Rapid drying-free determination of pure cashmere content in scoured cashmere using a novel method of NIR spectroscopy combined with moisture elimination and spectral reconstruction strategy

Abstract

Pure cashmere content (PCC) is a key parameter for assessing the quality of scoured cashmere. The traditional manual analytical method is quite laborious and time-consuming. A novel method has been developed by using near-infrared (NIR) spectroscopy combined with chemometrics and other mathematical methods. The accuracy of PCC calibration model, which is of great importance in practical application, remains a challenge due to the fact that the NIR diffuse reflectance spectra of scoured cashmere are badly influenced by absorbed moisture and light scattering. To improve the prediction accuracy, moisture elimination was first adopted to decrease the adverse effect of moisture on the spectra by subtracting the spectral contribution of water from the raw spectra. Spectral reconstruction was subsequently designed to take full advantage of the information contained in the residual values obtained after multiplicative scatter correction (MSC) pretreatment to retrieve the light scatter signal correlated with the physical properties of pure cashmere. Both the above two methods can improve the prediction performance of the partial least-squares regression (PLSR) model, and their combination can achieve the optimal model with root mean of square error of prediction (RMSEP) of 5.18 %, which satisfy the accuracy requirement for PCC measurement. The proposed method is rapid, low-cost, and environment-friendly for evaluating the quality of scoured cashmere fibers and shed light on the NIR-based analysis of the complex systems with valuable physical information.