Soil pH Values Research Articles

Continuous planting American ginseng (Panax quinquefolius L.) caused soil acidification and bacterial and fungal communities’ changes

Abstract Background American ginseng is an important herb crop and is widely cultivated in China. However, continuous cropping seriously affects the production of American ginseng, and the reason is still unclear and needs more research. We analyzed the soil microbial alpha diversity and community composition as well as soil physicochemical properties in bulk soils to assess the changes in soil associated with planting American ginseng. Results The cultivation of American ginseng resulted in a significant decrease in soil pH value. The alpha diversity of soil bacteria and fungi was significantly reduced with the increase of American ginseng planting years. Planting American ginseng also largely altered the community composition of soil bacteria and fungi, in particularly, increased the relative abundance of the pathogenic fungus Fusarium, and reduced the relative abundance of some beneficial microorganisms, such as KD4-96, RB41 and Sphingomonas. Conclusions Soil acidification, reduction of beneficial taxa and accumulation of fungal pathogens, therefore, may lead to the replantation problem of American ginseng.

Resource allocation design method based on WSN multi-dimension soil inspection

Abstract. With the industrialization of agriculture and the sharp rise of food prices, in order to promote the intensive development of natural resources and achieve economies of scale agriculture in production, people put forward the innovative strategy of "precision agriculture" to maintain the sustainable development of agriculture. To protect the environment and farmer communities and increase productivity. However, in the special context of precision agriculture, the problems related to energy consumption and electromagnetic wave propagation in complex environments have a significant impact on precision agriculture. In the case of no monitoring and harsh environment, wireless sensor networks (WSN) can complete the tasks of real-time monitoring and information collection. In the past, the understanding of WSN in agriculture was limited to unilateral detection, which led to the underutilization of the soil. This paper introduces an innovative solution for precision agriculture based on wireless sensor networks, which mainly focuses on the observation and impact assessment of soil water volume,PH value, temperature and pressure in agricultural production process. It aims to reduce the waste of natural resources and the use of fertilizer substances, while maintaining or improving the yield of farming, in order to better promote the development of WSN in the agricultural field.

Soil Acidification and Its Temporal Changes in Tea Plantations of Guizhou Province, Southwest China

ABSTRACTSoil acidification is a significant problem in intensive agricultural systems, particularly in tea plantations. Guizhou province, located in the center of the karst mountainous region of southwest China, has the largest tea plantation area in China. However, the soil acidification characteristics in the tea plantations of Guizhou province, as well as their temporal changes, have not yet been adequately studied. Therefore, soil acidification and associated soil properties in the major tea‐planting counties of Guizhou province were extensively assessed, and the temporal changes in soil acidity over the past 11 years were also evaluated through long‐term and short‐term experiments. The results showed that the average soil pH in the tea plantations in Guizhou province varied from 4.08 to 4.87, with a mean of 4.47. The average cation exchange capacity (CEC), TEA (total exchangeable acidity, TEA), EH (exchangeable H+), and EA (exchangeable Al3+) values were 9.6, 3.7, 5.8, and 19.0 cmol/kg, respectively. Seasonal changes in tea plantation soil pH were observed in low‐ and moderately acidic soils but not in highly acidic soils. The soil pH values did not significantly change during three consecutive years of in situ observations but significantly decreased over the past 11 years at an average of 0.03 yearly. Correlation analysis revealed that the soil pH in tea plantations was significantly positively correlated with the content of specific amino acids, such as glutamic acid, arginine, and valine, but was significantly negatively correlated with certain soil physicochemical properties. The findings of this study indicate that soil acidification in tea plantations of the Guizhou province is severe and possesses distinctive attributes that should be considered for its effective management.

Persistent Organic Pollutants (POPs) in farmland soils of Kumo Akko Local Government Area, Gombe State, Nigeria

This work investigated the Prevalence and Impact of Persistent Organic Pollutants (POPs) In Farmland Soil within the Vicinity of Kumo, Gombe State, Nigeria. by employing a combination of field sampling and laboratory analysis. The research aimed to analyze the present of the concentrations of POPs in farmland soils using GC-MS. Samples were collected from three different locations and analyzed, their content of POPs per sample area determined the major components present. The results obtained indicated the POPs components of each soil sample. The research revealed that eight components of POPs such as naphthalene with a retention time of 5.02 minutes amounting to a highest composition of 0.004141 ppm followed by acenaphthene with a retention time of 8.82 minutes which showed 0.00395 ppm. Moreover, phenanthrene showed the least concentration of 0.000139 ppm with a retention time of 12.5 minutes. The physical parameters of the farmland soil revealed the mean pH values of sample soil investigated with S3 having the highest value of 6.01 followed by S1 with pH value of 5.95, while S2 showed the lowest pH value of 5.20. This showed that the acidity value increase in the order of S2=5.20 < S1=5.95<S3=6.01 respectively.

