Soil Samples Research Articles

Isolation and characterization of two new species, Hymenobacter mellowenesis sp. nov. and Hymenobacter aranciens sp. nov., from soil.

Strains M29T and ASUV-10-1T, which are aerobic, non-flagellated, and Gram-stain-negative, were isolated from soil samples collected in Inje (37°57'49.1"N 128°19'53.7"E) and Cheonan City (36°48'47.1"N 127°05'22.4"E), South Korea. Phylogenetic analyses based on rRNA gene sequences revealed that strains M29T and ASUV-10-1T form a distinct branch within the family Hymenobacter (order Cytophagales, class Cytophagia). Strain M29T is most closely related to Hymenobacter rubidus DG7BT with a 16S rRNA gene sequence similarity of 97.05%. Strain ASUV-10-1T shows closest genetic similarity to Hymenobacter frigidus B1789T (96.42%), Hymenobacter jeongseonensis BT683T (95.97%), and Hymenobacter terricola 3F2TT (95.65%). The optimal growth conditions for these strains are pH 7.0, no NaCl, and a temperature of 25°C. The dominant cellular fatty acids identified in these strains are iso-C15:0, anteiso-C15:0, and Summed Feature 3 (C16:1ω 7c / C16:1ω 6c). Both strains predominantly contain MK-7 as the respiratory quinone. The major polar lipids in strains M29T and ASUV-10-1T are phosphatidylethanolamine, aminophospholipid, and aminolipid. Based on biochemical, chemotaxonomic, and phylogenetic data, it is evident that M29T and ASUV-10-1T represent new species within the genus Hymenobacter. The new species were classified based on biochemical and chemotaxonomic characteristics. The taxonomic classification of these species was conducted following the guidelines and protocols outlined in Bergey's Manual of Systematic Bacteriology. We followed the methods for determining physiological and biochemical characteristics, as well as chemotaxonomic markers such as fatty acid profiles, quinone types, and polar lipid compositions. We also compared with the results of carbohydrate utilization and enzyme activities results [Bergey 1994]. Therefore, we propose the names Hymenobacter mellowenesis for strain M29T (= KCTC 102056T = NBRC 116578T) and Hymenobacter aranciens for strain ASUV-10-1T (= KCTC 92969T = NBRC 116575T).

Use of Advanced Constitutive Models for the Mechanical Behavior of Soft Soils With Diatoms From Bogotá (Colombia)

ABSTRACTMost constitutive models did not initially consider special behaviors in some soils with singular characteristics (e.g., soft soils with diatom content). For example, at first, these models did not consider the effect of soil structure and viscosity. However, in the last decades, these variables have been incorporated into several constitutive models to describe the mechanical behavior of the soil in its natural state. Structure and viscosity laws that adequately reproduce the soil behavior had to be developed to include these variables. This paper compares the mechanical behavior of soft soils in Bogotá with different constitutive models. Bogotá’s soft soils are lacustrine deposits with a high content of diatoms in their structure. Natural soil samples with intact structures show a high‐water content, which can be higher than 300%, liquid limits of up to 400%, void ratios higher than five, and friction angles of almost 40°. In addition, the model validations were made through the simulations of triaxial tests in compression and shear paths. Modified Cam Clay (MCC), hypoplastic (HP), and subloading Cam Clay (SCC) were the constitutive models used. Two models are based on an elastoplastic framework, and the third uses a HP framework. Several lessons were learned from the simulations regarding the strengths and weaknesses of the models compared to the tests carried out. Finally, the extensive discussion revolves around determining the most suitable model for simulating the mechanical behavior of soft soils containing diatoms in Bogotá.

