr)) under different tillage systems on soil physico-chemical properties, soil water sorptivity (Sw), hydraulic conductivity (K), and soil hydrophobicity (R) in tropical Alfisol of Southwestern Nigeria. Results demonstrated cropping systems significantly impacted soil pH under each conventional tillage (CT), no tillage (NT), and compacted no till systems (NTC) tillage system in 2019, but not in the 2020 cropping season. Sorghum-cowpea SC) and sorghum-soybean (SS) intercropping systems under the three tillage systems had higher soil organic matter (SOM) contents than the corresponding sole sorghum (SOR) at the end of the study. Soil water sorptivity differed significantly (p < 0.001) among the cropping systems in 2019 and follows the order: SC > SS > SOY > SOR > COW while in 2020, averaged over three tillage systems, mean Sw values showed an increasing trend in the order: SOR (77.67 cm h-1/2) < COW (82.42 cm h-1/2) < SOY (88.00 cm h-1/2) < SS (88.73 cm h-1/2) < SC (98.29 cm h-1/2). In general, intercropping had a lower R than sole cropping. NTC soil was 46.48% and 56.39%; 32.47% and 41.67% more hydrophobic than soils under NT and CT in 2019 and 2020. Intercropping with legumes might have contributed to the higher K levels. Organic matter in soil improves conductivity by improving soil structure. The intercrop may have improved soil water conservation because of their shading and better soil protection. The study demonstrated that conservation tillage with intercropping could effectively enhance soil hydraulic properties.

Improving the Spatiotemporal Transferability of Hyperspectral Remote Sensing for Estimating Soil Organic Matter by Minimizing the Coupling Effect of Soil Physical Properties on the Spectrum: A Case Study in Northeast China

Soil organic matter (SOM) is important for the global carbon cycle, and hyperspectral remote sensing has proven to be a promising method for fast SOM content estimation. However, because of the neglect of the spectral response of soil physical properties, the accuracy and spatiotemporal transferability of the SOM prediction model are poor. This study aims to improve the spatiotemporal transferability of the SOM prediction model by alleviating the coupling effect of soil physical properties on spectra. Based on satellite hyperspectral images and soil physical variables, including soil moisture (SM), soil surface roughness (root-mean-square height, RMSH), and soil bulk weight (SBW), a soil spectral correction model was established based on the information unmixing method. Two important grain-producing areas in Northeast China were selected as study areas to verify the performance and transferability of the spectral correction model and SOM content prediction model. The results showed that soil spectral corrections based on fourth-order polynomials and the XG-Boost algorithm had excellent accuracy and generalization ability, with residual predictive deviations (RPDs) exceeding 1.4 in almost all the bands. In addition, when the soil spectral correction strategy was adopted, the accuracy of the SOM prediction model and the generalization ability after the model migration were significantly improved. The SOM prediction accuracy based on the XG-Boost-corrected spectrum was the highest, with a coefficient of determination (R2) of 0.76, a root-mean-square error (RMSE) of 5.74 g/kg, and an RPD of 1.68. The prediction accuracy, R2 value, RMSE, and RPD of the model after the migration were 0.72, 6.71 g/kg, and 1.53, respectively. Compared with the direct migration prediction of the model, adopting the soil spectral correction model based on fourth-order polynomials and XG-Boost reduced the RMSE of the SOM prediction results by 57.90% and 60.27%, respectively. This performance comparison highlighted the advantages for considering soil physical properties in regional-scale SOM predictions.

Assessing Soil Prediction Distributions for Forest Management Using Digital Soil Mapping

Texture, soil organic matter (SOM), and soil depth (SoD) are crucial properties in forest management because they can supply spatial information on forest site productivity and guide fertilizer applications. However, soil properties possess an inherent uncertainty that must be mapped to enhance decision making in management applications. Most digital soil mapping predictions primarily concentrate on the mean of the distribution, often neglecting the estimation of local uncertainty in soil properties. Additionally, there is a noticeable scarcity of practical soil examples to demonstrate the prediction uncertainty for the benefit of forest managers. In this study, following a digital soil mapping (DSM) approach, a Quantile Regression Forest (QRF) model was developed to generate high-resolution maps and their uncertainty regarding the texture, SoD, and SOM, which were expressed as standard deviation (Sd) values. The results showed that the SOM (R2 = 0.61, RMSE = 2.03% and with an average Sd = 50%), SoD (R2 = 0.74 and RMSE = 19.4 cm), clay (R2 = 0.63, RMSE = 10.5% and average Sd = 29%), silt (R2 = 0.59, RMSE = 6.26% and average Sd = 33%), and sand content (R2 = 0.55, RMSE = 9.49% and average Sd = 35%) were accurately estimated for forest plantations in central south Chile. A practical demonstration of precision fertilizer application, utilizing the predictive distribution of SOM, effectively showcased how uncertainty in soil attributes can be leveraged to benefit forest managers. This approach holds potential for optimizing resource allocation and maximizing economic benefits.

