International Journal of Molecular Sciences · 2023 · 10 citations · 65 references
AgricultureBioinformaticsPlant PathologyMolecular DiagnosticsPlant Disease DiagnosisPlant-microbe InteractionsFungal DiagnosticsMolecular DiagnosisPathogen DetectionPlant Virus DetectionPlant-pathogen InteractionsPlant-pathogenic FungiCausative PathogensFungal Pathogen DetectionMolecular Pathogen DetectionPathogen DiagnosisPathogen-plant InteractionsPlant Pathogen DetectionRapid Molecular DiagnosticsWhole-genome Sequencing Analysis
-tetrahydrocannabinol-containing (high-THC) cannabis genotypes and low-THC-containing hemp genotypes, has been impacted by an increasing number of plant pathogens. These include fungi which destroy roots, stems, and leaves, in some cases causing a build-up of populations and mycotoxins in the inflorescences that can negatively impact quality. Viroids and viruses have also increased in prevalence and severity and can reduce plant growth and product quality. Rapid diagnosis of the occurrence and spread of these pathogens is critical. Techniques in the area of molecular diagnostics have been applied to study these pathogens in both cannabis and hemp. These include polymerase chain reaction (PCR)-based technologies, including RT-PCR, multiplex RT-PCR, RT-qPCR, and ddPCR, as well as whole-genome sequencing (NGS) and bioinformatics. In this study, examples of how these technologies have enhanced the rapidity and sensitivity of pathogen diagnosis on cannabis and hemp will be illustrated. These molecular tools have also enabled studies on the diversity and origins of specific pathogens, specifically viruses and viroids, and these will be illustrated. Comparative studies on the genomics and metabolomics of healthy and diseased plants are urgently needed to provide insight into their impact on the quality and composition of cannabis and hemp-derived products. Management of these pathogens will require monitoring of their spread and survival using the appropriate technologies to allow accurate detection, followed by appropriate implementation of disease control measures.
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