Chemical Composition of Clay Soil Analysis and Potential Health Risks: Experimental Study in Tshwane District, Gauteng Province

The practise of geophagy is common amongst women of childbearing age from different geographic locations, including South Africa, regardless of their social and economic status such as their level of education, race, marital status, income or occupation. This study aimed to examine the women of childbearing age in Tshwane District, Gauteng Province, South Africa. An experimental study was conducted at the laboratory to examine the chemical composition of clay soil ingested by geophagic women of childbearing age. Thirty-nine clay soil samples were collected from study participants attending antenatal care services and family planning at public healthcare facilities of Tshwane District, Gauteng Province, and subjected to geochemical analysis. The concentrations of vanadium, manganese, chromium, and barium were detected in quantities exceeding 100 mg/kg in almost all samples. Cadmium, mercury and silver were detected in low concentrations below 1 mg/kg in all samples. The practice of geophagy amongst women of childbearing age has been reported to be associated with detrimental health outcomes and risks such as iron deficiency anaemia, constipation, shortness of breath, maternal and childhood mortalities and morbidities, neurological and central nervous system disorder, death, appendicitis, cancers, teratogenic risks, and ulcers. The chemical composition of clay soil eaten by geophagic women of childbearing age contains potentially harmful substances, thus the practise of geophagy is toxic and should be discouraged to protect public health.

Does the Reclamation Period Affect the Variation of Soil Nutrients Across Different Vegetation Types in a Reclaimed Opencast Coal Mine Dump? Validated Through Three Soil Sampling Replicates

Does the Reclamation Period Affect the Variation of Soil Nutrients Across Different Vegetation Types in a Reclaimed Opencast Coal Mine Dump? Validated Through Three Soil Sampling Replicates

Biochar affects organic carbon composition and stability in highly acidic tea plantation soil

Biochar amendments are effective in stabilizing soil aggregates and improving soil organic carbon (SOC) content. However, the effects of biochar on highly acidic soil and their relation with soil SOC stability remain understudied. The study aimed to investigate the impact of biochar on changes of aggregate distribution and SOC stability in a highly acidic tea plantation soils over an eight-year period. Soil samples were collected from plots with varying biochar application amounts (0, 2.5 t ha−1, 5 t ha−1, 10 t ha−1, 20 t ha−1 and 40 t ha−1). The content of SOC, iron bound organic carbon (OC-Fe), particulate organic carbon (POC), mineral-associated organic carbon (MAOC) and the functional group composition of SOC was analyzed. The results indicated that in the biochar application treatments, the value of soil pH, SOC, POC and MAOC contents were increased from 3.92 to 4.28, 6.68%–187.02%, 8.31%–66.78% and 13.07%–236.47% respectively, compared with CK, while the content of macro-aggregate (particle size>0.25 mm) and soil aggregates mean weight diameter (MWD) significantly increased with higher biochar application amounts. But dissolved organic carbon (DOC) and OC-Fe content exhibited downward trend, decreased from 2.43% to 6.97% and 4.18%–19.91%. Furthermore, aromatic-C levels increased, with increased biochar application amounts. The integration of biochar not only bolstered soil aggregate stability but also amplified the presence of aromatic-C, thereby enhancing the resilience of organic carbon in highly acidic tea garden soil (BC40 > BC20 > BC5>BC2.5 > BC10 > CK), with increases ranging from 6% to 47%. The principal component analysis and structural equation modeling identified soil pH, TN, SOC, POC, MAOC, R > 0.25 and MWD as key factors of soil organic carbon stability. These findings provide crucial insights into the mechanism underlying biochar's efficiency in fortifying organic carbon stability, particularly in the context of highly acidic soil.

