Content In Agricultural Soils Research Articles

Различные формы Sr в агротемногумусовых подбелах юга Приморского края

To assess the concentration level and identify the main phase-carriers of various forms of strontium (Sr), the total content, distribution and concentration of water-soluble forms of the element in Albic Stagnosoils, which composed the bulk of the arable fund of the region under study, were studied. Full-profile soil pits were dug at the long-term fallow, phytoreclamative, and fertilized with mineral and organic fertilizer variants of the experience. The study of the different Sr forms contents was carried out by energy dispersive X-ray fluorescence spectroscopy and atomic absorption spectrometry. The main Sr volume was immobilized in the composition of soil mineral phase in soils of all variants of the experience. The addition of mineral fertilizers to soil was accompanied by an increase in the total content (by 6.4 %) and concentration of water-soluble (by 5,7 times) Sr forms, compared to the soil of fallow, and intensification of Sr sorption by Mn-containing soil compounds. The long-term addition of different types of organic fertilizers contributed to the activation of stable Sr-organic complexes formation. Under a green manure application in conditions of soil solution acidity decrease, the increase in the influence of Ca-containing soil compounds on the distribution of Sr has been shown. The soils of all variants of the experience were characterized by the absence of factors and conditions that contributed to the Sr accumulation in profiles, it was suggested by the lower total Sr content compared to the mean background content for surface soils around the world and to the mean content in agricultural soils in Japan.

Effects of Tillage and Straw Mulching on Soil Hydrothermal and Nutrient Content in Agricultural Soil

Long-term intensive tillage has led to soil environment degradation, reduced fertility, and difficulty in increasing crop yield in the Mollisol region of northeast China. In order to improve the soil’shydrothermal environment and nutrient content, we conducted field experiments to investigate the effects of different tillage practices and the amount of straw mulching on soil hydrothermal environment and nutrient content in agricultural soils in seasonal permafrost areas. Four treatments were established: no-tillage without straw (NT0), no-tillage with half straw mulching (NT1), no-tillage with full straw mulching (NT2), and rotary tillage without straw (CK) as the control treatment. The results indicate that the no-tillage with straw mulching treatments increased the soil ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3−-N) content, accompanied by improvements in the soil’s water content and regulation of soil temperature changes, as compared to the CK treatment. Specifically, the soil’s NH4+-N and NO3−-N content in the NT2 treatment were significantly increased by 25.65% and 38.81%, respectively. Our study indicates that NT2 treatment is the most suitable tillage practice and straw-returning method in the Mollisol region of northeast China. This study can provide a theoretical basis and reference for the efficient utilization of farmland soil in seasonal permafrost areas.

Near Infrared Spectroscopy for Rapid Prediction of Soil Organic Carbon Content in Agricultural Soils

Near Infrared Spectroscopy for Rapid Prediction of Soil Organic Carbon Content in Agricultural Soils

Soil silicon availability and silicon uptake by winter wheat in Tokachi district, Hokkaido

ABSTRACT Silicon (Si) is the second most abundant element in soils and is a beneficial element for plant growth, particularly for gramineous plants such as rice, corn, and wheat. In Japan, soil Si availability and its relationship with Si in plants have been mainly focused on paddy soils and rice. Although Si has also been reported to benefit wheat production via enhanced phosphorous uptake and resistance to diseases, there is little study on Si availability in agricultural soils related to wheat production in Japan. The objectives of this study were to (1) assess the soil available Si and its relation to other soil properties in upland fields, (2) evaluate Si concentration and its distribution in winter wheat, (3) clarify the relationship between the soil available Si and the Si concentration in wheat, and (4) identify suitable methods to determine available Si for agricultural soils. Surface soil and wheat samples were collected from 40 growers’ field along four different river terraces including lowland, low terrace, middle terrace, and high terrace of the Tokachi district in 2020 and 2021. Soil available Si was evaluated by three methods using acetate buffer and phosphate buffer solution. The soil available Si contents in agricultural soils varied from field to field considerably, and were remarkably larger in the fields located on the middle and high terraces compared to the lowland and the low terrace, suggesting the effects of soil parent materials and pedogenic factors, particularly volcanic ashes and amorphous clay minerals. The mean Si uptake by winter wheat was 13.4 g m−2 and comparable to N and K uptake and greater than P. Winter wheat mainly stores Si in culms, leaves and husks, and the highest mean concentration of Si in above-ground part of winter wheat was 27.6 g kg−1 in husks. The high Si concentration in the husk may be related to enhancing plant physical protection to preharvest sprouting and fungal diseases. Among three methods, the acetate buffer solution method could be the most promising method to determine soil Si availability in agricultural soils of the studied area.

