The global agricultural sector faces increasing pressure to ensure food safety and supply chain integrity amidst rising phytosanitary regulations and climate-induced disease outbreaks. Rapid, decentralized diagnostic tools are becoming essential for compliance and competitive advantage. This technology addresses the urgent need for efficient disease management, enabling faster trade clearances and protecting crop investments, which is critical as global trade volumes for fresh produce continue to expand, projected to grow by over 5% annually.
Enables On-Site, Immediate Diagnosis: RT-LAMP requires no specialized equipment, allowing rapid diagnosis in fields or quarantine stations, contributing to early disease detection and spread prevention.
Ensures High Specificity and Reliability: Utilizes specific primer sets for JPCSaV RNA1-RNA5, accurately identifying pathogens and significantly reducing misdiagnosis risk.
Offers Simple Operation: Compared to PCR, which requires complex pre-processing and advanced skills, RT-LAMP is simpler to operate, enabling use by personnel with limited specialized knowledge.
This patent protects a method and kit for detecting JPCSaV using specific RT-LAMP primer sets, covering the detection process, kit components, and the primers themselves. The claims were robustly established and granted after overcoming an office action, demonstrating strong novelty and inventiveness against existing prior art.
This patent specifically covers RT-LAMP for JPCSaV. White space exists in developing broader multi-pathogen detection panels for other plant diseases or integrating this diagnostic method with automated sampling and data analytics platforms.
Assuming annual domestic pear disease losses of ~$6.5M (AI est.), with JPCSaV accounting for 5%, this technology could suppress disease spread by 20%, potentially avoiding ~$0.5M (AI est.) in annual losses. Additionally, rapid detection in quarantine could halve traditional inspection costs (annual ~$50K (AI est.)), saving ~$50K (AI est.).
X: On-Site Rapidity
Y: Implementation Cost Efficiency