您好，欢迎访问浙江省农业科学院 机构知识库！
浙江省农业科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Integrating automated machine learning and metabolic reprogramming for the identification of microplastic in soil: A case study on soybean

文献类型： 外文期刊

作者： Liu, Zhimin 1 ; Wang, Weijun 1 ; Geng, Yibo 1 ; Zhang, Yuting 1 ; Gao, Xuan 1 ; Xu, Junfeng 2 ; Liu, Xiaolu 1 ;

作者机构： 1.Univ Sci & Technol Beijing, Sch Chem & Biol Engn, 30 Xueyuan Rd, Beijing 100083, Peoples R China

2.Zhejiang Acad Agr Sci, State Key Lab Managing Biot & Chem Threats Qual &, Hangzhou 310021, Peoples R China

关键词： Polyethylene microplastic; Automated machine learning; Explainable analysis; Metabolic reprogramming; Soybean

期刊名称：JOURNAL OF HAZARDOUS MATERIALS （ 影响因子：11.3； 五年影响因子：12.4 ）

ISSN： 0304-3894

年卷期： 2024 年 478 卷

页码：

收录情况： SCI

摘要： The accumulation of polyethylene microplastic (PE-MPs) in soil can significantly impact plant quality and yield, as well as affect human health and food chain cycles. Therefore, developing rapid and effective detection methods is crucial. In this study, traditional machine learning (ML) and H2O automated machine learning (H2O AutoML) were utilized to offer a powerful framework for detecting PE-MPs (0.1 %, 1 %, and 2 % by dry soil weight) and the co-contamination of PE-MPs and fomesafen (a common herbicide) in soil. The development of the framework was based on the results of the metabolic reprogramming of soybean plants. Our study stated that traditional ML exhibits lower accuracy due to the challenges associated with optimizing complex parameters. H2O AutoML can accurately distinguish between clean soil and contaminated soil. Notably, H2O AutoML can detect PE-MPs as low as 0.1 % (with 100 % accuracy) and co-contamination of PE-MPs and fomesafen (with 90 % accuracy) in soil. The VIP and SHAP analyses of the H2O AutoML showed that PE-MPs and the co-contamination of PE-MPs and fomesafen significantly interfered with the antioxidant system and energy regulation of soybean. We hope this study can provide a reliable scientific basis for sustainable development of the environment.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：浙江省农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台