Accurate Quantification of 0–30 cm Soil Organic Carbon in Croplands over the Continental United States Using Machine Learning

Increases in organic carbon within agricultural soils are widely recognized as a “negative emission” that removes CO2 from the atmosphere. Accurate quantification of soil organic carbon (SOC) to a certain depth in the spatial domain is critical for the effective implementation of improved land management practices in croplands. Currently, there is a lack of understanding regarding what depth strategy should be used to estimate SOC at 0–30 cm when sample datasets come from multiple depths. Furthermore, few studies have examined depth strategies for mapping SOC at the agricultural management level (i.e., field level), opting instead for point-based analysis. Here, three types of approaches with different depth strategies were evaluated for their ability to quantify 0–30 cm SOC content based on soil samples from 0–5 (surface), 5–30 (subsurface), and 0–30 cm (full column). These approaches involved the generalized additive model and machine learning techniques, i.e., artificial neural networks, random forest, and XGBoost. The soil samples used for the model evaluation and selection consisted of the newly collected samples in 2020–2022 and the Rapid Carbon Assessment (RaCA) legacy samples collected in 2010–2011. Environmental covariates corresponding to these SOC measurements were used in model training, including long-term physical climate, short-term weather, topographic and edaphic, and remotely sensed variables. Among the models evaluated in this study, the XGB regression model with a full column depth assignment strategy yielded the best prediction performance for 0–30 cm SOC content, with an r2 (squared Pearson correlation coefficient) of 0.48, an RMSE (root mean square error) of 0.29%, an ME (mean error) of 0.06%, an MAE of 0.25%, and an MEC (modeling efficiency coefficient) of 0.36 at the pixel level and an r2 of 0.64, an RMSE of 0.32%, an ME of −0.20%, an MAE of 0.28%, and an MEC of 0.48 at the field level. This study highlights that machine learning models with a full column depth strategy should be used to quantify 0–30 cm SOC content in agricultural soils over the continental United States (CONUS).

Earthworms facilitate stabilization of both more-available maize biomass and more-recalcitrant maize biochar on mineral particles in an agricultural soil

Agricultural soils have lost enormous amounts of soil organic matter (SOM) as the result of conventional agriculture. Nowadays, returning plant biomass in the form of crop residues is used as an efficient strategy to increase the amount of SOM. In addition, earthworms help increase the SOM content by transforming OM into stable forms. There is, however, limited information on how earthworms transform and stabilize various forms of crop residues and what the potential feedbacks on soil quality are. In a five-month laboratory manipulation experiment, we added maize biomass and/or biochar to a temperate agricultural soil both in the presence and absence of earthworms and carried out physical fractionation to analyse the stabilization of OM either as aggregate-occluded particulate OM (oPOM) or mineral-associated OM (MAOM).We show that the combination of maize biomass, maize biochar and earthworms proved to be highly efficient in increasing the OM content in agricultural soils and that earthworms can simultaneously enhance both OM decomposition and stabilization. In the absence of earthworms, the OM was stabilized more in the oPOM fraction, suggesting that both maize substrates acted as aggregation agents. In the presence of earthworms, however, maize substrates were stabilized more in the MAOM fraction, either through direct sorption as plant-derived substrates or as microbial necromass, suggesting that earthworms facilitate stabilization of both more-available maize biomass and more-recalcitrant maize biochar on mineral particles. We provide evidence that plant-derived rather than microbial-derived MAOM is present in the earthworm-affected agricultural soil and is thus important in increasing the SOM content and stability.

