Analytical Sciences

A Near Infrared Spectroscopic Discrimination of Noodle Flours Using a Principal-Component Analysis Coupled with Chemical Information

Masanori KUMAGAI,*^,**  Kikuko KARUBE,* Tomoaki SATO,* Naganori OHISA,** Toshio AMANO,*** Ryoei KIKUCHI,* and Nobuaki OGAWA*

*Faculty of Engineering and Resource Science, Akita University, Tegata Gakuencho, Akita 010-8502, Japan
**Akita Research Institute of Food and Brewing, Arayamachi, Akita 010-1623, Japan
***OPT Research, Inc., Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan

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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