摘要
用近红外光谱法对人工林杨木的苯醇抽提物质量分数进行了快速测定。用国家标准方法测定了42个杨木木材样品苯醇抽提物质量分数,并用近红外光谱仪(LabSpec Pro FR/A114260)测定相应的光谱。在350~2 500 nm、1 300~2 050 nm、2 050~2 500 nm 3个不同的光谱区域,采用未处理、Baseline、一阶导数、二阶导数等光谱的预处理方法,并采用PLS1、PLS2、PCR等3种不同的建模方法,建立了相应的校正模型与交互验证模型。结果表明:当光谱区域为2 050~2 500 nm、光谱数据进行一阶导数预处理、采用PLS1的建模方法、主成分数为7时,建立的校正模型预测效果最佳,校正模型的相关系数r=0.997 8、均方根误差为0.000 3、标准误差为0.000 3,验证模型r=0.736 0,均方根误差为0.006 1、标准误差为0.006 1;采用建立的模型对未参与建模的样本进行预测,其预测结果与实测结果之间的相关系数为0.918 6。
The benzene-ethanol extractive contents of 44 samples of poplar were determined by national standard of China, and then the near infrared (NIR) of all samples were collected by LabSpec Pro FR/Al14260. The calibration and validation model were built using PLS1, PLS2 and PCR with different pretreatment methods of un-pretreatment, baseline, the first derivative and the second derivative in different spectral region of 350-2 500 nm, 1 300-2 050 nm and 2 050-2 500 nm. The best model was built using PLS1 with the first derivative pretreatment of spectral data and seven principal components in 2 050-2 500 nm. The coefficients of correlation (r), the root mean square error and the standard error of calibration model are 0. 997 8, 0. 000 3 and 0. 000 3, respectively, and 0. 736 0, 0. 006 1 and 0. 006 1 for validation model, respectively. The correlation (r) is 0. 918 6 between the prediction and lab measuring values.
出处
《东北林业大学学报》
CAS
CSCD
北大核心
2013年第6期126-129,共4页
Journal of Northeast Forestry University
基金
中央高校基本科研业务费专项资金资助(DL10BB13)
关键词
杨木
近红外光谱
预处理
苯醇抽提物质量分数
预测
Poplar
Near infrared spectroscopy (NIR)
Pretreatment
Benzene-ethanol extractive content
Prediction.