Potentially Toxic Metals Enrichment in Soils of Ishiagu Mining Community, Southeastern Nigeria

This Study was carried out to evaluate potentially toxic metals enrichment, pollution and potential ecological risk in the soils of Ishiagu. The concentrations of Cadmium (Cd), Chromium (Cr), Cobalt (Co), Copper (Cu), Lead (Pb), Manganese (Mn), Nickel (Ni), Zinc (Zn), Aluminum (Al) and Iron (Fe) in soil samples from the area were analyzed by Bureau Veritas Laboratory, Vancouver, Canada, using inductively-coupled plasma optic emission spectrometry (ICP-OES). Descriptive statistics, enrichment factor, pollution load and potential ecological risk indices were employed to analyze the data in order to understand the characteristics of potentially toxic metals in the study area. The potentially toxic metals statistic show the mean values (mg/kg-1 ) of Pb, Zn, Mn, Fe, Al, Cd, Cr, Ni, Co, and Cu to be 205.7, 162, 527, 35892, 11374, 1.3, 21.6, 15, 14.6 and 11.1 respectively. The soil enrichment varied considerably between mining and non-mining areas with mining area being extremely enriched with Pb, Zn and Cd, and significantly enriched with Co, Cu, Ni and Fe. Non- mining areas are minimally enriched with all investigated metals. The soils around the mines are polluted with Pb and Cd, where both metals also pose very high ecological risks.

Pore Structures in Detritusphere of Soils Under Switchgrass and Restored Prairie Vegetation Community

ABSTRACTRoot detritusphere, that is, the soil in the vicinity of decomposing root residues, plays an important role in soil microbial activity and C sequestration. Pore structure (size distributions and connectivity of soil pores) in the detritusphere serves as a major driver for these processes and, in turn, is influenced by the physical characteristics of both soil and roots. This study compared pore structure characteristics in the root detritusphere of soils of contrasting texture and mineralogy subjected to > 6 years of contrasting vegetation: monoculture switchgrass and polyculture prairie systems. Soil samples were collected from five experimental sites in the US Midwest representing three soil types. Soil texture and mineralogy were measured using a hydrometer and x‐ray powder diffraction, respectively. The intact cores were scanned with x‐ray computed micro‐tomography to identify visible soil pores, biopores, and particulate organic matter (POM). We specifically focused on pore structure within the detritusphere around the POM of root origin. Results showed that the detritusphere of coarser textured soils, characterized by high sand and quartz contents, had lower porosity in the vicinity of POM compared with finer textured soils. POM vicinities in finer textured soils had high proportions of large (> 300 μm diameter) pores, and their pores were better connected than in the coarser soils. Lower porosity in the outer (> 1 mm) parts of the detritusphere of switchgrass than of prairie suggested soil compaction by roots, with the effect especially pronounced in the coarser soils. The results demonstrated that soil texture and mineralogy played a major, while vegetation played a more modest, role in defining the pore structure in the root detritusphere.

Радиоэкологические исследования в районе архипелага Земля Франца-Иосифа в августе и сентябре 2023 года

The results of a study of the current activity of technogenic isotopes in the coastal zone of the Alexandra Land island of the Franz Josef Land archipelago are presented. Samples of sea water, algae, bottom sediments, soil and vegetation were taken during an expedition carried out under the auspices of the Northern Fleet and the Russian Geographical Society in August and September 2023. In the marine environment and littoral macrophytes, the content of technogenic 137Cs is gradually decreasing in comparison with the indicators of the previous period 2000–2010. In the terrestrial ecosystem, the distribution 137Cs is mosaic; the highest specific activity is found in soils (up to 71.4 Bq/kg). In single samples, the presence of the short-lived isotope 134Cs was noted, which is an indicator of relatively recent atmospheric fallout in the Arctic.

Contaminants in the Soil and Typical Crops of the Pannonian Region of Slovenia

Soil contamination and the uptake of pollutants by food crops are widespread issues that vary greatly by region and are influenced by the mineral composition of the soil and local human activities. The Pannonian region, where agriculture has played a key role since Roman times, has been particularly impacted by the long-standing agricultural and industrial practices. While soil contamination with heavy metals is monitored by the Slovenian government, microplastic contamination and the uptake of pollutants into food crops have yet to become a regular component of monitoring efforts. In this study, we conducted a preliminary investigation into soil and crop contamination across the Pannonian region, focusing on identifying harmful contaminants and their potential uptake into food crops. Both soil and crop samples were analyzed for the presence of heavy metals with proven methods such as atomic absorption spectrometry (FASS), graphite furnace atomic absorption spectrometry (GF-AAS), atomic fluorescence spectrometry (AFS), and inductively coupled plasma–mass spectrometry (ICP-MS). Energy-dispersive X-ray spectroscopy (EDS) was found to be a potentially faster method of obtaining data on soil composition. Special attention was also given to the potential presence of microplastics in the region’s soils.

