Machine Learning Workflow for Identifying Key Metabolites Linked to Oxidative Potential in Contaminated Soils. (IMAGE)

Nanjing Institute of Environmental Sciences, MEE

Machine Learning Workflow for Identifying Key Metabolites Linked to Oxidative Potential in Contaminated Soils.

Caption

This diagram outlines the process used to identify the top 20 metabolites associated with oxidative potential (OP) in heavy metal-contaminated soils. The analysis involves data collection from ryegrass exposed to Cu and Pb, followed by model development using various machine learning techniques, including random forest and XGBoost. Five-fold cross-validation is used for performance evaluation, and SHAP analysis is applied to interpret the importance of metabolites, leading to the identification of key metabolites related to OP.

Credit

Eco-Environment & Health

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CC BY

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