Biodegradation potentials of soil-borne fungal cultures grown on haloxyfop R methyl ester herbicide medium

The heterotrophic and haloxyfop-R methyl ester utilizing fungal counts associated with two top soil samples was determined. Five (5) fungal isolates; Aspergillus niger, Candida sp., Trichoderma sp., Fusarium sp., and Alternaria sp. Were cultured from the soil samples using serial dilution as well as pour plate techniques. These isolates were sub-cultured and screened for their ability to use haloxyfop-R methyl ester as sole source of metabolic energy as well as using the turbidimeteric method. Two of the screened fungal isolates which exhibited maximal optical density (OD) difference values; A. niger and Fusarium sp. Were selected and utilized for the subsequent degradation/shake flask experiment. Growth profile parameters which included; pH, OD, dissolved CO2 and weighed dry fungal biomass were determined during the growth profiling test at a 96 hour interval for 16 days using appropriate methods and equipment. Mean soil pH values were 5.08 ± 0.02 and 4.62 ± 0.02 for samples A and B. The mean total heterotrophic fungal count was 8.7×10³ cfu/g ± 1.5 for A and 1.6 × 10⁴ cfu/g ±1.0 for B. The mean pH value observed for A. niger in the course of the growth profile test ranged from 6.0 ± 8.7 to 7.3 ± 8.0 and 7.3 ± 5.8. The mean OD values observed for A. niger and Fusarium sp. In the course of the shake flask experiment varied from 0.66 ± 7.1 to 1.96 ± 4.5 and 1.62 ± 5.4 to1.99 ± 3.6 respectively. With reference to the detection of mean dissolved CO2 values, utilized as an indirect indicator of herbicide mineralization, the axenic cultured A. niger was the most effective amongst the growth profile fungal cultures.

Characteristics of organic carbon in tobacco-growing soils with different pH

This paper deal with the analysis of the relationship between acidity and alkalinity with organic carbon structure and humus components of tobacco-growing soils in Tengchong city. Under the same level of organic matter and nutrient content, soils with different pH values in Tengchong city were selected for the investigation. Results showed that the HA/FA values of the soil with low organic matter content gradually decreased with increasing pH, indicating a higher content of active carbon components and a lower content of stable carbon components in the soils. In soils with high organic matter content, pH value showed a highly significant negative correlation with HA/FA and PQ values. With increasing acidity, HA/FA became higher, and humus components with high stability increased. At the same level of organic matter content, the infrared A2920/A1630 ratio gradually increased with increasing pH. It indicates that at a certain pH range and the same level of organic matter content, the stable humus component increases, and the soil pH value decreases. Bangladesh J. Bot. 53(3): 745-755, 2024 (September) Special

Physico-chemical characteristics and quality assessment of soil in parts of the Banganga Basin in northeastern Rajasthan, NW India.

Soil is a vital natural resource that has a bearing on any developmental activity. A database comprising primary physicochemical characteristics and soil suitability would assist the planners in devising an appropriate land use policy and any intervention strategy for soil quality improvement. The physicochemical characteristics of soils in parts of the Banganga Basin, located in the semi-arid terrain of NW India were evaluated mainly through surface samples and sub-surface ones wherever sections were exposed in stream banks. The soil in the studied terrain is a Quaternary age, pale brown to dark brown and occasionally red, alluvial soil. Sandy loam is the dominant soil type, while sandy soil and loamy sand types also occur. The soil maintains a depth-wise consistency in physicochemical characteristics. The average soil pH value is 8.55, indicating a slightly alkaline and healthy soil. The soil has a high available nitrogen content (0.53 to 2.24%), adequate available phosphorus (23.58 and 62.18mg/kg), and low potassium (22.5 and 200mg/kg) contents. The organic carbon, Mg, and Ca levels are generally on the lower side. A consistency in overall soil characteristics is evident in the narrow range of the Soil Quality Index, varying between 10 and 14, and soil can be categorized into three categories with overlapping soil qualities.

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.