From aquatic to terrestrial: An examination of plant diversity and ecological shifts

Abstract Our study focuses on plant diversity in the Allal El Fassi dam, a semi-arid continental bioclimate, to understand human-impacted aquatic ecosystems. We analyzed plant, soil, and water samples from 40 stations using various indices. We identified 55 plant species across 35 families, with Poaceae, Asteraceae, Asparagaceae, and Rosaceae being dominant. The transition zone (formerly Zone 2) is characterized by dense vegetation of hydrophytes, hemicryptophytes, and therophytes. The transformed (formerly Zone 1) and terrestrial zones (formerly Zone 3) have less diverse vegetation, dominated by phanerophytes, geophytes, and chamerophites. Phanerophytes, due to their developed root systems, are suited to dam soil types. Predominant species like Tamarix gallica L., Nerium oleander L., Juncus acutus L., and Arundo donax L. indicate the dam’s ecological transformation into a terrestrial ecosystem isolated from the river by sedimentary deposits following floods. These species are opportunistic, and adapted to water level variations.

Spatial Heterogeneity of Soil Nutrient in Principal Paddy and Cereal Production Landscapes of Fengtai County within the Huai River Basin, Eastern China

The problem of cultivated land soil quality in the Huaihe River Basin has become increasingly prominent. How to accurately and quantitatively evaluate the soil quality of regional cultivated land and realize its efficient use has become an urgent problem. In order to explore the spatial autocorrelation and variation in soil nutrients in cultivated land in the plain of Fengtai County in the Huaihe River Basin, a total of 306 soil samples and mature wheat samples were collected in the study area to analyze soil pH, total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), available potassium (AK) and slow-release potassium (SK) content and wheat biomass, and combined with geostatistical methods and GIS technology. The Kriging interpolation method and Moram‘s I index method were systematically analyzed. Principal component analysis (PCA) and Pearson correlation analysis were used to establish the minimum data set (MDS) of soil quality, which was used to calculate the soil quality index (SQI) and determine the key factors affecting soil quality. The results showed that the soil pH was in weak variation, and the other nutrient indexes were in medium variation. The spatial variability of soil-available potassium nutrients was affected by random factors such as human activities and structural factors such as soil parent materials. The spatial autocorrelation of organic matter, total nitrogen, alkali-hydrolyzable nitrogen, available phosphorus, available potassium and mitigation potassium was weak, which was mainly affected by random factors such as human activities. An unequivocal positive spatial nexus was discerned across all nutrients. Cumulatively, the nutrient dispersion across the investigated territory was somewhat diffuse, manifesting in a mosaic pattern with pronounced zonal nutrient allocation disparities in the meridional, median, and septentrional segments. An explicit latitudinal dichotomy delineating zones of nutrient opulence and paucity was also observed. These insights can pave the way for tailored fertilization strategies and judicious pedological stewardship in Fengtai County.

Ecological risk assessment of heavy metals contaminated mining sites of eastern india using soil and moss.

