AIMC Topic: Soil

Clear Filters Showing 291 to 300 of 319 articles

Synergistic potential of halophytes and halophilic/halotolerant plant growth-promoting bacteria in saline soil remediation: Adaptive mechanisms, challenges, and sustainable solutions.

Microbiological research
Salinity stress poses significant challenges to agriculture, reducing productivity and limiting arable land by causing ionic and osmotic imbalances in plants, disrupting physiological processes, and leading to soil degradation over time. Halophytes a...

Predicting growth parameters of biofertilizer inoculated pepper, using root capacitance assessments and artificial neural networks in two soils.

Biologia futura
Monitoring the root system plays an important role in understanding plant physiological processes; however, its assessment using non-destructive methods remains challenging. Here, we evaluate the utility of root capacitance (C) as a practical indicat...

A critical review on occurrence, speciation, mobilization, and toxicity of per- and polyfluoroalkyl substances in the soil-microbe-plant system and bioremediation strategies.

Journal of hazardous materials
Per- and polyfluoroalkyl substances (PFAS) are a group of recalcitrant anthropogenic compounds that are extensively utilized for numerous industrial applications globally. Despite such vast utilization, PFAS accumulation in the soils and sediments wi...

Total nitrogen levels as a key constraint on soil organic carbon stocks across Australian agricultural soils.

Environmental research
Understanding how pedoclimatic drivers regulate soil organic carbon (SOC) stock is crucial for gaining insights into terrestrial carbon-climate feedback and thus adaptation to climate change. However, current data-driven SOC predictive models often n...

Heuristic Topological Graph Convolutional Network for Risk Prediction of Potentially Toxic Elements in Cultivated Soils.

Environmental science & technology
Contamination of cultivated soils with potentially toxic elements (PTEs) poses a growing threat to global food security. Although existing risk assessments have examined the accumulation and toxicity of PTEs, their dynamic interplay with multidimensi...

Afforestation Surpasses Abandonment in the Recovery of Post-Agricultural Soil Organic Carbon in China as Estimated by Machine Learning Models.

Global change biology
The surface soil organic carbon (SOC) dynamics typically follow a trend of initial loss followed by subsequent accumulation after cropland abandonment. However, the timing of SOC stock increase (referred to as the threshold in this study) remains ins...

Unraveling soil salinity on potentially toxic element accumulation in coastal Phragmites australis: A novel integration of multivariate and interpretable machine-learning models.

Marine pollution bulletin
Revealing the key mechanisms influencing the behavior of potentially toxic elements (PTEs) in soil-plant systems is of great significance for environmental protection and grassland development in coastal areas. This study utilized redundancy analysis...

Data-Driven Estimates of High-Resolution Soil HONO Emissions in China from 2000 to 2020.

Environmental science & technology
Soil nitrous acid (HONO) emissions influence air quality by affecting atmospheric oxidizing capacity and secondary pollutant formation. However, estimating soil HONO emissions remains uncertain due to complex factors and limited data. Here, we presen...

Soil type and content of macro-elements determine hotspots of Cu and Ni accumulation in soils of subarctic industrial barren: inference from a cascade machine learning.

Environmental pollution (Barking, Essex : 1987)
Aerial technogenic pollution from the activity of ferrous and non-ferrous metallurgy resulting in degradation of vulnerable natural ecosystems is a principal environmental problem in Russian Arctic. The industrial barren in the vicinity of Monchegors...

Optimizing swine manure composting parameters with integrated CatBoost and XGBoost models: nitrogen loss mitigation and mechanism.

Journal of environmental management
In this study, machine learning was used to optimize the aerobic composting process of swine manure to enhance nitrogen retention and compost maturity in order to meet the demand for high-quality organic fertilizers in sustainable agriculture. In thi...