Scientific Reports (May 2022)

Spatial distribution and identification of potential risk regions to rice blast disease in different rice ecosystems of Karnataka

  • Chittaragi Amoghavarsha,
  • Devanna Pramesh,
  • Shankarappa Sridhara,
  • Balanagouda Patil,
  • Sandip Shil,
  • Ganesha R. Naik,
  • Manjunath K. Naik,
  • Shadi Shokralla,
  • Ahmed M. El-Sabrout,
  • Eman A. Mahmoud,
  • Hosam O. Elansary,
  • Anusha Nayak,
  • Muthukapalli K. Prasannakumar

DOI
https://doi.org/10.1038/s41598-022-11453-9
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 14

Abstract

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Abstract Rice is a globally important crop and highly vulnerable to rice blast disease (RBD). We studied the spatial distribution of RBD by considering the 2-year exploratory data from 120 sampling sites over varied rice ecosystems of Karnataka, India. Point pattern and surface interpolation analyses were performed to identify the spatial distribution of RBD. The spatial clusters of RBD were generated by spatial autocorrelation and Ripley’s K function. Further, inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) approaches were utilized to generate spatial maps by predicting the values at unvisited locations using neighboring observations. Hierarchical cluster analysis using the average linkage method identified two main clusters of RBD severity. From the Local Moran’s I, most of the districts were clustered together (at I > 0), except the coastal and interior districts (at I 0.05), while Tungabhadra and Kaveri ecosystem districts were clustered together at p < 0.05. From the kriging, Hilly ecosystem, middle and southern parts of Karnataka were found vulnerable to RBD. This is the first intensive study in India on understanding the spatial distribution of RBD using geostatistical approaches, and the findings from this study help in setting up ecosystem-specific management strategies against RBD.