From Metabolic Reprogramming to Diagnostic Tool: A Machine Learning Framework Identifies Biomarkers for Soil Microplastic Stress in Rice

Ding Sheng

doi:10.1016/j.jhazmat.2026.142581

From Metabolic Reprogramming to Diagnostic Tool: A Machine Learning Framework Identifies Biomarkers for Soil Microplastic Stress in Rice

2026-06-02

0

PRE

AI

D

Ding Sheng

Y

Yao Liu

S

Shanshan Yin

Y

Yaowu Cao *

L

Long Teng

K

Kejie Cai

H

Hongbing Chen

J

Jun Cao

Z

Zongqing Ding

Z

Zukai Zhang

J

Jiong Gao

C

Chen Yang

Y

Yeran Huang

T

Tie Tian

X

Xiang Wu *

DOI：10.1016/j.jhazmat.2026.142581

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Abstract

En 中文

• Integrates untargeted metabolomics and machine learning to identify 7 biomarkers of rice responses to soil microplastic stress • Microplastics disrupt rice metabolism, revealing key metabolic reprogramming under microplastic stress • The stacking ensemble model achieves high predictive performance with robust classification ability • Provides a potentially scalable biomarker-based framework for assessing microplastic-induced soil stress

From Metabolic Reprogramming to Diagnostic Tool: A Machine Learning Framework Identifies Biomarkers for Soil Microplastic Stress in Rice

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