The blooming industrialization and urbanization is leading to increased mining operations. These intensified mining activities emit heavy metals into the environment, posing serious threats to ecosystems. Hence, this study focused on assessing heavy metal pollution in mining soil, utilizing mosses as bioindicators. The ecological risk, geo-accumulation factor, and contamination factor have been calculated to know the harmful effect of heavy metals on ecosystem. The study covered three distinct mining sites of eastern India within Odisha: Jajpur's Sukinda Valley (SP1, Cr), Keonjhar's Joda-Barbil (SP2, Fe and Mn), and Sundargarh's Koira-Joda (SP3, Fe). The collection of 48 soil samples through random sampling revealed significant variations in heavy metal concentrations. SP1 recorded Cr concentration of 6572 ± 445mg/kg and Ni of 8042.47 ± 501.38mg/kg, surpassing eco-toxicological levels. The storage site in SP2 exhibited the highest Fe concentration at 9872 ± 502mg/kg, and Mn levels in SP3 were at 7884 ± 432mg/kg. Storage areas in all three regions held the highest concentrations of heavy metals. Mosses in studied area demonstrated as potential bioindicators for monitoring heavy metal pollution. EF and Igeo assessments showed Cd, Pb, Hg, and other heavy metal contamination compared to earlier investigations. This study indicated higher ecological risks for Pb, As, Cu, Ni, and Zn. The Hyophila involuta accumulates Mn, Cr, Cd, Pb, Fe, and Hg, while Barbula arcuata accumulates Mn, As, and Cu in SP1. Hyophila involuta and Trematodon longicollis accumulate Mn, Cr, Cd, Pb, Fe, Hg, and Zn in SP2. Trematodon ambiguous accumulates Cd, Fe, and Ni, while Fissidens diversifolius accumulates Mn, Cr, Hg, As, Cu, and Zn in SP3. These findings emphasize the necessity of monitoring heavy metal pollution in contaminated zones using moss as a potential bioindicator.

Utilizing a medicinal plant and soil assays for heavy metal pollution assessment and its impacts in a Turkish Industrial Zone

Due to the worldwide growth in population, agricultural and industrial activities are expanding quickly, which pollutes the air, water, and soil and leads to the buildup of potentially hazardous substances in medicinal plants. The current study sought to determine the concentrations of various metals in Silybum marianum plants and soils in order to highlight the level of pollution in a Turkish Organized Industrial Zone in Dilovasi District, Kocaeli, and to investigate the effects of these heavy metals on plants. In order to determine the concentrations of elements evaluated within the scope of this study inductively coupled plasma optical emission spectroscopy was employed, due to the benefits of ICP that provides few or no organic molecules, few ionization interferences, as well as the ability to analyze many elements sequentially. Furthermore, in order to evaluate elemental analysis in terms of nutritional values, risk assessments using RDA, EDI, THQ, and HI parameters were conducted. The value of heavy metals in co-located soil samples is relatively high. However, except for Co, Mn, and Ni, it has stayed within the World Health Organization’s permitted limits. The evaluation of the co-located soil samples found that the highest contents (mg kg−1) of Al, Ca, Cd, Cr, Cu, Fe, K, Mn, Na, Ni, Pb, and Zn, were recorded as 7825.10, 4365.86, 4768.59, 2.50, 30.45, 38.49, 8352.00, 17452.26, 1495.82, 1495.82, 163.53, 1452.23, 28.67, 136.55 and 125.45, respectively, belonging to Location 1. These findings are in accordance with the Industrial Status Report since the place specified as Location 1 in the current study is characterized by its pronounced industrial activity and the robust electrical plant station with an industrial facility for generating electric power. Furthermore, the hazard index, the estimated daily intake and target hazard quotient for potentially harmful components and recommended daily allowance values for mineral nutrients were computed. Therefore, even though mineral nutritional values in some areas were found to be higher than Buyukada control location, this should be ignored. Consequently, this study warns against using S. marianum plants as food or medicine collected from current regions. As a result, ongoing inspection is necessary to prevent an excessive buildup of metals in the area and other places with similar human life-related features.

Soil erodibility mapping using remote sensing and in situ soil data with random forest model in a mountainous catchment of Indian Himalayas.