Heavy Metal Pollution Assessment in the Agricultural Soils of Bonao, Dominican Republic

Heavy metal content in agricultural soils potentially impacts the food chain and human health. The present study assessed the levels of heavy metals in topsoil samples collected within an agricultural region situated in Bonao, Dominican Republic. The Energy-Dispersive X-ray Fluorescence (EDXRF) technique was utilized to measure the concentrations of iron (Fe), manganese (Mn), chromium (Cr), copper (Cu), nickel (Ni), zinc (Zn), lead (Pb), and arsenic (As) in the samples. The assessment of soil pollution status and potential ecological risk (RI) involved the utilization of various soil pollution indices, such as the single pollution index (PI), integrated pollution index (IPI), and enrichment factor (EF). The average total concentrations of Fe, Mn, Cr, Cu, Ni, Zn, Pb, and As were 103,000, 2000, 347, 36, 92, 32, 9.6, and 4.2 mg·kg−1, respectively. The results showed that the Mn, Ni, Cu, and As levels exceeded the Food and Agriculture Organization (FAO)’s recommended levels for healthy agricultural soils. The distribution pattern of each individual metal was different, indicating they had different sources of origin. The average pollution indices indicated low-to-moderate pollution, and the potential ecological risk obtained was low. This study emphasizes the need for soil management practices to mitigate heavy metal contamination for food safety and environmental health.

Assessment of the Carbon Content in Agricultural Soils of the European Russia for Climate Projects

Assessment of the Carbon Content in Agricultural Soils of the European Russia for Climate Projects

Biogeochemical State of Salinized Irrigated Soils of Central Fergana (Uzbekistan, Central Asia)

The Central Fergana region is one of the overpopulated regions of Central Asia, which includes parts of Uzbekistan, Kyrgyzstan, and Tajikistan. Here, in the dry subtropical climate are the most ancient, irrigated oases used for agriculture. Fergana valley is the key to the food security of the region as a whole. The article provides information on diversity and chemical composition of newly developed, new and old-irrigated Calcisols soils formed on alluvial and alluvial–prolluvial sediments. Soils are poor with organic matter (0.37–0.81% of organic carbon), with high nitrogen content (C/N ratio is 4.92–5.79), and with neutral (7.01–7.30) pH values. Data on the content and the ratio of the key components of soil salinity (Na2CO3, Ca(HCO3)2, CaSO4, MgSO4, Na2SO4, NaCl) and the bulk content of salts in soils under different irrigation regimes are presented. It was shown that Na2CO3 concentration is minimal in all the soils, and this salt presents only in ground waters (0.100–0.135 g L−1). Newly irrigated soils are characterized by higher content of salts than old irrigated soils. All the soils investigated are characterized by increasing salinity rate within the soil depth with the highest content of all salts in ground waters. This chloride–sulfate type of salinization is most pronounced in all the soils studied. Gypsum content in agricultural soils results in limited water and nutrient retention and the potential for dissolution, primarily in response to irrigation. The soils of the Fergana Valley are also subjected to polychemical pollution, so the content of trace elements in them was studied. Irrigated meadow-takyr and meadow-saz soils show low levels of environmental hazard, but irrigation results in accumulation of such trace elements as nickel (30 mg kg−1), arsenic (11.75 mg kg−1), bromine (5.00 mg kg−1), antimony (1.48 mg kg−1), cesium (5.00 mg kg−1), and hafnium (2.97 mg kg−1). Irrigation also affects the soil texture and thus increases fine particle percentages in the superficial soil horizons. Thus, the complex chemical characteristics of salinized soils are presented for numerous irrigated landscapes of the region.