Effects of Vegetable Planting Ages on Community Structure of Ammonia-oxidizing Archaea and Ammonia-oxidizing Bacteria in Greenhouse Vegetable Fields

The ammonia oxidation process driven by microorganisms is a dominant source for nitrous oxide （N2O） emissions. Here, we examined the influence of greenhouse vegetable planting ages on soil ammonia-oxidizing archaea （AOA） and ammonia-oxidizing bacteria （AOB）, which is of great significance for assessing the soil quality status and greenhouse gas transformations. A field study was conducted at different times （1, 5, 10, and 20 a） in greenhouse vegetable soils of Gaoyi, Hebei Province. Chemical analysis and Illumina NovaSeq high-throughput sequencing were used to analyze the soil physicochemical properties and community structures and diversity of AOA and AOB. The variation in AOA and AOB communities and the driving factors in greenhouse soils at different ages were also investigated. The results showed that the contents of total nitrogen, organic matter, alkali-hydrolyzable nitrogen, available phosphorus, and available potassium first increased and then decreased with the prolongation of growth. The contents of nitrate nitrogen, ammonium nitrogen, and electrical conductivity first decreased and then increased with the prolongation of growth. The pH value of soils decreased with the prolongation of growth. The abundance and diversity index of AOA and AOB first decreased and then increased with the prolongation of growth. Nitrososphaeria, unclassified Thaumarchaeota, and Candidatus Nitrosocaldus were the dominant species of AOA, while Betaproteobacteria and Nitrosospira were the dominant species of AOB. The composition of the soil AOA community varied greatly compared to that of AOB with the prolongation of growth. Correlation analysis showed that the changes in soil nutrient factors had a significant correlation with AOA and AOB communities. Redundancy analysis indicated that ammonium nitrogen, alkali-hydrolyzable nitrogen, and nitrate nitrogen were key factors of AOA communities, while electrical conductivity, available potassium, and nitrate nitrogen were key factors for AOB. In summary, long-term planting of greenhouse vegetables significantly affected the abundance and composition of soil AOA and AOB communities. Our results provide a theoretical basis for further studies on the greenhouse gas transformation and microbial mechanisms of the nitrogen cycle in greenhouse soils.

Effects of decomposed and undecomposed straw of three crops on clubroot disease of Chinese cabbage and soil nutrients

Aims: Straw turnover plays an important role in reducing soil diseases, improving the ecological environment of plowland and realizing the effective ecological utilization of straw. Methods: Pot and field experiments were carried out to investigate the effects of maize, rice and wheat straws on the growth, clubroot disease of Chinese cabbage and soil nutrients. Undecomposed and decomposed maize, rice and wheat straws were quantitatively added to the monocultural soil of Chinese cabbage, and the crops without straw were taken as the control. Results: The results showed that the addition of maize, wheat and rice straws could promote the growth of monocultural Chinese cabbage, inhibit the occurrence of clubroot disease, increase soil pH value, the content of soil organic matter, alkaline hydrolyzable nitrogen and available potassium in pot experiment. Exogenous straw application could reduce the incidence rate by 22.54 ~ 47.85%, increase the plot yield of field 95.15 ~ 365.81%. Conclusions: In terms of inhibiting clubroot disease and improving soil properties, undecomposed rice straw is superior to maize and wheat straw, while decomposed maize straw is superior to rice and wheat straw.

Coupled reduction in arsenic methylation and methanogenesis with silicate amendment in arsenic-enriched paddy soils

Methanogens play an important role in the demethylation of arsenic. Soil amendments that inhibit methanogens can increase dimethylarsinic acid (DMA), which is responsible for straighthead disease in rice. A decrease in methanogenesis caused by silicate fertilizer may increase DMA concentration in paddy soils and rice grains; the relationship between these two factors and their impacts on DMA concentration remains unclear. We applied silicate fertilizer (2 Mg ha−1) to japonica and indica rice grown on arsenic-spiked soils and found a simultaneous reduction in methane emissions and pore-water DMA concentration, compared to no-silicate fertilization. Gene and transcript copies of mcrA and arsM, as well as dominant methanogens and arsenic-methylating microbes decreased significantly with silicate fertilization. However, the sulfate-reducing bacteria and the gene and transcript copies of dsrB did not change significantly in response to the application of silicate fertilizer to paddy soils. The abundance of arsenic methylating microbes was significantly and positively correlated with the abundance of methanogens, but not with the abundance of sulfate-reducing bacteria. Methylomonas and Methylobacter, which harbor the arsM gene, were suppressed under silicate fertilization, suggesting that they have the potential to methylate As and play a crucial role in reducing pore-water DMA in As-enriched flooded paddy soils. Increasing Fe concentration, soil pH, and Eh value decreased pore-water DMA concentration, while decreasing arsenite concentration, arsM and mcrA gene abundance decreased it. While silicate fertilization decreased arsenite and DMA concentrations in pore-water, it had no significant effect on rice DMA content, but significantly decreased arsenite content. Results reveal that methanogens and arsenic-methylating microbes have a synergistic relationship under silicate fertilization that facilitates a significant reduction in methane emissions and DMA concentration in As-enriched paddy soils.

