Classification of Tobacco Grades by Near-infrared Spectroscopy and PLS-DA

In order to rapidly classifying tobacco grades, the classification model of tobacco grades was established by partial least squares discrimination analysis (PLS-DA) with the near-infrared spectra of 150 tobacco samples collected from Qujing in Yunnan. The prediction were carried out on the 60 samples in the prediction set with the established model. The results indicated that:1) The prediction accuracies of training and prediction sets were 100.0% (150/150) and 96.7% (58/60), respectively; 2) PLS-DA was efficient in tobacco grade classifying. This model provides a new rapid discrimination analysis method for the classification of tobacco grades.