Available and total phosphorus background levels in soils: a calcareous and semi-arid region

It is critical to understand the risk of element pollution in soils by evaluating their background levels. Phosphorus (P) content in agricultural soils needs to be assessed from agronomic and environmental standpoints. The current study intended to calculate the background levels of available and total P in soils. To achieve this goal, 50 sites without human activities were selected. Soils were sampled from the surface and subsurface of each site (100 soil samples). The available P forms in soils were extracted using the water-extractable P (WEP), calcium chloride-extractable P (CCEP), and Olsen-extractable P (OEP) methods. The first two extractants are being used to evaluate P leaching from soils, while the last one is being used as an agronomic indicator. The methods used to calculate background levels were the iterative 2-δ technique (2-δ) and the calculated distribution function (CDF). Results showed that the upper limits of background levels using 2-δ method were 1.45, 0.92, 8.12, and 424.4mgkg-1 for WEP, CCEP, OEP, and total P, respectively. Also, the upper limits of background levels using CDF method were 1.42, 1.15, 12.09, and 447.6mgkg-1, for WEP, CCEP, OEP, and total P, respectively. It can be concluded that using these background levels, which for the first time were calculated for P, would enable us to have an accurate examination of P excess as a result of human activities.

Seasonal comparative geochemistry of ultra trace elements content in agricultural soils near Lake Sevan

The contamination status of the soils from Hrazdan, Gavar, and Martuni regions has been investigated by comparing UTEs indicators with % humus and pH in soil samples during different seasonal intervals steppe chernozem soil type was studied. It was found that the maximum of % humus exceeded the minimum % almost twice in the soil samples. The soil samples were found to be neutral in terms of pH character. The results for the Hrazdan region show on 10% increase of barium content and 70% decrease of arsenic content in soil samples taken in winter 2022 compared to the whole period studied. For spring 2022, the same variant shows on 27% increase of chromium and 19% of vanadium. The change in nickel content was within the average for the whole period. The results for the Gavar region show an average dynamic increase of 22% of barium content in soil samples from autumn 2021 to spring 2022 compared to the whole sampling period. The change of the content other UTEs was within the average value for the whole sampling period. Alternating decreases (winter and summer 2022) and increases (autumn 2021 and spring 2022) of the barium content were observed in the soil samples from the Martuni region. The change of UTEs content in the soil was within the average value for the whole period sampled. The increased value of the Zc coefficient in autumn was found to be typical for all investigated regions, although the values vary. The highest value of the coefficient is observed in the Hrazdan region and the lowest value in the Martuni region.

Fluoride in a tropical wetland agroecosystem and its relationship with soil properties

Elevated fluoride content in agricultural soils has now become an emerging global concern. The objective of this study was to evaluate the soil properties and fluoride content in the Kuttanad wetlands of south India and to examine whether these soil properties do have any relationship with fluoride content. Soil samples collected from 15 locations of Kuttanad rice fields were analyzed for its properties, total fluoride, available nutrients, and elemental oxides using standard procedures. The study revealed that the soils (Inceptisols) are predominantly sandy with substantial clay fraction. Among the soil properties, bulk density (BD), moisture and temperature, electrical conductivity (EC), cation exchange capacity (CEC) and available nitrogen (N) remained within the normal limit and organic carbon (OC) available phosphorus (P) (94.50 kg h−1), potassium (K) (383.0 kg h−1) and total fluoride (F) (38.7 mg kg−1) in a higher level. Soil properties such as pH (0.331**), EC (0.874**), CEC (0.797**), OC (0.578**), available N (0.633**) and P (0.855**) showed positive relationship with fluoride content in soil whereas, the relationship between available K (− 0.721**), iron (Fe) and aluminium (Al) sesquioxides (− 0.866**) were negative. Our finding suggests that elevated fluoride content in soils of Kuttanad is influenced by pH, EC, CEC, OC, N and P besides being inherited from the parent material. The study warrants the need of considering these variables while adopting the fluoride mitigation strategies in this agroecosystem.

Heavy metal assessment in agricultural soils and vegetables in the vicinity of industrial pollutants in the Pljevlja municipality (Montenegro): ecological and health risk approach.