Plant investigation and the impact on earthen site soil properties in the east city wall of the Sanxingdui site

In southern China, vegetation on exposed earthen sites serves not only to mitigate erosion but also alters their visual appearance, leading to biodeterioration. However, how plants influence the properties of earthen sites is virtually unknown. This study undertook an ecological investigation of the original habitat in the east city wall of the Sanxingdui site, analyzing its soil properties and investigating plant-soil interactions. Research findings indicate that existing plant communities are not conducive to biodiversity nor site presentation. Plants exert a direct influence within a vertical range extending 0–40 cm beneath the site; root content correlates negatively with soil pH value but positively with organic matter content. The herbaceous community (E-2 and E-3) exhibits higher clay content than the arbor community (E-1) within this range. The above conclusions exhibit statistical significance. This study offers a scientific elucidation of the ecological parameters governing plant communities concerning the conservation of earthen sites, and provides an initial influence range of plant communities and biodegradation on the east city wall of the Sanxingdui sites, thereby revealing the technical potential for employing plants as a soft capping for earthen sites in the open air from the function method.

Sentinel-2 Multispectral Satellite Remote Sensing Retrieval of Soil Cu Content Changes at Different pH Levels

With the development of multispectral imaging technology, retrieving soil heavy metal content using multispectral remote sensing images has become possible. However, factors such as soil pH and spectral resolution affect the accuracy of model inversion, leading to low precision. In this study, 242 soil samples were collected from a typical area of the Pearl River Delta, and the Cu content in the soil was detected in the laboratory. Simultaneously, Sentinel-2 remote sensing image data were collected, and two-dimensional and three-dimensional spectral indices were established. Constructing independent decision trees based on pH values, using the Successive Projections Algorithm (SPA) combined with the Boruta algorithm to select the characteristic bands for soil Cu content, and this was combined with Optuna automatic hyperparameter optimization for ensemble learning models to establish a model for estimating Cu content in soil. The research results indicated that in the SPA combined with the Boruta feature selection algorithm, the characteristic spectral indices were mainly concentrated in the spectral transformation forms of TBI2 and TBI4. Full-sample modeling lacked predictive ability, but after classifying the samples based on soil pH value, the R2 of the RF and XGBoost models constructed with the samples with pH values between 5.85 and 7.75 was 0.54 and 0.76, respectively, with corresponding RMSE values of 22.48 and 16.12 and RPD values of 1.51 and 2.11. This study shows that the inversion of soil Cu content under different pH conditions exhibits significant differences, and determining the optimal pH range can effectively improve inversion accuracy. This research provides a reference for further achieving the efficient and accurate remote sensing of heavy metal pollution in agricultural soil.

Integrating IoT for Soil Monitoring and Hybrid Machine Learning in Predicting Tomato Crop Disease in a Typical South India Station.

This study develops a hybrid machine learning (ML) algorithm integrated with IoT technology to improve the accuracy and efficiency of soil monitoring and tomato crop disease prediction in Anakapalle, a south Indian station. An IoT device collected one-minute and critical soil parameters-humidity, temperature, pH values, nitrogen (N), phosphorus (P), and potassium (K), during the vegetative growth stage, which are essential for assessing soil health and optimizing crop growth. Kendall's correlations were computed to rank these parameters for utilization in hybrid ML techniques. Various ML algorithms including K-nearest neighbors (KNN), support vector machines (SVM), decision tree (DT), random forest (RF), and logistic regression (LR) were evaluated. A novel hybrid algorithm, 'Bayesian optimization with KNN', was introduced to combine multiple ML techniques and enhance predictive performance. The hybrid algorithm demonstrated superior results with 95% accuracy, precision, and recall, and an F1 score of 94%, while individual ML algorithms achieved varying results: KNN (80% accuracy), SVM (82%), DT (77%), RF (80%), and LR (81%) with differing precision, recall, and F1 scores. This hybrid ML approach proved highly effective in predicting tomato crop diseases in natural environments, underscoring the synergistic benefits of IoT and advanced ML techniques in optimizing agricultural practices.

