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用近红外光谱法对人工林杨木的木质素含量进行了快速测定,采用国家标准方法测定了42个杨木木材样品的酸不溶木质素含量,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1 300~2 050 nm,光谱数据未进行预处理,采用PLS2的建模方法,主成分数为10时,建立的校正模型预测效果最佳。校正模型的相关系数r=0.968 5,均方根误差为0.006 4,标准误差为0.006 6;验证模型的相关系数r=0.655 3,均方根误差为0.020 2,标准误差为0.020 5。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0.766 5。
The content of lignin in poplar wood was determined by near infrared spectroscopy (FTIR). The content of acid-insoluble lignin in 42 poplar wood samples was determined by the national standard method and was determined by near infrared spectroscopy (LabSpec Pro FR / A114260) The corresponding spectrum. Three different spectral regions of 350 ~ 2 500 nm, 1 300 ~ 2 050 nm and 2 050 ~ 2 500 nm were pretreated with the spectra of untreated, Baseline, first derivative, second derivative and so on. PLS1 , PLS2, PCR and other three different modeling methods, the establishment of the corresponding calibration model and interactive verification model. The results show that when the spectral region is 1 300 ~ 2 050 nm, the spectral data is not preprocessed, and the PLS2 modeling method is used. The principal component is 10, the calibration model established is the best. The correlation coefficient of the calibration model was 0.968 5, the root mean square error was 0.006 4, the standard error was 0.006 6, the correlation coefficient of the validation model was r = 0.655 3, the root mean square error was 0.020 2, and the standard error was 0.020 5. The established model was used to predict the non-participating samples, and the correlation coefficient between the predicted and measured data was 0.766 5.