THE APPLICATION OF PARTIAL LEAST SQUARE TO THE INVERSION OF SEVERITY OF WINTER WHEAT STRIPE RUST DISEASE

Abstract

Following the inoculation of stripe rust disease of different levels in the winter wheat field, thes measured the stripe rust disease severity and winter wheat canopy reflectance at different growth stages. PLS (Partial Least Square) was adopted to build a regression model for disease severity inversion from canopy reflectance. The results indicate that the inversion accuracy of PLS is higher than that of the method proposed in reference[4], which used PRI (Photochemical Reflectance Index) to predict disease severity. Regression coefficients of PLS were investigated to obtain useful knowledge. It has been found that the first derivatives on the two sides of the chlorophyll absorption valley (505～550 nm,640～670 nm,680～700 nm) are most important in determining disease severity. Diseased winter wheat has higher absolute values of first derivatives in the three spectral regions.