Detection of Alternaria blight disease severity in mustard crops using ground-based hyperspectral remote sensing

Alternaria blight is a destructive disease of mustard crops that causes significant economic loss and usually warrants extensive pesticide application. Characterization and estimation of pest severity for better management is the need of the hour to increase the scope of advisories to the farmers. In this study, statistical approaches like multiple stepwise linear regression, principal component regression and partial least square regression have been employed to detect the disease severity of Alternaria blight in mustard leaves using hyperspectral reflectance data. The predicted values of diseased leaves in all the regression models were significantly reduced vis-à-vis healthy mustard leaves. The results of this study indicate that it is possible to detect the disease severity of Alternaria blight in mustard crops using hyperspectral reflectance data