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  • Title: A near infrared spectroscopic discrimination of noodle flours using a principal-component analysis coupled with chemical information.
    Author: Kumagai M, Karube K, Sato T, Ohisa N, Amano T, Kikuchi R, Ogawa N.
    Journal: Anal Sci; 2002 Oct; 18(10):1145-50. PubMed ID: 12400663.
    Abstract:
    Using a portable near infrared (NIR) spectrometer, we discriminated flours for making Japanese noodles (Soba), not only relying on a statistical and mathematical approach, but also on a chemical interpretation of the NIR spectra. In original NIR spectra, the particle-size difference, which results in an undesired systematic variation, was extracted and interpreted as the first-principal component factor by a principal-component analysis. The discrimination of flour materials cannot be satisfied by this factor. However, after a standardized treatment for the original spectra, the particle-size effects were eliminated; alternatively, differences in the chemical contents were extracted as principal-component factors. Using these factors, flour material discrimination was achieved much better. This study suggests a novel idea of utilizing the wavelength contribution ratio spectra for interpreting the factors extracted from the principal-component analysis for the NIR spectra. This report also describes the relationship between the NIR spectra and the chemical-analysis data.
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