Properties and environmental quality of the overburden and tailings of manganese mining in the Eastern Amazon

Knowledge about the characteristics of overburden and tailings from manganese (Mn) mining is essential for defining their levels of potentially toxic elements (PTEs) and appropriate environmental management. This study aimed to assess the total and bioavailable contents of PTEs in Mn mining areas in the Eastern Amazon, as well as the associated environmental risks. The samples were collected in areas of overburden and tailings deposition, in addition to forest soils in the Azul mine, Carajás Mineral Province, Brazil. These samples were characterized in terms of fertility, granulometry, and total and bioavailable PTE contents. The pH values of the forest soil were more acidic than those of the overburden and tailings, and the organic matter contents were considerably higher in the forest soil. All PTEs, especially Mn, Ba, Cu, Zn, and Pb, presented higher contents in the overburden and tailings. However, chemical fractionation revealed that PTEs were predominantly in the residual fraction, with percentage contents above 60% of the total content. These results suggest a low risk of environmental contamination. The findings of this study may support more efficient environmental rehabilitation in Mn mining areas in the Amazon.

Impact of Dolomite Liming on Ammonia-Oxidizing Microbial Populations and Soil Biochemistry in Acidic Rice Paddy Soils

Background and Aims: Over the last few decades, rampant nitrogen fertilization has exacerbated soil acidification in agricultural ecosystems. To counteract this, liming has become an essential technique for rehabilitating fertility in acid-degraded agricultural soils. Our research aimed to shed light on the response of ammonia oxidizers to liming in acidic soils within a controlled rice paddy experiment. We conducted a pot experiment with rice, featuring three different treatments: a control with only soil, a low dolomite dose (LD), and a high dolomite dose (HD). Various soil properties were investigated throughout the study. Under flooding, soil pH values rose across the treatments, from 5.4 in the control to 6.8 in HD. Ammonium and nitrate levels peaked in the HD treatment, reaching 30 and 22 mg kg−1, respectively. Similarly, dissolved organic carbon and microbial biomass carbon surged at mid-season aeration, hitting highs of 101 and 30 mg kg−1, respectively, in the HD treatment. Ammonia-oxidizing bacteria (AOB) and archaea (AOA) were responsive to dolomite-lime application, with distinct reactions; AOB abundance and potential nitrification rates were positively affected by higher lime doses, whereas AOA numbers decreased over time and with dolomite application. Additionally, soil enzymes such as urease, catalase, invertase, phenol oxidase, and phosphatase also increased progressively, mirroring the rise in soil pH. This study identified increased soil pH as the critical factor influencing various soil parameters, especially the balance between AOA and AOB populations. Both AOB and AOA were sensitive to liming; AOA decreased while liming stimulated AOB abundance.

Pollution Evaluation and Risk Control Suggestion of Heavy Metals in Soil-crop System in Different Soil Parent Material Areas of Guangxi

To study the heavy metal pollution and influencing factors of soils and crops in different parent material areas and provide the basis for the classification and control of cultivated land, a total of 1 326 soil surface samples and 46 crop seed-root soil samples were collected from Xingye County in the southeast of Guangxi. The enrichment characteristics of heavy metals in the soil-crop system of four soil-forming parent materials were compared and analyzed, and the influencing factors of Cd absorption by rice were studied. The comprehensive quality impact index method was used to evaluate the soil and crops in the study area, and the safe use of cultivated land was proposed according to the evaluation results. The results showed that in the four soil-forming parent material areas, only the carbonate rock parent material area showed obvious enrichment of heavy metals in the soil, especially Cd. According to the "National Food Safety Standard for the Limit of Pollutants in Food" （GB 2762-2022）, the excess rate of heavy metal Cd in rice seeds was 35.7%, and the other heavy metal rates were not exceeded. The bioconcentration coefficient of heavy metal Cd in rice from different parent material areas was as follows： quaternary sediment area > carbonate parent material area > clastic parent material area > granite parent material area. The enrichment of Cd in rice was affected by soil pH and CaO. When the soil pH value was in the range of 5.5-6.5, the Cd content and exceeding rate of rice seed increased significantly. The evaluation results of soil-crop heavy metal pollution showed that the overall heavy metal risk in the study area was high, and the proportions of clean, mild, light, moderate, and heavy pollution were 23.91%, 10.87%, 17.39%, 17.39%, and 30.43%, respectively. Combined with the distribution of the comprehensive quality influence index and the pollution characteristics of different parent materials, the classification and control suggestions were put forward, which provided ideas for the safe utilization of polluted cultivated land.