Land degradation is accelerating in the Himalayan ecosystem, resulting in the loss of soil nutrients due to severe erosion. Soil erosion presents a significant environmental challenge, resulting in both on-site and off-site consequences, such as reduced soil productivity and siltation in reservoirs. Soil erodibility (K factor), an inherent soil property, determines the susceptibility of soils to erosion. Sampling across hilly and mountainous terrain pose challenges due to its complex landscape. Despite these challenges, it is essential to study K factor variations in different land use/land cover types to comprehend the threat of erosion. Digital soil mapping offers an opportunity to overcome this limitation by providing spatial predictions of soil properties. The objective of our study is to map the spatial distribution of soil erodibility using the Random Forest (RF) model, a machine learning method based on sampled in situ soil data and environmental covariates. We collected 556 surface soil samples from the mountainous catchment (Tehri dam catchment) using the stratified random sampling approach. The model performed satisfactorily in both training (r2 = 0.91; RMSE = 0.00185) and testing (r2 = 0.45; RMSE = 0.00318) phases. Subsequently, we generated a digital map with a resolution of 12.5m to depict the distribution of the K factor. Our analysis revealed that key environmental variables influencing the prediction of the K factor included geology, mean NDVI, and climatic factors. The average K factor value was estimated at 0.0304 and ranging from 0.0251 to 0.0400 t ha h ha-1MJ-1mm-1. A higher K factor was observed in the barren land (0.0344) primarily located in the higher and trans-Himalayan region of seasonally snow-covered areas. These areas typically feature young soils with weak soil formation and unstable soil aggregates. Subsequently cropland/cultivated soils (0.0307) exhibited higher K factor values due to the breakdown of soil aggregates by ploughing activities and exposing carbon to decomposition. The average K factor value of evergreen (0.0294) and deciduous (0.0295) forests were the lowest compared to other land use/land cover types indicating the role of forests in resisting soil erosion. By assessing and predicting soil erodibility, land planners and farmers can implement erosion control measures to protect soil health, prevent sedimentation in water bodies, and sustain agricultural productivity in the Himalayas.

Assessment of Constraints and Suggestion Insights from Beneficiaries of Centrally Sponsored Agricultural Schemes: A study of PKVY, PMKSY and SHC in Vidarbha Region of Maharashtra, India

The present study focused on assessing the constraints faced by the beneficiaries of centrally sponsored agricultural schemes namely Paramparagat Krishi Vikas Yojana (PKVY), Pradhan Mantri Krishi Sinchayee Yojana (PMKSY), and the Soil Health Card Scheme (SHC) and invited suggestions from them to overcome the constraints. For the proposed study, 60 beneficiary farmers were selected from Amravati districts and 60 beneficiary farmers were selected from Buldhana districts in Vidarbha region of Maharashtra for each scheme. Thus, for the three schemes, a total of 360 beneficiary farmers were selected. In the case of PKVY beneficiaries, the major constraints faced were lack of proper marketing channel for organic produce, lack of sustainability in the reduction of cost of organic cultivation and reduced productivity of organic farm produce even after conversion period. Whereas, in the case of constraint faced by PMKSY beneficiaries, the first constraint faced by the beneficiary was longer time for getting the subsidy credited, followed by lack of increase in the sources of irrigation and load shedding of electricity. In the case SHC beneficiaries, the major constraint faced were long time gap between soil sample collection and issuing SHC, difficulty to comprehend the information and follow the recommendations provided in SHC and lack of effective training and demonstrations provided to farmers about soil health. In the case of PKVY beneficiaries, majority of them (74.17%) gave the suggestion for establishment of proper marketing channel for organic produce, followed by 34.17 per cent of them suggested the strengthening of farmer groups and developing them into Farmer Producer Organizations (FPOs). Whereas in the case of PMKSY beneficiaries, 84.17 per cent of them suggested to ensure timely crediting of subsidies, followed by expansion of irrigation infrastructure through the construction of water harvesting structures such as check dams, farm ponds, tanks and bore wells (59.16%). In the case of SHC beneficiaries, majority of them (85.83%) gave the suggestion to speed up the process of issuing Soil Health Cards and 71.66 per cent suggested for training programs and field level demonstrations focused on soil health and the practical application of SHC recommendations to improve farmers' knowledge and skills.

