文献类型：期刊文献

中文题名：近红外光谱法快速测定速生桉木化学成分含量

英文题名：Rapid Prediction of Chemical Components in Fast-growing Eucalyptus by Near Infrared Spectroscopy

作者：吴珽[1,2,3,4] 房桂干[1,2,3,4] 梁龙[1,2,3,4] 崔宏辉[1,2,3,4] 邓拥军[1,2,3,4]

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]江苏省生物质能源与材料重点实验室;[3]国家林业局林产化学工程重点开放性实验室;[4]生物质化学利用国家工程实验室

年份：2015

卷号：32

期号：3

起止页码：51-56

中文期刊名：桉树科技

外文期刊名：Eucalypt Science & Technology

收录：CSTPCD

基金：国家林业局948项目"农林剩余物制机械浆节能和减量技术引进"(2014-4-31)

语种：中文

中文关键词：近红外光谱法;速生桉木;偏最小二乘法;化学成分

外文关键词：near-infrared spectroscopy technique; fast-growing Eucalyptus; partial least squares; chemical component

分类号：O657.3;TS721

摘要：用常规方法测定了104个速生桉木样品的综纤维素、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,确定最佳主成分数并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Rval2分别为0.906 7、0.903 3、0.950 4、0.957 0;预测均方根误差（RMSEP）分别为0.33%、0.50%、0.31%、0.17%;相对分析误差（RPD）值分别为3.22、3.20、4.43、4.73;绝对偏差（AD）分别为-0.53%-0.60%、-0.95%-0.77%、-0.55%-0.52%、-0.22%-0.29%,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速生桉木原料的需求。
A study was conducted to use the conventional method to analyze the content of holocellulose, pentosan, lignin and benzene-alcohol extractive content of 104 fast-growing Eucalyptus wood samples and the near-infrared （NIR） spectra were also collected. After the original spectra were subject to multiplicative scatter correction （MSC）, partial least squares （PLS） method and cross-validation were used to confirm the best factors. Based on those factors, calibration models for holocellulose, pentosan, lignin and benzene-alcohol extractive content were formulated. The independent verification showed the coefficient of determination （Rval^2） for the holocellulose, pentosan, lignin and benzene-alcohol models were 0.91, 0.90, 0.95 and 0.96 respectively. The root mean square errors of prediction （RMSEP） were 0.33%, 0.50%, 0.31% and 0.17% respectively. The relative percent deviations （RPD） were 3.22, 3.20, 4.43 and 4.73 respectively. And, the absolute deviations （AD） were -0.53% - 0.60%, -0.95% - 0.77%, -0.55% - 0.52% and -0.22% - 0.29% respectively. All the calibration models met the requirements for rapid determination of wood properties of Eucalyptus based on their good predictive performance.