Long-Term Straw Incorporation under Controlled Irrigation Improves Soil Quality of Paddy Field and Rice Yield in Northeast China.

Soil quality is an indicator of the ability to ensure ecological security and sustainable soil usage. The effects of long-term straw incorporation and different irrigation regimes on the yield and soil quality of paddy fields in cold regions remain unclear. This study established four treatments: controlled irrigation + continuous straw incorporation for 3 years (C3), controlled irrigation + continuous straw incorporation for 7 years (C7), flooded irrigation + continuous straw incorporation for 3 years (F3), and flooded irrigation + continuous straw incorporation for 7 years (F7). Analysis was conducted on the impact of various irrigation regimes and straw incorporation years on the physicochemical characteristics and quality of the soil. The soil quality index (SQI) for rice fields was computed using separate datasets for each treatment. The soil nitrate nitrogen, available phosphorus, soil organic carbon, and soil organic matter contents of the C7 were 93.51%, 5.80%, 8.90%, and 8.26% higher compared to C3, respectively. In addition, the yield of the C7 treatment was 5.18%, 4.89%, and 10.32% higher than those of F3, C3, and F7, respectively. The validity of the minimum data set (MDS) was verified by correlation, Ef and ER, which indicated that the MDS of all treatments were able to provide a valid evaluation of soil quality. The MDS based SQI of C7 was 11.05%, 11.97%, and 27.71% higher than that of F3, C3, and F7, respectively. Overall, long-term straw incorporation combined with controlled irrigation increases yield and soil quality in paddy fields in cold regions. This study provides a thorough assessment of soil quality concerning irrigation regimes and straw incorporation years to preserve food security and the sustainability of agricultural output. Additionally, it offers a basis for soil quality diagnosis of paddy fields in the Northeast China.

Drivers of plant diversification along an altitudinal gradient in the alpine desert grassland, Northern Tibetan Plateau

Revealing alpine plant diversity patterns can contribute to conserving mountain plant diversity. However, the spatial variation in the ecological niche and diversity patterns of the plant community and the mechanism by which it maintains itself in alpine desert grasslands remain poorly understood. Here, we conducted a field investigation across altitudinal gradients (3093, 3296, 3549, and 3790 m) in the northern Tibetan Plateau and compared species composition, diversity indices, Levins' niche breadth, and Pianka's niche overlap. The results showed that perennial herbs replaced semi-shrubs and xermesophytes and mesophytes replaced xerophytes with increasing altitude. The plant community heights decreased with altitude. The cover of the herb layer increased with altitude, whereas that of the shrub layer was hump-shaped. Species diversity indices (Patrick, Pielou, Shannon-Wiener, and Simpson) increased with increasing altitude. Sympegma regelii (1.05), Leymus chinensis (1.03), and Reaumuria kaschgarica (0.94) had larger niche breadths and were widespread. Species with a high niche overlap occupied a considerable proportion at higher altitudes, indicating strong interactions among species. The redundancy analysis revealed that altitude, soil water content, soil organic matter content, and pH were the main factors driving changes in plant diversity (P = 0.036, F = 3.7). Our study illustrated that environmental filtering and biotic interactions jointly shape plant composition and diversity in alpine desert grasslands along altitudinal gradients.

