利用近红外光谱进行羊绒与羊毛的鉴别技术研究

利用近红外光谱技术,以不同产地的羊绒、羊毛纤维为研究对象,结合主成分分析法和多元线性回归方法分别建立了羊绒、羊毛定性分析模型和羊绒-羊毛混纺纤维的定量分析模型.对模型的验证结果表明:定性分析模型能够准确地鉴别出羊绒与羊毛纤维;定量分析模型的相关系数和预测标准偏差分别达到了0.998 1和1.206 1,能够对羊绒-羊毛混纺纤维的含量进行准确的预测;近红外光谱技术用于羊绒、羊毛定性及定量分析具有可行性.

Study on Identification of Cashmere and Wool Using Near Infrared Spectroscopy

The fibers of cashmere and wool from different areas were studied via near infrared （NIR） spectroscopy technology, and during this process principal component analysis （PCA） and multiple linear regression （MLR） were used respectively to develop qualitative identification model and quantitative analysis model for cashmere and wool. The results of model validation indicated that the qualitative model could identify cashmere and wool accurately; and the quantitative model, which yielded correlation coefficient （ R2 ） = 0. 998 1 and standard error of prediction （SEP） = 1. 206 1, could predict the contents of cashmere-wool blend. The outcome proved that it was feasible to analyze cashmere and wool qualitatively and quantitatively via near infrared spectroscopy technology.