• Title of article

    Short-wave near-infrared spectroscopy analysis of major compounds in milk powder and wavelength assignment Original Research Article

  • Author/Authors

    Di Wu، نويسنده , , Yong He، نويسنده , , Shuijuan Feng، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2008
  • Pages
    11
  • From page
    232
  • To page
    242
  • Abstract
    In this study, short-wave near-infrared (NIR) spectroscopy at 800–1050 nm region was investigated for the analysis of main compounds in milk powder. Through quantitative analysis, the feasibility is further demonstrated for the simultaneous measurement of fat, proteins and carbohydrate in milk powder. Two models, partial least-squares and least-squares support vector machine, were compared and utilized for regression coefficients and loading weights. The affect of standard normal variate spectral pretreatment to model performance was evaluated. Based on the resulted coefficients and loading weights, interesting wavelength regions of nutrition in milk powder are screened and the assignment of all specific wavelengths is firstly proposed in the details associated with chemical base. Instead of the whole short-wave NIR spectral data, these assigned wavelengths which can be reliably exploited were used for the content determination. Compared with other spectroscopy technique, assigned short-wave NIR spectral wavelengths did a good work. Determination coefficients for prediction are 0.981, 0.984, and 0.982, respectively for three components. The proposed wavelength assignment in the short-wave NIR region could be used for the component contents determination of milk powder, and could be as a guidance to interpret the spectra of milk powder.
  • Keywords
    Partial least-squares (PLS) , Short-wave near-infrared spectroscopy (short-wave NIRS) , Least-squares support vector machine (LS-SVM) , Wavelength assignment , Milk powder
  • Journal title
    Analytica Chimica Acta
  • Serial Year
    2008
  • Journal title
    Analytica Chimica Acta
  • Record number

    1031473