AIMC Topic: Soil

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Machine learning-driven analysis of soil microplastic distribution in the Bang Pakong Watershed, Thailand.

Environmental pollution (Barking, Essex : 1987)
Microplastics (MPs) have emerged as a pervasive environmental pollutant due to their persistence and global distribution. However, MPs relationships with covariables remain largely unexplored. This study investigates factors influencing MPs occurrenc...

Investigation of spatially varying relationships between cadmium accumulation and potential controlling factors in the topsoil of island of Ireland based on spatial machine learning approaches.

Environmental research
BACKGROUND: Cadmium (Cd) contamination in soils is a pressing environmental issue due to its toxicity and persistence. Given the diverse geological formations and intensive agricultural activities in Ireland, understanding the distribution and source...

Machine learning-assisted source identification and probabilistic ecological-health risk assessment of heavy metal(loid)s in urban park soils.

Scientific reports
The accumulation of heavy metal(loid)s (HMs) in the soils of urban parks in industrial cities has raised global concerns because of their environmental and health impacts. However, traditional deterministic assessments commonly overlook uncertainties...

Water status and plant traits of dry bean assessment using integrated spectral reflectance and RGB image indices with artificial intelligence.

Scientific reports
This study investigated the potential of using remote sensing indices with artificial neural networks (ANNs) to quantify the responses of dry bean plants to water stress. Two field experiments were conducted with three irrigation regimes: 100% (B100)...

Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM.

PloS one
Soil pH is an important parameter that affects plant nutrient uptake and biological activity and has received extensive attention and research. In this paper, we propose a neural network algorithm using Ghostnet combined with Convolutional Block Atte...

A framework for identifying calcium accumulation problem in cropland: Integrating field surveys, legacy soil map, and machine learning models.

PloS one
The calcium accumulation problem (CAP) in cinnamon soil regions of northern China significantly impacts crop yields. Identifying and mitigating CAP is crucial for improving soil quality and agricultural productivity. This study, based on field resear...

Integrated irrigation of water and fertilizer with superior self-correcting fuzzy PID control system.

PloS one
To address the fixed-parameter limitations of traditional PID control (e.g., excessive overshoot, prolonged settling time, poor adaptability to nonlinearities) and the insufficient real-time adjustment capability of conventional fuzzy PID control, wh...

Dominant Edaphic Controls on Particulate Organic Carbon in Global Soils.

Global change biology
The current soil carbon paradigm puts particulate organic carbon (POC) as one of the major components of soil organic carbon worldwide, highlighting its pivotal role in carbon mitigation. In this study, we compiled a global dataset of 3418 data point...

[Soil Cadmium Prediction and Health Risk Assessment of an Oasis on the Eastern Edge of the Tarim Basin Based on Feature Optimization and Machine Learning].

Huan jing ke xue= Huanjing kexue
Soil heavy metal pollution poses a serious threat to food security, human health, and soil ecosystems. Based on 644 soil samples collected from a typical oasis located at the eastern margin of the Tarim Basin, a series of models, namely, multiple lin...

[Multi-factor Impact Analysis of Grassland Phenology Changes on the Qinghai-Xizang Plateau Based on Interpretable Machine Learning].

Huan jing ke xue= Huanjing kexue
The vegetation phenology of the Qinghai-Xizang Plateau is changing significantly in the context of climate change. However, there are many hydrothermal factors affecting the phenology, and few studies have focused on the effects of multiple factors o...