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Visible and near infrared (Vis/NIR) spectroscopy was investigated to determine the acetic acid of plum vinegar based on three different calibration methods, including partial least squares analysis (PLS), multiple linear regression (MLR) and least squares-support vector machine (LS-SVM). Five concentration levels (100%, 80%, 60%, 40% and 20%) of plum vinegar were studied with 60 samples for each level. PLS was the calibration method as well as extraction method for latent variables (LVs). Simultaneously, five effective wavelengths (EW) were selected by regression coefficients. The LVs and EWs were employed as the inputs of MLR and LS-SVM models. The optimal prediction results were achieved by LV-LS-SVM model, and the correlation coefficient (r), root mean square error of prediction (RMSEP) and bias for validation set were 0.9994, 0.2361 and 0.0064, respectively. The results indicated that Vis/NIR spectroscopy combined with chemometrics could be utilized as a parsimonious and efficient way for the determination of acetic acid of plum vinegar.