A nondestructive optical method for determining the internal quality of bayberry juice was investigated. Two types of preprocessing were used before the data were analyzed with multivariate calibration methods of PLS. Spectral data set as the logarithms of the reflectance reciprocal (absorbance (log1/R)) were analyzed to build a best model for predicting the SSC and acidity (pH) of bayberry juice. A model with a regression coefficient of 0.85, a standard error of prediction (SEP) of 0.40 g/100 ml and a bias of -0.14 for SSC and 0.92, 0.19 g/100 ml, -0.05 for acidity showed an excellent prediction performance. At the same time, the sensitive wavelengths corresponding to the SSC and acidity of bayberry juices or some element at a certain band were proposed on the basis of regression coefficients by PLS. The results show that using Vis/NIRS technique to fast and nondestructive detection the internal quality of bayberry juices was feasible. (c) 2006 Elsevier Ltd. All rights reserved.