Machine learning predicts ecological risks of nanoparticles to soil microbial communities

• Published in: Environmental pollution (1987) Vol. 307; p. 119528
• Main Authors: Xu, Nuohan, Kang, Jian, Ye, Yangqing, Zhang, Qi, Ke, Mingjing, Wang, Yufei, Zhang, Zhenyan, Lu, Tao, Peijnenburg, W.J.G.M., Josep Penuelas, Bao, Guanjun, Qian, Haifeng
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 15.08.2022
• Subjects: biosynthesis; chronic exposure; Ecotoxicity; edaphic factors; Machine learning; metadata; Metadata analysis; Methylophilus; microbial communities; Microbiota; Nanoparticles; pollution; Soil ecosystems; soil heterogeneity; soil microorganisms; species diversity; Streptomyces; Nanoparticles; Microbiota; Soil ecosystems; Ecotoxicity; Machine learning; Metadata analysis

With the rapid development of nanotechnology in agriculture, there is increasing urgency to assess the impacts of nanoparticles (NPs) on the soil environment. This study merged raw high-throughput sequencing (HTS) data sets generated from 365 soil samples to reveal the potential ecological effects o...