%0 Journal Article
%T 近红外光谱法快速测定制浆材化学成分含量
%A 吴？E
%A 房桂干
%A 
%A 梁龙
%A 崔宏辉
%A 熊智新
%J 林业工程学报
%D 2016
%R 10.13360/j.issn.2096-1359.2016.02.014
%X 为实现制浆材化学成分含量的快速测定与实时分析,用常规方法测定了120个制浆材样品的综纤维素、聚戊糖、酸不溶木素及苯醇抽出物含量,并采集了样品的近红外光谱。对原始光谱进行多元散射校正后,运用偏最小二乘法和交互验证的方法,根据主成分数与PRESS值的关系,确定最佳主成分数分别为9,10,8,9,据此建立样品相关化学成分含量的校正模型。独立验证中综纤维素、聚戊糖、酸不溶木素和苯醇抽出物模型的决定系数R2val分别为0.918 8,0.949 3,0.946 6和0.928 4,预测均方根误差(RMSEP)分别为0.70%,0.75%,0.72%和0.24%,相对分析误差(RPD)值分别为3.50,4.44,4.33和3.74,绝对偏差(AD)分别为-0.95%～1.22%,-1.42%～1.29%,-1.39%～1.14%和-0.34%～0.39%,4个校正模型较好地预测了验证集样品的化学成分含量,基本满足制浆造纸工业中快速测定的需求。</br>In order to realize rapid determination and real-time analysis of chemical components contents in pulpwood, the content of holocellulose, polypentanose, acid-insoluble lignin and benzene-alcohol extractives in 120 pulpwood samples were analyzed by means of conventional methods, and their near-infrared(NIR)spectroscopy were collected. Based on the pretreatment of the original spectra by multipliplicative scatter correction(MSC), the factors were confirmed by means of partial least squares(PLS)method and cross-validation. On the basis of the relationship between factors and PRESS value, the four optimum factors were confirmed as 9, 10, 8, 9, respectively. According to the four optimum factors, calibration models for the content of holocellulose, polypentanose, acid-insoluble lignin and benzene-alcohol extractives were built. The independent verification showed that the coefficient of determination(R2val)of the holocellulose, polypentanose, acid-insoluble lignin and benzene-alcohol models were 0.918 8, 0.949 3, 0.946 6 and 0.928 4, respectively, and the root mean square error of prediction(RMSEP)were 0.70%, 0.75%, 0.72% and 0.24%, respectively. The relative percent deviation(RPD)were 3.50, 4.44, 4.33 and 3.74, respectively, and the absolute deviation(AD)were -0.95% to 1.22%, -1.42% to 1.29%, -1.39% to 1.14% and -0.34% to 0.39% respectively. All the calibration models basically meet the requirements of rapid determination in pulp and paper industry with their good predictive performance
%K 近红外光谱
%K 偏最小二乘法
%K 制浆材
%K 化学成分&lt
%K /br&gt
%K near-infrared spectroscopy
%K partial least squares(PLS)
%K pulpwood
%K chemical component
%U http://lkkf.njfu.edu.cn//oa/darticle.aspx?type=view&id=201602014