AI Article Synopsis
- The study focused on developing an integrated biovigilance platform to understand and combat crop diseases, particularly cereal rust pathogens, through advanced tools like DNA diagnostics and predictive modeling.
- Research conducted in British Columbia and southern Alberta from 2015 to 2018 tracked microbial dynamics and revealed that air flow barriers affected pathogen dispersal across diverse environments.
- The use of bioinformatics and modeling techniques improved the identification of rust species and highlighted key environmental factors influencing their distribution, ultimately contributing to a system that aids farmers in early disease detection and prevention.
Article Abstract
In the face of evolving agricultural practices and climate change, tools towards an integrated biovigilance platform to combat crop diseases, spore sampling, DNA diagnostics and predictive trajectory modelling were optimized. These tools revealed microbial dynamics and were validated by monitoring cereal rust fungal pathogens affecting wheat, oats, barley and rye across four growing seasons (2015-2018) in British Columbia and during the 2018 season in southern Alberta. ITS2 metabarcoding revealed disparity in aeromycobiota diversity and compositional structure across the Canadian Rocky Mountains, suggesting a barrier effect on air flow and pathogen dispersal. A novel bioinformatics classifier and curated cereal rust fungal ITS2 database, corroborated by real-time PCR, enhanced the precision of cereal rust fungal species identification. Random Forest modelling identified crop and land-use diversification as well as atmospheric pressure and moisture as key factors in rust distribution. As a valuable addition to explain observed differences and patterns in rust fungus distribution, trajectory HYSPLIT modelling tracked rust fungal urediniospores' northeastward dispersal from the Pacific Northwest towards southern British Columbia and Alberta, indicating multiple potential origins. Our Canadian case study exemplifies the power of an advanced biovigilance toolbox towards developing an early-warning system for farmers to detect and mitigate impending disease outbreaks.
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| http://dx.doi.org/10.1111/1755-0998.13983 | DOI Listing |
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