Journal of Agrometeorology (Aug 2022)

Assessing rice blast disease severity through hyperspectral remote sensing

  • NANDITA MANDAL,
  • DEB K. DAS,
  • RABI N. SAHOO,
  • SUJAN ADAK,
  • A. KUMAR,
  • C. VISWANATHAN,
  • J. MUKHERJEE ,
  • H. RAJASHEKARA,
  • RAJEEV RANJAN,
  • B. DAS

DOI
https://doi.org/10.54386/jam.v24i3.1587
Journal volume & issue
Vol. 24, no. 3

Abstract

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Remote sensing is being increasingly used in stress management in different agricultural practices. It is useful for real time analysis for crop stress which is not possible for visual observation alone. Rice blast caused by fungus Pyricularia Oryzae is a serious constrain in rice production in India. There is hardly any basic information available for spectral characteristics of rice blast disease for its real-time detection and management. Present study is to characterize spectral reflectance of blast affected rice in order to identify the sensitive spectral range. Disease severity of 10 different genotypes of rice was graded 0 to 9 based on the extent of host organ covered by symptom or lesion. Result shows that severely infected plant (score 9) have higher reflectance at visible region and lower reflectance at NIR region. Change in the reflectance for the infected plant as compare to the healthy plant was more pronounced in the VNIR, 550 to 760 nm and 1140 and 1300 nm having correlation coefficient above 0.6. The study of change in the reflectance with the change in wavelength (1st derivative) revealed that VNIR region have high correlation with the disease severity. Maximum rate of change value at red edge position (REP) is called as red edge value (REV) which has good relation with disease severity levels. Amplitude of the red edge peak decreases with the increase in severity levels. Amplitude of score 0 and 9 was 0.00929 and 0.002301, respectively for upland land condition whereas the amplitude of the score 0 and 9 was 0.010421 and 0.00193, respectively for upland land rice. This study identifies that VNIR and red edge region are sensitive for detecting rice blast, which could be utilized to aerial or satellite based monitoring blast affected rice cropping region.

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