Application of successive projections algorithm for variable selection to determine organic acids of plum vinegar

作者：Liu, Fei; He, Yong^*

来源：Food Chemistry, 2009, 115(4): 1430-1436.

DOI：10.1016/j.foodchem.2009.01.073

• Visible and near infrared spectroscopy
• Successive projections algorithm
• Variable selection
• Least squares-support vector machine
• Plum vinegar
• Organic acids

Visible and near infrared (Vis/NIR) spectroscopy was investigated to determine the acetic, tartaric and lactic acids of plum vinegar based on a newly proposed combination of successive projections algorithm-least squares-support vector machine (SPA-LS-SVM). SPA, compared with regression coefficients (RC), was applied to select effective wavelengths (EWs) with least collinearity and redundancies. Five concentration levels (100%, 80%. 60%, 40% and 20%) of plum vinegar were studied. Multiple linear regression (MLR) and partial least squares (PLS) models were developed for comparison. The results indicated that SPA-LS-SVM achieved the optimal performance for three acids comparing with full-spectrum PLS, SPA-MLR, SPA-PLS, RC-PLS and RC-LS-SVM. The root mean square error of prediction (RMSEP) was 0.3581, 0.0714 and 0.0201 for acetic, tartaric and lactic acids, respectively. The overall results indicated that Vis/NIR spectroscopy incorporated to SPA-LS-SVM could be applied as an alternative fast and accurate method for the determination of organic acids of plum vinegars.

• 出版日期2009-8-15
• 单位浙江大学