Hyperspectral reflectances of the healthy and lodged rice caused by rice planthopper and rice panicle blast were measured with visible/near-infrared (VIS/NIR) spectroradiometer at the canopy level. The principal component analysis (PCA) was used to obtain the principal components (PCs) and to reduce the spectral dimensions of hyperspectral reflec- tance. Two principal components were extracted. The first (PC1) and second (PC2) reveal the general feature of rice spectral reflectance and spectra change of lodged rice relative to healthy rice, respectively. The front two PCs entered the support vector classification (SVC) as the input vectors to build the discrimination model. The recognition accuracies of healthy and lodged rice are 100% and 90.9% for the rice planthopper and rice panicle blast stresses, respectively. The results demonstrate that visible/near-infrared spectroscopy technique may provide potential discrimination accuracy for lodged rice.