Miyamae Yuta, Yamakawa Yumika, Ozaki Yukihiro
POLA Chemical Industries, Inc., Quality Design & Assurance R&D Department, 560 Kashio-cho, Totsuka-ku, Yokohama 244-0812, Japan.
Appl Spectrosc. 2007 Feb;61(2):212-7. doi: 10.1366/000370207779947503.
The objective of the present study is to develop a novel nondestructive, simple, and quick method to evaluate the friction, twist, and gloss of human hair based on near-infrared diffuse reflectance (NIR-DR) spectroscopy and chemometrics. NIR-DR spectra were measured for human hair, which was collected from eleven Japanese women (age 5-44 years), by use of an optical fiber probe. Partial least squares (PLS) regression has been applied to the NIR-DR spectra of human hair after mean centering (MC), standard normal variate (SNV), and first derivative (1d) or second derivative (2d) analysis to develop calibration models that predict the friction, twist, and gloss of human hair. We identified the most suitable wavenumber region for the evaluation of each physical property. Correlation coefficients and standard errors of calibration of the PLS calibration models for the friction, twist, and gloss of hair were calculated to be 0.96 and 0.023, 0.81 and 3.27, and 0.90 and 0.36, respectively. Thus, the calibration models have high accuracy.
本研究的目的是基于近红外漫反射(NIR-DR)光谱和化学计量学开发一种新颖的无损、简单且快速的方法,用于评估人发的摩擦、扭转和光泽度。使用光纤探头对从11名日本女性(年龄5 - 44岁)收集的人发测量NIR-DR光谱。在进行均值中心化(MC)、标准正态变量变换(SNV)以及一阶导数(1d)或二阶导数(2d)分析后,将偏最小二乘法(PLS)回归应用于人发的NIR-DR光谱,以建立预测人发摩擦、扭转和光泽度的校准模型。我们确定了评估每种物理性质最合适的波数区域。头发摩擦、扭转和光泽度的PLS校准模型的相关系数和校准标准误差分别计算为0.96和0.023、0.81和3.27、0.90和0.36。因此,校准模型具有较高的准确性。