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Plant diseases are responsible for 20–40% of global crop yield losses, posing a significant threat to food security in the face of an ever-growing population. Genomic surveillance emerges as a powerful tool for diagnosing, early warning, and mitigating emerging plant diseases. This approach provides molecular insights into plant-pathogen interactions, essential for developing durable management strategies. Various omics techniques, including metagenomics, are employed in genomic surveillance to systematically monitor and analyze pathogen genomes. These analyses enable early detection of emerging threats, characterization of pathogen populations, tracking of pathogen movement, and accurate prediction of disease outbreaks. Genomic data serve as the foundation for point-of-care disease management using genome-specific primers and CRISPR technology. Despite its significant advantages, genomic surveillance faces challenges such as data analysis complexity, protocol standardization, ethical considerations, and technology accessibility. Key strategies to address these challenges include open data sharing, open science, and international collaboration. Recent advancements in sequencing technologies, bioinformatics tools, and collaborative networks offer promising solutions to these challenges, enhancing the potential of genomic surveillance in plant pathology. This comprehensive review updates the current progress and future prospects of genomic surveillance in disease detection and sustainable plant health management. It critically discusses the challenges of large-scale application and explores mitigation strategies through open data sharing, open science, and international collaboration.
Plant diseases are responsible for 20–40% of global crop yield losses, posing a significant threat to food security in the face of an ever-growing population. Genomic surveillance emerges as a powerful tool for diagnosing, early warning, and mitigating emerging plant diseases. This approach provides molecular insights into plant-pathogen interactions, essential for developing durable management strategies. Various omics techniques, including metagenomics, are employed in genomic surveillance to systematically monitor and analyze pathogen genomes. These analyses enable early detection of emerging threats, characterization of pathogen populations, tracking of pathogen movement, and accurate prediction of disease outbreaks. Genomic data serve as the foundation for point-of-care disease management using genome-specific primers and CRISPR technology. Despite its significant advantages, genomic surveillance faces challenges such as data analysis complexity, protocol standardization, ethical considerations, and technology accessibility. Key strategies to address these challenges include open data sharing, open science, and international collaboration. Recent advancements in sequencing technologies, bioinformatics tools, and collaborative networks offer promising solutions to these challenges, enhancing the potential of genomic surveillance in plant pathology. This comprehensive review updates the current progress and future prospects of genomic surveillance in disease detection and sustainable plant health management. It critically discusses the challenges of large-scale application and explores mitigation strategies through open data sharing, open science, and international collaboration.
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