Development of a method for the determination of human skin moisture using a portable near-infrared system.

In this study, a portable near-infrared (NIR) system was newly integrated with a photodiode array detector that has no moving parts, and this system has been successfully applied for the evaluation of human skin moisture. The good correlation between NIR absorbance and the absolute water content of separated hairless mouse skin, in vitro, was showed, depending on the water content (7.4-84.9%) using this portable NIR system. Partial least squares (PLS) regression was used for calibration with the 1150-1650-nm wavelength range. For practical use for the evaluation of human skin moisture, the PLS model for human skin moisture was developed in vivo using the portable NIR system on the basis of the relative water content values of stratum corneum from the conventional capacitance method. The PLS model showed a good correlation. This study indicated that the portable NIR system, as compared to conventional methods, could be a powerful tool for human skin moisture, which may be much more stable to environmental conditions, such as temperature and humidity. Furthermore, to confirm the performance of the newly integrated portable NIR system, a scanning-type conventional NIR spectrometer was used in the same experiments, and the results were compared.

Near-infrared spectroscopy as a convenient analytical method for alkyl polyglycosides.

Near infrared (NIR) spectroscopy is used for the rapid determination of decyl glucopyranoside (10G1) and alkyl polyglycoside (AG) mixtures having different alkyl chain length and the number of glucose unit in aqueous solution. NIR spectroscopy is a much simpler spectroscopic analysis method compared to three analytical methods for mixture of AGs such as thin layer chromatography (TLC), high performance liquid chromatography (HPLC), and photometry method. NIR spectra of AGs between 0.030 and 0.540 mg/ml in aqueous solutions were utilized to develop a calibration model. Both raw spectra and the second derivatives of AGs were tested for the best fit. The best calibration was built with second derivative spectra by using multiple linear regression (MLR). The standard error of calibration (SEC) and the standard error of prediction (SEP) were used for the evaluation of the model. The best calibration provides an SEP of 0.052 and 0.061 mg/ml for the prediction set of 10G1 and AG mixture, respectively.

Discrimination of herbal medicines according to geographical origin with near infrared reflectance spectroscopy and pattern recognition techniques.

Herbal medicines have an important role in clinical therapy in Asian countries such as Korea, Japan, and China. The objective of this study is to develop a nondestructive and accurate analytical method to discriminate herbal medicines according to geographical origin. Even though they are the same species, their qualities are different by growing conditions such as climate and soil. Near infrared (NIR) reflectance spectroscopy and a pattern recognition technique were applied for discrimination of herbal medicines according to geographical origin (Korea and China). Astragali Radix (AR), Ganoderma, and Smilacis Rhizoma (SR) were examined. It is shown that the representative NIR reflectance spectra in each group are different according to geographical origin after second derivatization to enhance spectral features. Also, the NIR reflectance spectra of Chinese and Korean samples were differentiated using principal component (PC) score plots. To establish the discrimination rule, Mahalanobis distance and discriminant analysis with PLS2 were utilized.