USE OF NEAR-INFRARED REFLECTANCE SPECTROMETRY AND MULTIVARIATE DATA-ANALYSIS TO DETECT ANTHER SMUT DISEASE (MICROBOTRYUM-VIOLACEUM) IN SILENE-DIOICA

Near-infrared reflectance (NIR) spectral data was used in principal co mponent analysis (PCA) to detect infection of Silene dioica by Microbo tryum violaceum. Rosette leaf samples were accurately identified as ei ther healthy (97%) or infected (96%) when NIR data was analyzed by PCA . The two classes overlapped slightly when principal component models were used to classify unknown samples. A method to measure the degree of infection is also presented. The use of NIR and PCA for both detect ion and quantification of fungal biomass in plant material should be u seful for studying plant-pathogen interactions and as a method for ass essing disease incidence in crops.