Hollowness in white radishes was detected by hyperspectral imaging. Three illumination patterns were used and compared. Important wavelengths were determined by the successive projections algorithm. PLS-DA and back propagation neural networks were used for classifying hollowness. Satisfactory classification accuracy was acquired using semi-transmittance mode.