文献类型：期刊文献

中文题名：近红外光谱法快速测定速生相思的材性

英文题名：Rapid Prediction of Wood Property of Fast Growing Acacia by Near Infrared Spectroscopy Technique

作者：吴珽[1,2,3,4] 房桂干[1,2,3,4] 梁龙[1,2,3,4] 张新民[5] 赵振义[5]

第一作者：吴珽

机构：[1]中国林业科学研究院林产化学工业研究所;[2]生物质化学利用国家工程实验室;[3]国家林业局林产化学工程重点开放性实验室;[4]江苏省生物质能源与材料重点实验室;[5]华夏科创仪器有限公司

年份：2015

卷号：49

期号：5

起止页码：27-33

中文期刊名：生物质化学工程

外文期刊名：Biomass Chemical Engineering

收录：北大核心:【北大核心2014】；

基金：国家林业局948技术引进项目(2014-4-31)

语种：中文

中文关键词：近红外光谱法;偏最小二乘法;速生相思;化学成分;基本密度

外文关键词：near-infrared spectroscopy; partial least squares （PLS） ; fast growing acacia; chemical composition; basic density

分类号：TQ35;O657.3

摘要：为了实现制浆原料材性的快速测定,用常规方法测定了147个相思木材样品的化学成分和基本密度,并采集了样品的近红外光谱。对原始光谱进行预处理后,运用偏最小二乘法和交互验证的方法,建立样品综纤维素、木质素、苯醇抽出物、基本密度的校正模型,4个模型建立过程中所提取的最佳主成分数分别为10、8、9和9。对4种校正模型进行独立验证,得到其决定系数（R2val）分别为0.910 3、0.950 5、0.970 6和0.969 5;预测均方根误差（RMSEP）分别为0.45%、0.32%、0.21%和0.007 1 g/cm3;相对分析误差（RPD）值分别为3.34、4.50、5.82、5.73;绝对偏差（AD）分别为-0.60%～0.68%、-0.50%～0.48%、-0.29%～0.33%和-0.009 7～0.009 1 g/cm3,RMSEP和AD基本符合测定对误差的要求,4个模型能够满足制浆造纸工业中速生相思木材的快速测定。
The chemical compositions and basic densities of 147 fast growing acacia samples were analyzed by using the traditional method, and the near-infrared （NIR） spectra were also collected. Partial least squares （PLS） method and cross-validation were used to confirm the best factor and build the calibration models for holocellulose, lignin, benzene-alcohol extract and basic density after the original spectra were pretreated. The best factors of the four models were 10, 8, 9 and 9. The independent verification of the calibration models showed the coefficients of determinations （ R2 ） were 0. 910 3, 0. 950 5, 0. 970 6 and 0.969 5, respectively. The root mean square errors of prediction （RMSEP） were 0.45%, 0.32%, 0.21% and 0.007 1 g/cm3, respectively. The relative percentage deviations （ RPD ） were 3.34, 4.50, 5.82 and 5.73, respectively. And the absolute deviations （AD） were -0.60%-0.68%, -0.50%-0.48%, -0.29%-0.33% and -0.009 7-0.009 1 g/era3, respectively. The root mean square errors of prediction and the absolute deviations basically met the needs of error and the four calibration models could fulfil the rapid determination in pulping and paper making industry for the good predictive performance.