Efficiency of metal oxides in reducing heavy metal uptake in typical crops: A machine learning-assisted meta-analysis
文献类型: 外文期刊
作者: Tao Min;Tao Lu;Shen Zheng;Wenfeng Tan;Tong Luo;Guohong Qiu
作者机构:
关键词: (0-1-4)Food security;Heavy metals;Machine learning;Meta-analysis;Metal oxides
期刊名称: Journal of Cleaner Production
ISSN: 0959-6526
年卷期: 2025 年 491 卷
页码:
收录情况: SCIE(2025版) ; ; EI(2025版)
摘要: Heavy metal pollution poses a significant threat to safe agricultural production. Metal oxides can be utilized to effectively reduce heavy metal uptake in crops. However, previous studies have reported inconsistent findings, and the factors influencing their effects remain elusive. In this work, a meta-analysis was conducted on 90 peer-reviewed articles to quantitatively assess the effects of different factors on the heavy metal uptake and biomass of typical crops, and machine learning was employed to identify the key influencing factors. The results indicated that the presence of metal oxides could decrease the heavy metal content in the edible part, shoot, and root by 44.7%, 24.9%, and 22.3%, respectively, with iron oxides and cerium oxides exhibiting particularly excellent performance. Moreover, such changes were particularly pronounced in fruits and grains. Application of metal oxides increased the edible part and shoot biomass by increasing the chlorophyll content and antioxidant capacity, especially that of valence-variable metals. Random forest analysis revealed that the empirical categories for heavy metal uptake of crops followed an order of soil properties > metal oxide characteristics > experimental conditions > heavy metal properties in importance. The partial dependence plots further identified the marginal contributions of soil organic matter, pH, cation exchange capacity, primary size and dosage of metal oxides, and exposure time to the model output outcomes. Overall, iron oxides and cerium oxides are recommended to be used for safe and high-quality production of typical crops, especially in alkaline soils.
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