Summary
This narrative review examines emerging technologies for extraction and diagnosis of plant pathogens in agricultural settings. The authors highlight that whilst traditional serological and nucleic acid-based assays dominate current practice, they lack the precision, specificity and speed required for field-level deployment. The review advances the case for field-deployable point-of-care devices and artificial intelligence-assisted detection platforms, coupled with simplified sample preparation protocols, as critical tools for early-stage pathogen identification and crop health monitoring.
UK applicability
The diagnostic approaches reviewed are applicable to UK crop production and disease surveillance. Field-deployable diagnostics could support UK farmers and agronomists in rapid on-farm monitoring and decision-making, particularly given the UK's diverse horticultural and arable sectors and emerging disease pressures from climate change.
Key measures
Sensitivity and specificity of diagnostic assays; rapidity of detection; field-deployability of point-of-care devices; cell-lysis and purification-free extraction efficiency; AI-assisted detection accuracy and deployment timescale
Outcomes reported
This review synthesises emerging extraction and diagnostic technologies for plant pathogen detection, including field-deployable point-of-care devices and AI-assisted approaches. The paper discusses advances in nucleic acid extraction methods and detection platforms, evaluating their sensitivity, specificity, rapidity, and suitability for on-field deployment.
Topic tags
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