A fast and non-invasive method based on visible-near infrared reflectance spectroscopy was put forward for discriminating lines and authenticity of hybrid rice seed. Five different varieties of rice seed were analyzed using a FieldSpec?3 visible-near infrared spectrometer,and 32 samples were used for each variety of rice. All samples were divided randomly into two groups,one group with 125 samples used as calibrated set,and another with 35 samples used as validated set. The samples data were pretreated with the methods of S.Golay smoothing and standard normal variable (SNV),and then analyzed by principal component analysis (PCA). The anterior 9 principal components computed by PCA were used as the new variables,and analysised by Fuzzy pattern recognition,back-propagation artificial neural network (ANN-BP),Fisher multi-types linear discriminant and Bayes multi-types stepwise discriminant. Then,the 35 unknown samples in the validated set were predicted. Therefore,the feasibility of discriminating the lines and authenticity of hybrid rice seed in rapid and non-invasive way by visible-near spectra technology was proved,and PCA combined with Bayes multi-types stepwise discriminant was confirmed as a preference method.