Biotechnological Approaches for Plant Disease Isolation and Identification: Advances and Applications

Plant diseases caused by fungi, bacteria, viruses, phytoplasmas, nematodes, and oomycetes continue to pose a major threat to global agricultural productivity and food security. Early, accurate, and reliable identification of plant pathogens is a cornerstone of effective disease management. Conventional diagnostic methods based on symptomatology, microscopy, and culture-based isolation are often time-consuming, labor-intensive, and limited in sensitivity and specificity. Over the past two decades, biotechnological innovations have transformed plant disease diagnostics by enabling rapid, precise, and high-throughput detection of pathogens at molecular, genomic, and phenotypic levels. This review critically examines advances in biotechnological approaches for plant disease isolation and identification, integrating molecular diagnostics, high-throughput sequencing, CRISPR-based systems, biosensors, and artificial intelligence-driven imaging technologies. Comparative analyses of traditional and modern techniques are presented, highlighting their analytical performance, advantages, limitations, and practical applications. The review also discusses emerging trends, field-deployable platforms, and future prospects for integrated plant disease diagnostics and management.