Differential responses of the electron transfer capacities of soil humic acid and fulvic acid to long-term wastewater irrigation

Wastewater irrigation is used to supplement agricultural irrigation because of its benefits and freshwater resource scarcity. However, whether wastewater irrigation for many years affects the electron transfer capacity (ETC) of natural organic matter in soil remains unclear, and organic matter could influence the decomposition and mineralization of substances with redox characteristics in soil through electron transfer, ultimately affecting the soil environment. The composition of soil humic substances (HS) is highly complex, and the effects of soil humic acid (HA) and fulvic acid (FA) on ETC is poorly understood. In this study, we separately evaluated the responses of the electron-accepting capacity (EAC) and electron-donating capacity (EDC) of soil HA and FA in agricultural fields to various durations of wastewater irrigation. Results showed that the EAC of HA and FA increased significantly with increasing the duration of wastewater irrigation. When wastewater irrigation lasted for 56 years, the EAC of HA showed a higher increment (590 %) than that of FA (223 %). The EDC of soil HA and FA, conversely, decreased compared to the control, with the highest reduction of 35.6 % for HA and 65.9 % for FA. Specifically, the EDC of HA gradually decreased starting from 29 years of wastewater irrigation, whereas the decrease in the EDC of FA exhibited no clear pattern in relation to the duration of wastewater irrigation. Increased soil organic matter and total nitrogen content under long-term wastewater irrigation led to an increase in sucrase and phosphatase activities, along with an increase in EAC and a decrease in EDC of HS. This suggests that soil enzyme activities may ultimately lead to changes in ETC. The results of this research provide practical insights into the redox system in soil and its driving role in soil organic matter transformation and nutrient cycling under wastewater irrigation.

Remediation of petroleum hydrocarbon contaminated soils by nZVI coupled with electrokinetic activation of persulfate

This paper explores the use of nanoscale zero-valent iron (nZVI) coupled with electrically activated persulfate (nZVI-EK/PS) for remediating petroleum hydrocarbon-contaminated soil. The effects of persulfate (PS) dosage, nZVI dosage, and soil organic matter content on the remediation of petroleum hydrocarbons were investigated. The study concludes that persulfate (PS) and nanoscale zero-valent iron (nZVI) are the primary factors influencing the remediation of petroleum hydrocarbons in the nZVI-EK/PS system. The optimal reaction conditions of PS = 170 mmol and nZVI = 17 mmol increased the efficiency of petroleum hydrocarbon treatment to 40.45%, with the highest removal efficiency of petroleum hydrocarbons observed at position S2, reaching 48.5%. With the addition of organic matter at 5%, the efficiency of petroleum hydrocarbon treatment reached 50.08%, representing a 9.68% enhancement in the nZVI-EK/PS system. Furthermore, potential mechanisms for the degradation of petroleum hydrocarbons by the nZVI-EK/PS system were identified using gas chromatography-mass spectrometry (GC-MS). The degradation order of different components was found to be esters < alkenes < alkanes < phenols.

EFFECT OF PROBIOTIC TREATMENT ON THE MICROBIOLOGICAL ACTIVITY OF UKRAINIAN TYPICAL BLACK SOIL

The search for novel substances that promote the establishment of a microbial community and facilitate optimal humification processes while increasing soil organic matter content offers an opportunity for land restoration. The objective of study was to determine the abundance of ecological and trophic groups of soil microorganisms and the intensity of microbiological processes when subjected to probiotic treatment at various concentrations and doses in typical black soil. The eco-trophic groups of soil microorganisms were identified by inoculating dilutions of soil suspensions onto selective nutrient media. The direction and intensity of soil microbiological processes were assessed using the mineralization-immobilization, oligotrophy, and pedotrophy indexes. The results demonstrate that probiotics has a positive impact on the microbiological activity of the soil, leading to an increase in the number of ecological and trophic groups of soil microorganisms during both spring and autumn seasons. Notably, a significant effect on the soil microorganism conditions was observed after 30 days of probiotic treatment. Probiotics exhibit a favorable influence on microbiological processes within the soil, fostering conducive conditions for the development of soil microorganisms and the formation of humus. The most effective concentration of probiotics for promoting the functionality of microbial communities in black soils is determined to be 10%, accompanied by a dose of 100 l ha-1. Consequently, the application of probiotic treatment at a concentration of 10% and a dose of 100 l/ha-1 holds the potential to enhance the biological state of the soil, restore soil microbial diversity, and serve as an environmentally safe fertilizer.