A multi-pathogen behavioral exposure model for young children playing in public spaces in developing communities.

Diarrheal disease is the second leading cause of death among children under five in developing communities, despite active interventions to improve access to water, sanitation, and hygiene resources. Even interventions with high fidelity and compliance saw minimal improvements in health outcomes, necessitating a need for looking beyond traditionally targeted exposure pathways. This study focuses on the pathogen exposure a young child may receive while playing in the public spaces of informal settlements, where animal feces, human feces, and garbage are frequently observed. The study utilized 79 soil samples previously collected across ten cluster sites in Corail, Haiti and processed using DelAgua cultural assays and quantitative Polymerase Chain Reaction methods. Molecular assays screened for Aeromonas, Vibrio cholera, and several pathogenic Escherichia coli species. Behavioral observations of young children (<5 years old) were also conducted in overlapping areas with the environmental sampling to quantify frequency of risky and mitigating behaviors. Environmental and behavioral data were combined to obtain the posterior distribution of children's pathogen exposure from playing in a public space for one hour. The model estimated that children have a likelihood of approximately 70% of being exposed to a pathogen during one hour of play and a greater than 30% chance of being exposed to multiple pathogens in the same period. While children and toddlers practice fewer risky behaviors compared to infants, they were shown to have higher likelihood of exposure and slightly higher pathogen dose per exposure. As anticipated, a high correlation between genes from the same E. coli species was observed in the model output. These findings demonstrate the need to consider public spaces as an important exposure pathway for young children for both future research and interventions.

Machine learning-assisted risk evaluation of heavy metals in the Hainan gold mining region, China.

This study employed machine learning (ML) to thoroughly investigate the impact of informal mining activities on the distribution and pollution status of heavy metals in soils near private gold mines in Hainan Province, southern China, a region known for its ecological sensitivity and economic importance. By systematically collecting surface soil samples and samples at depths of 0.5-1m from 175 drilling sites, a comprehensive quantitative analysis was conducted on major heavy metal elements, including lead (Pb), copper (Cu), cadmium (Cd), nickel (Ni), mercury (Hg), chromium (Cr), arsenic (As), and zinc (Zn). Combined with evaluation methods such as the Pollution Load Index (PLI), Normalized Pollution Index (NIPI), and Ecological Risk Index (ERI), the study revealed a high level of soil pollution at informal mining sites. The findings indicated that the average concentrations of Pb, Cd, Hg, As, and Zn in surface soils significantly exceeded the background values for soils in China, with a pronounced positive correlation observed between these heavy metal elements in both surface and deep soil profiles (r > 0.5). Furthermore, leveraging the heavy metal content in surface soils and the constructed environmental indicators, the predictive accuracy for metal content in deep soils was found to range from R2 = 0.27 to 0.68, suggesting that informal mining activities have led to substantial variations in metal content across different soil profiles. Through the application of a random forest model for predictive analysis of the PLI, NIPI, and ERI, high prediction accuracy was achieved (R2 = 0.78, 0.86, and 0.60, respectively). The study demonstrates that informal mining activities not only elevate the risk of soil pollution but also alter the distribution patterns of heavy metals. Also, this study provides a crucial foundation for the scientific assessment of soil quality and potential environmental hazards, while also affirming the efficacy of ML techniques in forecasting soil quality parameters.