This paper aims to assess ecological and health risks associated with heavy metal (As, Hg, Cd, Pb, Cu, Zn, Cr) content in agricultural soils and vegetables (potato tuber, beetroot, onion bulb, carrot root) collected near the lead and zinc mine (MLZ), coal-fired power station (CFPS) and coal mine (CM) located in Pljevlja municipality (Montenegro). The ecological risk of soil was estimated using the ecological risk index (RI) and pollution load index (PLI). The health risk was evaluated through different soil exposure pathways (ingestion, inhalation, dermal contact) and vegetable consumption. The pollution indices RI and PLI indicated the highest contamination in MLZ study area followed by CM and CFPS areas. RI values revealed considerable contamination in MLZ and CM study areas, while CFPS area is moderately contaminated by heavy metals. According to PLI, soil in MLZ and CM areas is classified as polluted, while the soil in the vicinity of CFPS is classified as unpolluted. Non-carcinogenic and carcinogenic health risks through soil exposure were identified for both children and adults, in all investigated areas. Dermal contact was identified as the main contributor to carcinogenic risk. Dermal contact was also identified as the main exposure pathway for non-carcinogenic risk in MLZ area, while for CFPS and CM areas, ingestion was the main exposure route. As for vegetables, only Cu and Zn were detected in all examined vegetables. Non-cancerogenic health risk of edible vegetable consumption was found for children in all study areas, while there was no health risk for adults.

Decadal trends in soil and grain microelement concentrations indicate mainly favourable development in Finland

AbstractBackgroundObservations on declining nutrient contents in crops have raised concerns about soil fertility and food quality. Long‐term monitoring data are valuable in exposing trends and indicating the need for interventions.AimsThis study aimed to assess the soil microelement status and grain nutritional value on a national scale in Finland over the last decades.MethodsUsing nationwide sets of samples and time‐series datasets, temporal trends in readily available zinc, copper, boron, iron, manganese, cadmium, molybdenum, nickel, aluminium, cobalt, and lead in cultivated soils of Finland during 1974–2018 and the corresponding total element concentrations in grains of oats and barley during 1988–2019 were determined.ResultsIn soil, initially increasing trends of element concentrations tended to prevalently level off towards the end of the study period. A decreasing trend was observed only for cadmium and zinc in coarse soils. In grains of barley and oat, aluminium and lead concentrations decreased between 1988 and 2019. Barley grains exhibited a decreasing trend in manganese and cobalt, whereas an increasing trend was detected for copper and iron in oats.ConclusionsNo alarming decreases in micronutrient contents in agricultural soils or cereal grains were detected over the study period. In grains, the concentrations of potentially toxic elements decreased. Although the nationwide micronutrient status in Finland is on average satisfactory or good, local micronutrient deficiencies may occur.

Using multispectral variables to estimate heavy metals content in agricultural soils: A case of suburban area in Tianjin, China

Efficient estimation and mapping of soil heavy metal concentrations based on rapid and environmentally friendly multispectral data can provide a reference for the prevention and control of non-point source pollution and safety in ecosystems. In this study, the spatial variation of soil heavy metals (As, Cd, Cr, Cu, Ni, and Zn) in Wuqing was analyzed with 394 and 57 soil samples gathered in 2005 and 2019. Based on these samples, as well as multispectral variables (raw bands and their respective vegetation index and derivative transformation), random forest-ordinary kriging (RFOK) and artificial neural network-ordinary kriging (ANNOK) were combined to predict spatial variations of heavy metal content. Results indicated that the mean values of soil As, Cd, Cr, Cu, and Zn in 2019 exceeded their respective concentrations in 2005 by 1.40, 1.36, 1.12, 1.12, and 1.35 times, and exceeded the standard rate of background values (BGV) in 2019 for all soil heavy metals (except for Ni). Compared to RF, ANN, and RFOK, the ANNOK method exhibited the best estimation performance for As (R20052= 69.47% andR20192= 65.03%), Cd (R20052= 64.48% andR20192= 64.20%), Cr (R20052= 72.02% andR20192= 70.65%), Cu (R20052= 72.05% andR20192= 70.53%), Ni (R20052= 69.37% andR20192= 66.03%), and Zn (R20052= 71.16% andR20192= 67.11%) in the validation dataset. Mapping of heavy metals derived from ANNOK revealed a similar distribution in 2005 and 2019, where the high concentrations of all soil heavy metals were in the southern part of the study area. The effects of multispectral bands as indicated by vegetation index and derivative transformation exhibited sensitivity for predicting soil heavy metals based on hybrid geostatistical methods. Overall, greater efficiency of spatial estimation for the content of soil heavy metals is important for the prevention and control of non-point source pollution.