Hyperspectral estimation model of soil organic matter content based on principal gradient grey information

PurposeIn order to explore a new estimation approach of hyperspectral estimation, this paper aims to establish a hyperspectral estimation model of soil organic matter content with the principal gradient grey information based on the grey information theory.Design/methodology/approachFirstly, the estimation factors are selected by transforming the spectral data. The eigenvalue matrix of the modelling samples is converted into grey information matrix by using the method of increasing information and taking large, and the principal gradient grey information of modelling samples is calculated by using the method of pro-information interpolation and straight-line interpolation, respectively, and the hyperspectral estimation model of soil organic matter content is established. Then, the positive and inverse grey relational degree are used to identify the principal gradient information quantity of the test samples corresponding to the known patterns, and the cubic polynomial method is used to optimize the principal gradient information quantity for improving estimation accuracy. Finally, the established model is used to estimate the soil organic matter content of Zhangqiu and Jiyang District of Jinan City, Shandong Province.FindingsThe results show that the model has the higher estimation accuracy, among the average relative error of 23 test samples is 5.7524%, and the determination coefficient is 0.9002. Compared with the commonly used methods such as multiple linear regression, support vector machine and BP neural network, the hyperspectral estimation accuracy of soil organic matter content is significantly improved. The application example shows that the estimation model proposed in this paper is feasible and effective.Practical implicationsThe estimation model in this paper not only fully excavates and utilizes the internal grey information of known samples with “insufficient and incomplete information”, but also effectively overcomes the randomness and grey uncertainty in the spectral estimation. The research results not only enrich the grey system theory and methods, but also provide a new approach for hyperspectral estimation of soil properties such as soil organic matter content, water content and so on.Originality/valueThe paper succeeds in realizing both a new hyperspectral estimation model of soil organic matter content based on the principal gradient grey information and effectively dealing with the randomness and grey uncertainty in spectral estimation.

Effects of Application of Different Organic Materials on Phosphorus Accumulation and Transformation in Vegetable Fields

Presently, the improvement of soil organic matter is the basis to ensure food security, but the accumulation and transformation characteristics of soil phosphorus (P) as affected by organic matter remain unclear. The accumulation, transformation, and migration characteristics of soil P in different soil layers of vegetable fields were researched under the application of organic materials. Six treatments were set up in the experiment:control (no fertilization), traditional fertilizer application by farmers, biochar, chicken manure, food waste, and straw application. Available phosphorus (Olsen-P), water-soluble phosphorus (CaCl2-P) content, soil phosphorus forms, soil organic matter (SOM), and pH were determined during the pepper harvest period. In the 0-5 cm and 5-10 cm soil layers, the available phosphorus content of traditional fertilization of farmers was higher, and the available phosphorus content of the four organic materials was in the order of straw &gt; biochar &gt; chicken manure &gt; food waste. Compared to that with food waste, the straw and biochar treatments increased soil available phosphorus by 59.6%-67.3% and 29.1%-36.9%, respectively. The straw treatment could easily enhance the soil labile P pool, and soil labile P in the 0-5 cm soil layer increased by 47.3% and 35.1% compared with that under the chicken manure and food waste treatments, respectively. With the increase in soil depth, the proportion of available phosphorus in the chicken manure treatment decreased the least, and available phosphorus of the 20-30 cm soil layer accounted for 55.9% of the topsoil layer but only accounted for 16.0%-34.0% under treatment with the other three materials. Compared with that under the traditional fertilization of farmers, the pH significantly increased by 0.18-0.36 units after the application of organic fertilizer, and the pH of the chicken manure and food waste treatments was significantly higher than that of biochar and straw (P &lt; 0.05). SOM content under the biochar treatment significantly increased by 7.7%-17.6% compared to that under the other three organic materials. Among the four organic materials, the straw treatment boosted the labile P pool the most, which was conducive to the rapid increase in plant-available P. Phosphorus was most likely to migrate downward under the chicken manure treatment. In the field management based on soil fertility enhancement, the application of biochar could not only improve soil pH and SOM but also avoid excessive accumulation of phosphorus in the surface layer, which decreases environmental risks.

Green Manuring Enhances Soil Multifunctionality in Tobacco Field in Southwest China.