An IoT-Enabled Real-Time Crop Prediction System Using Soil Fertility Analysis

Changes in soil fertility have led to a decline in crop production, making it challenging for farmers to select the best crops based on soil conditions. Accurate crop prediction can significantly enhance crop productivity, and machine learning plays a crucial role in this process. Crop forecasting is influenced by soil, geographic, and environmental characteristics, with feature selection being essential for identifying suitable crops. In this study, we developed a real-time soil fertility analyzer to obtain the real-time values of soil parameters such as potassium, phosphorus, nitrogen content, temperature, pH, moisture content, and electrical conductivity. The crops examined were coconut, ginger, plantain, and tapioca. The data collected from this analysis served as the dataset for different training and testing classification algorithms for crop prediction using 100 soil samples. Among the algorithms tested, the k-nearest neighbors (KNN) algorithm demonstrated the highest performance, with an accuracy of 84%, precision of 85%, recall of 88.8%, and specificity of 92.4%. These results indicate that machine learning, combined with real-time soil analysis, can effectively predict suitable crops, enhancing crop productivity and aiding farmers in making informed decisions. This approach can revolutionize traditional farming practices by providing precise, data-driven insights into crop selection, ultimately improving agricultural efficiency and sustainability.

Changes in the Phylogenetic Structure of Alpine Grassland Plant Communities on the Qinghai–Tibetan Plateau with Long-Term Nitrogen Deposition

Nitrogen (N) deposition rates have notably increased around the world, especially in high-altitude regions like the Qinghai–Tibetan Plateau (QTP). We conducted a six-year comprehensive experiment to simulate nitrogen deposition in an alpine grassland area near Qinghai Lake. Four levels of nitrogen depositions, i.e., 0 (CK), 8 kg N ha−1year−1 (N1), 40 kg N ha−1year−1 (N2), and 72 kg N ha−1year−1 (N3), with three replicates for each N treatment, were tested annually in early May and early July, with the meticulous collection of plant and soil samples during the peak growth period from 15 July to 15 August. We used the null model to evaluate the impact of environmental filtration and interspecific competition on the dynamics of the plant community was assessed based on the level of discrete species affinities within the plant community by constructing a phylogenetic tree. The results showed that the environmental filter was the predominant driver for the change of community’s genealogical fabric. The N2 and N3 treatments increased the influence of soil factors on the change of plant community structure. Climatic factors played a crucial role on the change of plant community in the CK grassland area, while soil factors were dominant in the N1- and N3-treated grasslands.

Soil degradation around Orji municipal solid waste dump site: a spatial assessment.

The present study assessed the impact of municipal solid waste dump on the degradation of soil around Orji dump site. A total of 15 soil samples were collected for this study. Twelve soil samples were collected around the dump site at 0m, 10m, and 20m distance and three from Imo State University (IMSU) research farm as control. The samples were collected from the east, west, north, and south of the dump site. The samples were subjected to laboratory analyses. The mean results obtained indicate that the values of the dump site soil parameters analyzed ranged from 86.67 to 89.00% (sand), 4.33 to 5.67% (silt), 7.00 to 7.67% (clay), 6.80 to 7.50 (pH), 4.33 to 7.00 dS m-1 electric conductivity (EC), 0.0028 to 0.0045mgkg-1 (salinity), 2.36 to 3.76% soil organic matter (SOM), 24.13 to 38.93 cmolc kg-1 cation exchange capacity (CEC), 4.50 to 9.57 cmolc kg-1 calcium (Ca), and 1.0 to 2.25 cmolc kg-1 magnesium (Mg). At the control, mean values were 81.24% (sand), 6.39% (silt), 12.45% (clay), 5.69 (pH), 0.47 dS m-1 (EC), 0.0005mgkg-1 (salinity), 1.99% (SOM), 5.08 cmolc kg-1 (CEC), 2.17 cmolc kg-1 (Ca), and 1.67 cmolc kg-1 (Mg). These values showed substantial enrichment. Correlations indicate that EC, salinity, and CEC majorly determined the availability of most of the parameters analyzed. Soil degradation index (SDI) was used to determine degradation around the dump site. It ranged from 2.546.61% (0m) to 1573.50% (10m) and 1.603.73% (20m). Thus, distance affected the rate of soil degradation in all directions away from the dump site.