• DocumentCode
    2620613
  • Title

    Comparison and Determination of Acetic Acid of Plum Vinegar Using Visible/Near Infrared Spectroscopy and Multivariate Calibration

  • Author

    Wang, Zunyi ; Liu, Fei ; He, Yong

  • Author_Institution
    Zhejiang Wanli Univ., Ningbo, China
  • Volume
    7
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    201
  • Lastpage
    204
  • Abstract
    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.
  • Keywords
    calibration; infrared spectra; organic compounds; support vector machines; visible spectra; acetic acid; calibration method; chemometrics; effective wavelengths; extraction method; latent variables; least squares-support vector machine; multiple linear regression; near infrared spectroscopy; partial least square analysis; plum vinegar; root mean square error; visible spectroscopy; Aging; Calibration; Chemical analysis; Food industry; Infrared spectra; Least squares methods; Linear regression; Root mean square; Spectroscopy; Vectors; acetic acid; least squares-support vector machine; vinegar; visible and near infrared spectroscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.728
  • Filename
    5170309