1. Characterization of core microbiota of barley seeds from different continents for origin tracing and quarantine pathogen assessment.
- Author
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Zhou, Xin, Liu, Fang, Wang, Chun-Chun, Zhang, Hui-Li, Zhao, Peng, Xie, Fu-Hong, Hu, Dian-Ming, Duan, Wei-Jun, and Cai, Lei
- Subjects
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MACHINE learning , *BIOLOGICAL pest control agents , *FUNGAL communities , *BACTERIAL communities , *MICROBIAL communities - Abstract
Seeds are important microbial vectors, and seed-associated pathogens can be introduced into a country through trade, resulting in yield and quality losses in agriculture. The aim of this study was to characterize the microbial communities associated with barley seeds, and based on which, to develop technical approaches to trace their geographical origins, and to inspect and identify quarantine pathogens. Our analysis defined the core microbiota of barley seed and revealed significant differences in the barley seed-associated microbial communities among different continents, suggesting a strong geographic specificity of the barley seed microbiota. By implementing a machine learning model, we achieved over 95% accuracy in tracing the origin of barley seeds. Furthermore, the analysis of co-occurrence and exclusion patterns provided important insights into the identification of candidate biocontrol agents or microbial inoculants that could be useful in improving barley yield and quality. A core pathogen database was developed, and a procedure for inspecting potential quarantine species associated with barley seed was established. These approaches proved effective in detecting four fungal and three bacterial quarantine species for the first time in the port of China. This study not only characterized the core microbiota of barley seeds but also provided practical approaches for tracing the regional origin of barley and identifying potential quarantine pathogens. [Display omitted] • We characterized the barley-seed associated bacterial and fungal communities of Oceania, North America, and Europe. • Our analysis defined the core microbiota of barley seed and revealed significant differences among different continents, suggesting a strong geographic specificity of the barley seed microbiota. • We could accurately predict the original countries of imported barley grains within the RF prediction model, with an accuracy greater than 95%. • We constructed a barley-related quarantine pathogens database. Based on this database, some important pathogens were intercepted through metabarcoding sequencing. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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