基于近红外光谱法的人工林杨木木质素含量预测

Prediction of lignin content of plantation poplar using near infrared spectroscopy method

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（LabSpecProFR／A114260）测定相应的光谱。在350～2500nm、1300～2050nm、2050—2500nm3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PLSl、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l300～2050nm，光谱数据未进行预处理，采用PLS2的建模方法，主成分数为lO时，建立的校正模型预测效果最佳。校正模型的相关系数r=0．9685，均方根误差为0．0064，标准误差为0．0066；验证模型的相关系数r=0．6553，均方根误差为0．0202，标准误差为0．0205。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0．7665。

The lignin contents of plantation poplar were estimated using the method of the near infrared. The lignin con- tents of 42 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/A114260 in this paper. The calibration and validation model were built using PLS1, PLS2 and PCR with different pretreatment methods of no-pretreatment. Baseline, the first derivative and the sec- ond derivative in different spectral region of 350 - 2 500 nm, 1 300 - 2 050 nm and 2 050 - 2 500 nm. The result shows that the model is the best using PLS2 with no-pretreated of spectral data and 10 principal components in 1 300 - 2 050 rim. The coefficients of correlation （r）, the root mean square error and the standard error of calibration model are O. 968 5, 0. 006 4 and 0. 006 6, respectively, and O. 655 3,0. 020 2 and 0. 020 5 for validation model. The correlation （r） is 0. 766 5 between the prediction and lab measuring values of the samples without involved in modeling.