光谱预处理对近红外光谱预测木材纤维素结晶度的影响

Effects of Spectral Pretreatment on the Prediction of Crystallinity of Wood Cellulose Using Near Infrared Spectroscopy

木材纤维素结晶度是木质材料的一个重要性质,它与树木的生长特性、结构与化学组成均有密切关系,并对木材的杨氏模量、尺寸稳定性、密度和硬度等具有重要的影响,文章研究了利用近红外光谱结合多变量数据分析技术对人工林木材纤维素的结晶度进行预测的能力。本研究从人工林湿地松木粉试样的表面采集近红外漫反射光谱,并利用X射线衍射法测定了木材纤维素的结晶度。研究表明,采用一阶导数和二阶导数光谱预处理没有提高近红外模型的预测效果,而采用原始光谱的预测效果最好,预测值与X射线衍射测定值的相关系数r可以达到0.950,各项预测误差值较低,说明采用近红外光谱结合多变量数据分析方法建立的结晶度预测模型具有理想的预测能力。

The crystallinity of wood has an important effect on the physical, mechanical and chemical properties of cellulose fibers. The aims of this study were to investigate the ability of near infrared spectroscopy （NIR） to predict the crystallinity of wood cellulose and the effect of spectral pretreatment on the prediction of crystallinity in wood cellulose using near infrared spectroscopy （NIR）. Near infrared diffuse reflectance spectra were collected from wood powder with a fiber-optical probe and the crystallinity of wood was determined by X-ray diffractometer （XRD） in this experiment. The results showed that near infrared spectroscopy coupled with partial least square （PLS） regression could be correlated with the crystallinity of plantation wood, and the ability of NIR prediction based on original spectra was better than that based on the first derivative or second derivative treated spectra. There was a significant correlation between NIR spectra and XRD determined crystallinity with a correlation coefficient of 0. 950 and a low RMSEP. Near infrared spectroscopy coupled with multivariate data anlaysis has proven to be an accurate and fast method for rapid prediction of wood crystallinity.