GIS-based survey and molecular detection of bacterial blight of soybean in sub-Himalayan ranges of Uttarakhand, India

• Published in: Tropical plant pathology Vol. 48; no. 3; pp. 332 - 346
• Main Authors: Surbhi, Kumari, Singh, K. P., Aravind, T., Bhatt, Pooja, Jeena, Himani, Rakhonde, Gaurav
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.06.2023; Springer Nature B.V
• Subjects: Bacteria; Biomedical and Life Sciences; Blight; Disease; Epidemiology; Geographic information systems; Life Sciences; Original Article; Pathogens; Plant Pathology; Remote sensing; Soybeans; Uttarakhand India; India; Polymerase chain reaction; Bacteria; Soybean; Geographic information system; Molecular identification
• ISSN: 1983-2052; 1982-5676; 1983-2052
• DOI: 10.1007/s40858-023-00568-7

Bacterial blight of soybean is one of the most damaging diseases, which renders the crop unproductive and deteriorates the seed quality. Timely detection and precise diagnosis of the pathogen is critical for predicting disease outbreaks. Geographic information systems (GIS) unfold new dimensions towards improving the speed and accuracy of disease assessment. The use of molecular markers is another important key to the early detection of pathogens from plant samples and is more reliable than conventional detection procedures. The present study was conducted in 11 districts in the sub-Himalayan ranges of Uttarakhand, India, with the aim of mapping the locations with prevalence of bacterial blight of soybean during 2019–2021. The disease was found to be more prevalent in hilly region of Kumaon as compared to Garhwal with a mean incidence of 12.57 percent and 9.0 percent, respectively. Highest mean incidence (15.33%) and severity (13.03%) of the disease were observed in district Udham Singh Nagar, Champawat, and Pithoragarh during 2019, 2020, and 2021. Lowest incidence (< 5%) was observed in Rudraprayag, Tehri, and Dehradun. Three molecular markers were used for detection of the causal agent of blight disease, Pseudomonas savastanoi pv. glycinea. All the markers used in the study provided positive results for identifying the pathogen and can prove useful for early detection in areas marked with high incidence by GIS. The results are of significant importance from the epidemiological aspect as the early detection of pathogens allows ample time for planning effective management strategies for the disease.