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Detection of Organic Acids and pH of Fruit Vinegars Using Near-Infrared Spectroscopy and Multivariate Calibration

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Abstract

Near-infrared (NIR) spectroscopy was investigated to determine the acetic, tartaric, formic acids and pH of fruit vinegars. Optimal partial least squares (PLS) models were developed with different preprocessing. Simultaneously, the performance of least squares-support vector machine (LS-SVM) models was compared with three kinds of inputs, including wavelet transform (WT), latent variables, and effective wavelengths (EWs). The results indicated that all LS-SVM models outperformed PLS models. The optimal correlation coefficient (r), root mean square error of prediction and bias for validation set were 0.9997, 0.3534, and −0.0110 for acetic acid by WT-LS-SVM; 0.9985, 0.1906, and 0.0025 for tartaric acid by WT-LS-SVM; 0.9987, 0.1734, and 0.0012 for formic acid by EW-LS-SVM; and 0.9996, 0.0842, and 0.0012 for pH by WT-LS-SVM, respectively. The results indicated that NIR spectroscopy (7,800–4,000 cm−1) combined with LS-SVM could be utilized as a precision method for the determination of organic acids and pH of fruit vinegars.

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Acknowledgments

This study was supported by the National Science and Technology Support Program (2006BAD10A09), the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE, P. R. C., and Natural Science Foundation of China (project no. 30671213).

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Authors and Affiliations

  1. College of Biosystems Engineering and Food Science, Zhejiang University, 268 Kaixuan Road, Hangzhou, Zhejiang, 310029, People’s Republic of China

    Fei Liu, Yong He, Li Wang & Guangming Sun

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  1. Fei Liu
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  2. Yong He
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  3. Li Wang
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  4. Guangming Sun
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Correspondence to Yong He.

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Liu, F., He, Y., Wang, L. et al. Detection of Organic Acids and pH of Fruit Vinegars Using Near-Infrared Spectroscopy and Multivariate Calibration. Food Bioprocess Technol 4, 1331–1340 (2011). https://doi.org/10.1007/s11947-009-0240-9

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