Advances in Molecular Techniques for Detecting Sweet Potato (Ipomoea batatas (L.) Lam) Viruses: A Comprehensive Review

Abstract

Sweet potato (Ipomoea batatas (L.) Lam) is an important global food crop, but its production is threatened by numerous viral pathogens. More than 30 RNA and DNA viruses have been reported worldwide, making rapid and accurate detection essential for disease management, epidemiological surveillance, germplasm exchange, and resistance breeding. Although previous reviews have addressed sweet potato viruses and individual diagnostic methods, a comprehensive synthesis of emerging molecular technologies remains limited. This review addresses that gap by critically integrating recent advances from PCR-based and isothermal assays to high-throughput sequencing, CRISPR-based diagnostics, biosensors, nanotechnology, and artificial intelligence-driven detection platforms. Conventional approaches, including symptom observation, biological indexing, electron microscopy, and ELISA, have contributed to early virus identification but often lack the sensitivity, specificity, and speed needed for modern diagnostics. Molecular and isothermal techniques have substantially improved detection accuracy and enabled rapid identification and field-deployable diagnostics of diverse and mixed infections, while sequencing, CRISPR, biosensors, and AI-based platforms offer greater capacity for detecting novel and emerging viruses. This review discusses the comparative evaluation of molecular technologies for sweet potato virus detection in terms of diagnostic performance, cost-effectiveness, speed, and suitability for both laboratory and field applications, while highlighting future priorities for next-generation virus diagnostics. Integrating portable and high-throughput diagnostic platforms will strengthen virus surveillance, support virus-free planting material production, and promote sustainable sweet potato production worldwide.