Elucidating the synergistic effects of potential heavy metal toxicity in tea soil on microbial diversity and traits through metagenomics and machine learning approaches.

This study aims to investigate the combined effects of potential heavy metal toxicity in tea soil on microbial diversity and functional traits using advanced metagenomic and machine learning approaches. By unraveling the intricate interactions between soil microbial communities, the research seeks to identify key microbial taxa and functional pathways affected by heavy metals. These insights are critical for understanding the resilience and adaptability of soil microbiomes under environmental stress. The study is particularly relevant for sustainable agriculture, as it can guide the development of strategies to mitigate heavy metal toxicity, maintain soil health, and ensure the productivity of tea plantations, which are vital for both local economies and global markets.