AIMC Topic: Soil
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Reevaluating the Drivers of Fertilizer-Induced NO Emission: Insights from Interpretable Machine Learning.
Environmental science & technology
Aug 20, 2024
Direct nitrous oxide (NO) emissions from fertilizer application are the largest anthropogenic source of global NO, but the factors influencing these emissions remain debated. Here, we compile 1134 observations of fertilizer-induced NO emission factor...
Estimation of 100 m root zone soil moisture by downscaling 1 km soil water index with machine learning and multiple geodata.
Environmental monitoring and assessment
Aug 19, 2024
Root zone soil moisture (RZSM) is crucial for agricultural water management and land surface processes. The 1 km soil water index (SWI) dataset from Copernicus Global Land services, with eight fixed characteristic time lengths (T), requires root zone...
Application of machine learning approaches to predict ammonium nitrogen transport in different soil types and evaluate the contribution of control factors.
Ecotoxicology and environmental safety
Aug 17, 2024
The loss of nitrogen in soil damages the environment. Clarifying the mechanism of ammonium nitrogen (NH-N) transport in soil and increasing the fixation of NH-N after N application are effective methods for improving N use efficiency. However, the ma...
Harnessing artificial intelligence microscopy to improve diagnostics for soil-transmitted helminthiasis and schistosomiasis: a review of recent advances and future pathways.
Current opinion in infectious diseases
Aug 2, 2024
PURPOSE OF REVIEW: This opinion piece aims to explore the transformative potential of integrating artificial intelligence with digital microscopy to enhance diagnostics for soil-transmitted helminthiasis (STH) and schistosomiasis (SCH), two pervasive...
Soil organic carbon estimation using remote sensing data-driven machine learning.
PeerJ
Aug 1, 2024
Soil organic carbon (SOC) is a crucial component of the global carbon cycle, playing a significant role in ecosystem health and carbon balance. In this study, we focused on assessing the surface SOC content in Shandong Province based on land use type...
Quantifying the impact of factors on soil available arsenic using machine learning.
Environmental pollution (Barking, Essex : 1987)
Jul 17, 2024
Arsenic (As) can accumulate in edible plant parts and thus pose a serious threat to human health. Identifying the contributions of various factors to soil available As is crucial for evaluating environmental risks. However, research quantitatively as...
Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area.
Environmental geochemistry and health
Jul 13, 2024
Mining activities have resulted in a substantial accumulation of cadmium (Cd) in agricultural soils, particularly in southern China. Long-term Cd exposure can cause plant growth inhibition and various diseases. Rapid identification of the extent of s...
Uptake of zinc from the soil to the wheat grain: Nonlinear process prediction based on artificial neural network and geochemical data.
The Science of the total environment
Jul 10, 2024
Trace elements in plants primarily derive from soils, subsequently influencing human health through the food chain. Therefore, it is essential to understand the relationship of trace elements between plants and soils. Since trace elements from soils ...
Machine learning-driven source identification and ecological risk prediction of heavy metal pollution in cultivated soils.
Journal of hazardous materials
Jul 5, 2024
To overcome challenges in assessing the impact of environmental factors on heavy metal accumulation in soil due to limited comprehensive data, our study in Yangxin County, Hubei Province, China, analyzed 577 soil samples in combination with extensive...
Ensemble learning algorithms to elucidate the core microbiome's impact on carbon content and degradation properties at the soil aggregate level.
The Science of the total environment
Jul 4, 2024
Soil aggregates are crucial for soil organic carbon (OC) accumulation. This study, utilizing a 32-year fertilization experiment, investigates whether the core microbiome can elucidate variations in carbon content and decomposition across different ag...
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