Scale-Specific Prediction of Topsoil Organic Carbon Contents Using Terrain Attributes and SCMaP Soil Reflectance Composites

There is a growing need for an area-wide knowledge of SOC contents in agricultural soils at the field scale for food security and monitoring long-term changes related to soil health and climate change. In Germany, SOC maps are mostly available with a spatial resolution of 250 m to 1 km2. The nationwide availability of both digital elevation models at various spatial resolutions and multi-temporal satellite imagery enables the derivation of multi-scale terrain attributes and (here: Landsat-based) multi-temporal soil reflectance composites (SRC) as explanatory variables. In the example of a Bavarian test of about 8000 km2, relations between 220 SOC content samples as well as different aggregation levels of the explanatory variables were analyzed for their scale-specific predictive power. The aggregation levels were generated by applying a region-growing segmentation procedure, and the SOC content prediction was realized by the Random Forest algorithm. In doing so, established approaches of (geographic) object-based image analysis (GEOBIA) and machine learning were combined. The modeling results revealed scale-specific differences. Compared to terrain attributes, the use of SRC parameters leads to a significant model improvement at field-related scale levels. The joint use of both terrain attributes and SRC parameters resulted in further model improvements. The best modeling variant is characterized by an accuracy of R2 = 0.84 and RMSE = 1.99.

Organic amendments, deficit irrigation, and microbial communities impact extracellular polysaccharide content in agricultural soils

Soil extracellular polysaccharides (EPSac) can improve irrigation water productivity in agriculture by increasing soil aggregate stability and retaining water on and around plant roots. However, limited studies assay soil EPSac directly from field trials and to date no studies have examined the long-term confounding impacts of organic amendments and deficit irrigation on soil EPSac and the underlying microbial communities. We quantified soil aggregate stability, EPSac content, chemical properties, and microbial community compositions and abundances in separate field studies in turfgrass and tomato. Soil samples were collected 4–5 years after soil amendment with compost, biochar, their combination, or biosolids from plots that had received full and deficit irrigation regimens for 4 years. Amending the soil with compost, with or without biochar co-application, enhanced soil total carbon, aggregate stability, EPSac, and total soil microbial biomass and shifted microbial community structures, trends which were more pronounced under turfgrass than for tomato. In both sites deficit irrigation treatments had higher quantities of soil EPSac per unit of microbial biomass. Indicators of microbial physiological stress and ubiquitous classes of soil bacteria were associated with soil EPSac production. These results provide mechanistic understanding of organic amendment benefits in drought-impacted and deficit-irrigated agriculture.

Estimation of Soil Organic Carbon Contents in Croplands of Bavaria from SCMaP Soil Reflectance Composites

