AbstractThe feasibility of using near-infrared spectroscopy (NIR) to identify wood species was investigated in this study. Case I considers the principal component analysis scores plot of NIR spectra for three wood species. Case II considers whether NIR combined with partial least squares discriminant analyses can be used to identify the three wood species. Three wood species were studied, and each species included five randomly collected wood blocks, 21 samples for each wood block, and 315 total wood samples. In case I, the samples in the PCA analysis were clustered together. In case II, samples in the training set were classified into the correct group, and the accuracy of the test set was up to 90%.