The use of green manure can substantially increase the microbial diversity and multifunctionality of soil. Green manuring practices are becoming popular for tobacco production in China. However, the influence of different green manures in tobacco fields has not yet been clarified. Here, smooth vetch (SV), hairy vetch (HV), broad bean (BB), common vetch (CV), rapeseed (RS), and radish (RD) were selected as green manures to investigate their impact on soil multifunctionality and evaluate their effects on enhancing soil quality for tobacco cultivation in southwest China. The biomass of tobacco was highest in the SV treatment. Soil pH declined, and soil organic matter (SOM), total nitrogen (TN), and dissolved organic carbon (DOC) content in CV and BB and activity of extracellular enzymes in SV and CV treatments were higher than those in other treatments. Fungal diversity declined in SV and CV but did not affect soil multifunctionality, indicating that bacterial communities contributed more to soil multifunctionality than fungal communities. The abundance of Firmicutes, Rhizobiales, and Micrococcales in SV and CV treatments increased and was negatively correlated with soil pH but positively correlated with soil multifunctionality, suggesting that the decrease in soil pH contributed to increases in the abundance of functional bacteria. In the bacteria-fungi co-occurrence network, the relative abundance of key ecological modules negatively correlated with soil multifunctionality and was low in SV, CV, BB, and RS treatments, and this was associated with reductions in soil pH and increases in the content of SOM and nitrate nitrogen (NO3--N). Overall, we found that SV and CV are more beneficial for soil multifunctionality, and this was driven by the decrease in soil pH and the increase in SOM, TN, NO3--N, and C- and N-cycling functional bacteria.

Assessment of Effects of Amended Bioremediation of Toxic Metal-polluted Soil using Organic Composites and Bacillus sp on Plant Growth Parameters

It has become pertinent to develop improved bioremediation techniques, to avert the deleterious effects of heavy metal pollution on agricultural productivity, and safety of its produce. In this study, cow dung, poultry wastes and their composites used as organic amendments were collected and processed, while Bacillus sp used as plant growth promoting rhizosphere was isolated and identified. Then 24 kg of fertile soil was polluted by introducing 20 mL of 0.1M lead acetate solution, before bagging 5 kg of polluted soil into ten perforated nylons. Soil sample was then analyzed before and after treatment. After mixing with Bacillus sp suspension, two of the pot experiments were amended with each of 0.5 kg cow dung only, 0.5 kg poultry wastes only and 1:1 ratio of their composites. Control samples were set up without amendment, and they were bioremediated for 25 days. Following germination of sown corn seedlings, heights of their shoots and number of leaves were monitored on day 4, weeks 2, 4 and 7, before harvesting for analysis together with soil samples. Results obtained revealed that seedlings grown on treated samples as well as properties of treatment of soil were generally better than those of control samples. Highest percentage increase in organic matter content of soil was recorded in treatment with mixture of cow dung only and Bacillus sp, with 9.28% and 7.63% increase at 33.75 mg/kg and 52.55 mg/kg of lead (Pb) pollution. Seedlings grown on samples treated with poultry wastes only, recorded the highest protein content of 161.25±5.5 mg/g, 104.99±4.95 mg/g and 79.75±3.2 mg/g protein contents, at 32.75 mg/kg, 42.02 mg/kg and 52.44 mg/kg levels of Pb pollution, respectively. The amendments also reduced bioaccumulation of Pb in corn seedlings, which was in the order; stem&lt;leaf&lt;root. Therefore, these amendments can be exploited for improved bioremediation of heavy metals.

Does biochar combined with cover crops improve health and productivity of sandy, sloping, and semi‐arid soils?

AbstractBiochar may improve the health of environmentally sensitive soils (i.e., low C, sandy, sloping) especially if combined with cover crops (CCs), but research is scant. We assessed how wood biochar (836 g C kg−1) applied at 0, 6.25, 12.5, 25, and 50 Mg ha−1 to sandy, sloping, and semi‐arid soils with and without CCs affects soils and crop yields in the central US Great Plains for 3 years. We measured crop yields and CC biomass each year, and most soil properties in Years 1 and 3. Biochar did not interact with CCs, suggesting the combination was no better than biochar or CC alone. In the semi‐arid soil, crop and CC did not establish due to persistent droughts. Biochar benefits were highly site‐specific. Biochar improved some soil properties but only in the sandy and sloping soils and at the biochar application depth (0‐ to 15‐cm soil depth). The 50 Mg biochar ha−1 improved the soil's ability to sorb water (0.08 cm s−1/2). Also, in the sandy soil, it increased soil organic matter concentration (2.5 g kg−1), soil pH (0.65 units), and available water (0.07 m3 m−3) only in Year 1, suggesting a biochar benefit in sandy soils is short‐lived. In the sloping soil, &gt;25 Mg biochar ha−1 reduced bulk density (0.16 Mg m−3) and increased soil mean weight diameter of water‐stable aggregates (0.58 mm), organic matter concentration (11.42 g kg−1), infiltration (9.35 cm), CC biomass production (0.27 Mg ha−1), and some microbial biomass groups. Biochar did not affect crop yields. Overall, &gt;25 Mg biochar ha−1 improved properties in some soils without interacting with CCs.

