Evaluation of Physical Properties of Human Hair by Diffuse Reflectance Near-Infrared Spectroscopy

Abstract

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.