The analysis of genetic basis of breeding materials is the precondition for the improvement programs on populations and interesting traits in eucalypt. However, the traditional ways for that have high professional requirements and are time-consuming and laborsome. The aim of present study was to study the relationship between NIRs and genetic information of eucalypt, and discuss the practicability and the accuracy of the discriminant model for the classification of eucalypt hybrids by NIRs data. The NIRs of seven eucalypt hybrids and four parental pure species were scanned with healthy leaves using handheld portable near infrared spectrometer Phazir Rx (1624). 10 individuals were selected for a genotypic species, and 10 healthy current-year leaves were chosen per individual tree. Specially five scans for NIRs from each side of the middle part of the frontal vein of the leaves were taken, and estimated the average of that as the NIRs information of a leaf. In total, 100 NIRs were gained per genotypic species, 70 of which constitute the calibration set, and the validation set consists of the rest 30 NIRs. The transformation of S.G 2nd derivative were performed for the raw NIRs data in present study so as to eliminate the effects of baseline and other factors on the NIRs information, and to strengthen the characteristic peaks of NIRs. The later analysis were conducted after the pretreatment. Firstly, the relationship between NIRs and genetic information of eucalypt hybrids was studied by the scores plot of principal components (PCs) in principal component analysis (PCA), and on this basis, the NIRs discriminant model was developed. The soft independent modeling of class analogy (SIMCA) and partial least squares-discriminant analysis (PLS-DA) pattern recognition were used to classify eucalypt hybrids with the NIRs model calibrated. The coefficient variation curves of NIRs transformation showed that all phenotypic species studied had rich characteristic peaks, and big differences among them after the wavelength of 2000 nm. The scores plot of PC1 and PC2 in PCA demonstrated clear groups among parental species, hybrids, as well as between hybrids and their parents, suggesting NIRs was a direct response to the genetic information of different genotypes. The discriminant accuracy of SIMCA pattern recognition between some cross combinations, which shared close genetic relation of cross parents, were relatively low using NIRs model. In contrast, the discriminant accuracy of SIMCA pattern recognition among most of eucalypt combinations changed between 73% and 100%. The discriminant accuracy of PLS-DA pattern recognition using single and combined NIRs model of hybrids all were 100%, and the combined model of hybrids based on PLS-DA pattern can discriminate seven hybrids clearly. Studies showed that, the discriminant accuracy of PLS-DA pattern was much higher than that of SIMCA pattern recognition. The current study indicated that NIRs information is the correct response of different genotypic eucalypt species, and the NIRs calibrated model can classify different species of eucalypt accurately, so the NIRs would be used in the qualitative discrimination analysis of eucalypt hybrids and pure species in field, providing an alternative way for the analysis of genetic basis of breeding materials in eucalypt.