For food security issues or global climate change, there is a growing need for large-scale knowledge of soil organic carbon (SOC) contents in agricultural soils. To capture and quantify SOC contents at a field scale, Earth Observation (EO) can be a valuable data source for area-wide mapping. The extraction of exposed soils from EO data is challenging due to temporal or permanent vegetation cover, the influence of soil moisture or the condition of the soil surface. Compositing techniques of multitemporal satellite images provide an alternative to retrieve exposed soils and to produce a data source. The repeatable soil composites, containing averaged exposed soil areas over several years, are relatively independent from seasonal soil moisture and surface conditions and provide a new EO-based data source that can be used to estimate SOC contents over large geographical areas with a high spatial resolution. Here, we applied the Soil Composite Mapping Processor (SCMaP) to the Landsat archive between 1984 and 2014 of images covering Bavaria, Germany. Compared to existing SOC modeling approaches based on single scenes, the 30-year SCMaP soil reflectance composite (SRC) with a spatial resolution of 30 m is used. The SRC spectral information is correlated with point soil data using different machine learning algorithms to estimate the SOC contents in cropland topsoils of Bavaria. We developed a pre-processing technique to address the issue of combining point information with EO pixels for the purpose of modeling. We applied different modeling methods often used in EO soil studies to choose the best SOC prediction model. Based on the model accuracies and performances, the Random Forest (RF) showed the best capabilities to predict the SOC contents in Bavaria (R² = 0.67, RMSE = 1.24%, RPD = 1.77, CCC = 0.78). We further validated the model results with an independent dataset. The comparison between the measured and predicted SOC contents showed a mean difference of 0.11% SOC using the best RF model. The SCMaP SRC is a promising approach to predict the spatial SOC distribution over large geographical extents with a high spatial resolution (30 m).

Pulp and paper mill sludges decrease soil erodibility.

Declining carbon (C) content in agricultural soils threatens soil fertility and makes soil prone to erosion, which could be rectified with organic soil amendments. In a 4‐yr field trial, we made a single application of three different organic sludges from the pulp and paper industry and studied their effects on cereal yield, soil C content, and fungal and bacterial composition. In laboratory rainfall simulations, we also studied the effects of the soil amendments on susceptibility to erosion and nutrient mobilization of a clay‐textured soil by measuring the quality of percolation water passing through 40‐cm intact soil monoliths during 2‐d rainfall simulations over four consecutive years after application. A nutrient‐poor fiber sludge reduced wheat yield in the first growing season, but there were no other significant effects on cereal yield or grain quality. An input of ∼8 Mg ha−1 C with the soil amendments had only minor effects on soil C content after 4 yr, likely because of fast microbe‐mediated turnover. The amendments clearly changed the fungal and bacterial community composition. All amendments significantly reduced suspended solids (SS) and total phosphorus (TP) concentrations in percolation water. The effect declined with time, but the reduction in SS and TP was still >25% 4 yr after application. We attributed the lower tendency for particle detachment in rain simulations to direct interactions of soil minerals with the added particulate organic matter and microbe‐derived compounds that stabilize soil aggregates. In soils with low organic matter content, pulp and paper industry by‐products can be a viable measure for erosion mitigation.

Assessment of bioavailability and mobility of major and trace elements in agricultural soils collected in Port St Johns, Eastern Cape, South Africa using single extraction procedures and pseudo-total digestion.

The aim of this study was to evaluate the applicability of ultrasound assisted single extraction and pseudo-total digestion procedures to investigate the bioavailability and mobility of major and trace elements collected from agricultural soil collected in Mzimvubu farmstead area located in Port St Johns, Eastern Cape Province (South Africa). The potential metal availability was assessed using complexing agent (ethylenediaminetetraacetic acid (EDTA)), mild (cacium chloride (CaCl2) and ammonium nitrate (NH4NO3)), deionized water and acidic (CH3COOH) extractants with the assistance of ultrasound to evaluate mobility and bioavailability of metals. The ultrasound radiation was used to assist the single extraction of major and trace metals from agricultural soils as well shortening the extraction time. The pseudo-total metal content in agricultural soils was obtained using pseudo-total digestion employing aqua-regia. The results obtained using different solvents for single extraction procedures, revealed that higher extraction of Al (256-681mgkg-1), Fe (172-430mgkg-1) and Mn (35-136mgkg-1), was observed compared to other metals. Among the investigated solvents, deionized water, acetic acid and EDTA proved to be the most aggressive extractants. The geo-accumulation index (2-6) and contamination factor (3-6) demonstrated that Fe, Cr, Mn, Co, Cu, Ni, and Zn could pose significant environmental contamination risk. Based on the results obtained, it can be concluded that the high levels of some studied metals was due to anthropogenic activities. The online version contains supplementary material available at 10.1007/s40201-020-00581-x.