Fusarium root rot caused by the Fusarium species complex significantly affects the yield and quality of Angelica sinensis, a valuable medicinal herb. Traditional management primarily relies on chemical fungicides, which have led to pathogen resistance, environmental hazards, and concerns regarding public health and the active components in A. sinensis. This study explores the efficacy of a novel plant-derived biopesticide Shi Chuang Zhi Feng Ning (T1; SCZFN), alongside Bacillus subtilis wettable powder (T2) and a chemical fungicide (T3), in controlling root rot and understanding their impacts on the rhizosphere microbial community and root metabolome. Results of the field experiment demonstrated that treatments T1 and T3 achieved control efficiencies of 73.17% and 75.45%, respectively, significantly outperforming T2 (39.99%) and the control. High-throughput sequencing revealed that all treatments altered the diversity and structure of microbial communities, with T1 and T2 reducing the abundance of taxa linked to root rot, such as Muribaculaceae spp., Humicola spp., Fusarium spp., and Mycochlamys spp. Treatment T1 notably enhanced beneficial bacterial taxa, including Acidobacteria spp., Nitrospira spp., and Pedosphaeraceae spp., involved in carbon cycling and plant growth promotion. Metabolomic analysis identified 39, 105, and 45 differentially expressed metabolites (DEMs) across the treatments, demonstrating T1's potential to modulate the root metabolome effectively. Further, a correlation analysis demonstrated a stronger correlation between distinct microorganisms with significant influence and DEMs of T1 treatment compared to other treatments. These findings underscore biopesticide SCZFN's role in enhancing plant health and disease suppression in A. sinensis, providing insights into its biocontrol mechanisms and supporting the development of sustainable disease management strategies in its cultivation.
Keywords: Angelica sinensis; biological control; disease suppression; rhizosphere microbiome modulation; root metabolomics.