Plant Monitoring System Using Gray Level Co-occurrence Matrix and Weight Based Artificial Neural Network Algorithm over Internet of Things

The potential deployment of the plant monitoring system in cutting-edge technologies is currently generating a great deal of interest. A new IoT-based technology is used to track both the development and wellness of the plant. Setting up cross-device connectivity over the internet is the idea underlying IoT devices. It is a sizable network that links people and various interconnected elements in order to gather and transmit data. This research article aims to generate a manufacturing Internet of Things (IoT) based plant monitoring system that uses IoT sensors to detect environmental conditions. The IoT term is used to link objects to the internet and make it easier for consumers to obtain data. The technology can accurately perceive the surroundings in agriculture and convey the data to users. The system keeps track of several factors like soil moisture, temperature, and light intensity. The method begins with the collection of plant images and noise reduction pre-processing. Once the images have been segmented, they are done so utilizing the Region based K-Means Clustering (RKMC) technique. Following that, Gray Level Co-occurrence Matrix (GLCM) is utilized to extract features, with a focus on extracting the more informative characteristics like color, texture, and shape features. The classifying process is completed by utilizing Weight based Artificial Neural Network (WANN) algorithm for improving the plant monitoring system performance significantly. It offers IoT-based solutions to categorize plant illnesses and observe variables including soil moisture, air temperature, and pH values. Te findings of the suggested GLCM-WANN algorithm show better performers than existing methods for obtained values of computation complexity, accuracy, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE).

The interaction of microplastic and heavy metal in bioretention cell: Contributions of water-soil-plant system

The effectiveness of bioretention cells for heavy metals (HMs) and microplastics (MPs) removal from stormwater runoff has been demonstrated. Knowledge of the mechanisms that dictate the interactions between MPs and HMs would be helpful in pollution control. In this study, the performances of different water-soil-plant bioretention cells for HMs removal through the interception of polyethylene MPs (PE-MPs) were investigated. The results showed that PE-MPs bound to HMs and preferentially tended to bind to Pb (32%–44%) in the complex HMs (Cu, Zn, Cd, and Pb). This could be the reason that the concentration of Pb significantly increased in the effluent under low-intensity simulated rainfall events over a long duration. The accumulation of 1.49 g/kg PE-MPs caused a significant soil pH value decrease and a notable soil zeta potential increase in the bioretention cell, while the low sand/silt ratio media buffered this process. The retention of PE-MPs increased 138.5% in the 0–10 cm soil surface layer when the sand/silt ratio reduced from 2:1 to 1:1 and planted with Canna indica. Meanwhile, PE-MPs amplified the instability of Zn removal in bioretention cells under low-intensity rainfall events in long-duration, high silt percentage substrate and vegetation coverage. The study would contribute to developing a long-term management program for PE-MPs and HMs trapped in bioretention cells to reduce the risk of pollution transport.

Asynchronous Synergetic Remediation Strategy for Cd-Contaminated Soil via Passivation and Phytoremediation Technology

Cadmium (Cd) contamination in soil has emerged as a significant challenge for agricultural production. Phytoremediation and passivation are key techniques for remediating Cd-contaminated soil. However, few studies have focused on the synergistic effects of these two techniques. In this work, the effectiveness of synergetic remediation strategies, both synchronous and asynchronous, utilizing passivation and phytoremediation techniques, was explored. The results of pot experiments and field experiments indicated that optimal remediation effects were obtained by asynchronous synergetic remediation, removing over 80% of bioavailable Cd within 14 days. Mechanistic studies conducted using XPS analysis, soil property analysis, and microbial diversity analysis confirmed that the chelation effect of SDD and soil pH value are the primary factors contributing to the effectiveness of both remediation strategies. In contrast, the variations in microbial populations are identified as the crucial factors influencing the varying outcomes of the two sequential remediation approaches. This research demonstrates that asynchronous synergistic remediation is a promising strategy for mitigating Cd contamination in soil.