Pattern Recognition of Vis/NIR Spectroscopy from White Vinegar Based on PLS and BP-ANN Model

Visible/near infrared (Vis/NIR) transmittance spectroscopy was employed in discriminating white vinegar varieties. White vinegar samples were scanned in the Vis/NIR monochromatic instrument in transmission. It could get the scores of principal components (PCs) from original spectrum using partial least squares (PLS), the first 6 PCs picked according to the cumulative contribution rates would be taken as the inputs of back-propagation artificial neural network (BP-ANN), 240 samples from three varieties were used to build the model. Then this model was used to predict the varieties of 80 unknown samples and 97.5% resolving capability was achieved. It is indicated that Vis/NIR transmittance spectroscopy combined with PLS and BP-ANN is an effective measure to discriminate varieties of white vinegar.