Shifts in controls and abundance of particulate and mineral-associated organic matter fractions among subfield yield stability zones

Abstract. Spatiotemporal yield heterogeneity presents a significant challenge to agricultural sustainability efforts and can strain the economic viability of farming operations. Increasing soil organic matter (SOM) has been associated with increased crop productivity, as well as the mitigation of yield variability across time and space. Observations at the regional scale have indicated decreases in yield variability with increasing SOM. However, the mechanisms by which this variability is reduced remain poorly understood, especially at the farm scale. To better understand the relationship between SOM and yield heterogeneity, we examined its distribution between particulate organic matter (POM) and mineral-associated organic matter (MAOM) at the subfield scale within nine farms located in the central United States. We expected that the highest SOM concentrations would be found in stable, high-yielding zones and that the SOM pool in these areas would have a higher proportion of POM relative to other areas in the field. In contrast to our predictions, we found that unstable yield areas had significantly higher SOM than stable yield areas and that there was no significant difference in the relative contribution of POM to total SOM across different yield stability zones. Our results further indicate that MAOM abundance was primarily explained by interactions between crop productivity and edaphic properties such as texture, which varied amongst stability zones. However, we were unable to link POM abundance to soil properties or cropping system characteristics. Instead, we posit that POM dynamics in these systems may be controlled by differences in decomposition patterns between stable and unstable yield zones. Our results show that, at the subfield scale, increasing SOM may not directly confer increased yield stability. Instead, in fields with high spatiotemporal yield heterogeneity, SOM stocks may be determined by interactive effects of topography, weather, and soil characteristics on crop productivity and SOM decomposition. These findings suggest that POM has the potential to be a useful indicator of yield stability, with higher POM stocks in unstable zones, and highlights the need to consider these factors during soil sampling campaigns, especially when attempting to quantify farm-scale soil C stocks.

Estimation of soil moisture and organic matter content in saline alkali farmland by using CARS algorithm combined with covariates

Rapid acquisition of the data of soil moisture content (SMC) and soil organic matter (SOM) content is crucial for the improvement and utilization of saline alkali farmland soil. Based on field measurements of hyperspectral reflectance and soil properties of farmland soil in the Hetao Plain, we used a competitive adaptive reweighted sampling algorithm (CARS) to screen sensitive bands after transforming the original spectral reflectance (Ref) into a standard normal variable (SNV). Strategies Ⅰ, Ⅱ, and Ⅲ were used to model the input variables of Ref, Ref SNV, Ref-SNV+ soil covariate (SC), and digital elevation model (DEM). We constructed SMC and SOM estimation models based on random forest (RF) and light gradient boosting machine (LightGBM), and then verified and compared the accuracy of the models. The results showed that after CARS screening, the sensitive bands of SMC and SOM were compressed to below 3.3% of the entire band, which effectively optimized band selection and reduced redundant spectral information. Compared with the LightGBM model, the RF model had higher accuracy in SMC and SOM estimation, and the input variable strategy Ⅲ was better than Ⅱ and Ⅰ. The introduction of auxiliary variables effectively improved the estimation ability of the model. Based on comprehensive analysis, the coefficient of determination (Rp2), root mean square error (RMSE), and relative analysis error (RPD) of the SMC estimation model validation based on strategy Ⅲ-RF were 0.63, 3.16, and 2.01, respectively. The SOM estimation models based on strategy Ⅲ-RF had Rp2, RMSE, and RPD of 0.93, 1.15, and 3.52, respectively. The strategy Ⅲ-RF model was an effective method for estimating SMC and SOM. Our results could provide a new method for the rapid estimation of soil moisture and organic matter content in saline alkali farmland.