Abstract

Plant diseases are the driving force for substantial losses to the agricultural industry all around the globe. There is sufficient information available regarding most of these pathogens and their nature of damage. But effective management of all these biotic stresses is still a great challenge to plant pathologists and farming community as accurate identification and diagnosis of plant diseases are not possible with the available conventional methods. Serological techniques like enzyme-linked immunosorbent assay (ELISA) and molecular methods such as polymerase chain reaction (PCR) brought a revolution in disease diagnosis and detection but it takes long time in terms of sample harvesting, processing and analysis. Simultaneously, it is not very reliable at the asymptomatic stage, especially in case of the pathogen with systemic infection. Keeping pace with these emerging challenges and requirement of advanced, reliable, sensitive and specific diagnosis tool, there is a strong need of innovative technology which may enable detection of early stage of disease development. Detection of plant disease through some automatic technique will be beneficial as it will reduce a work of monitoring in big farms. To meet the requirements, the technology like application of novel sensors based on host response, biosensors and remote sensing techniques coupled with spectroscopy-based methods, Image segmentation for detection in plant leaf diseases should be adapted. These techniques may produce successful and efficient detection of disease in primary infection stage. The biosensors and remote sensing technologies make the monitoring and forecasting more effective and easy. Hence, the application of these innovations may become an unbeatable tool for timely detection and diagnosis of the devastating pathogen and helps to generate effective management practices which are economical, ecofriendly and farmer-friendly crop protection tools.