近红外光谱技术快速识别针叶材和阔叶材的研究

对一种针叶材和一种阔叶材的横切面采集波长范围为780～2 500 nm的近红外漫反射光谱，结合偏最小二乘判别分析法(PLS-DA)对针叶材杉木和阔叶材桉树快速识别的可行性进行了研究，结果表明：(1)利用近红外光谱结合PLS-DA法建立的识别模型对建模样品的识别正确率达到100%，识别模型预测的分类变量值与实际值之间相关系数r达到0.99，SEC为0.07;(2)即使采用短波区域780～1 100 nm的近红外光谱也可以获得理想的识别结果(识别正确率为100%)，识别模型的r也达到0.99，SEC为0.07;(3)利用近红外光谱建立的识别模型对未知样本的识别正确率都为100%，说明近红外光谱技术可以快速、准确识别针叶材和阔叶材，这为木材识别提供了一种新方法和技术，也为开发低成本的近红外光谱识别仪器提供了科学依据。

Rapid Identification of Softwood and Hardwood by Near Infrared Spectroscopy of Cross-Sectional Surfaces

The feasibility of wood identification of softwood and hardwood by near infrared spectroscopy(NIR) coupled with partial least squares discriminant analysis(PLS-DA) was investigated in the present paper.The near infrared spectra(780~2 500 nm) were collected from wood cross-section from one softwood species(Chinese fir) and one hardwood species(eucalyptus).The results show that:(1) The identification accuracy of the calibration samples predicted by the model based on NIR coupled the PLS-DA was 100%.The correlation coefficient between the NIR predicted category variable value and the true value was 0.990,and the SEC was 0.071;(2) The identification accuracy by the model based on the spectra with 780~1 100 nm wavelengths also was 100%,and the correlation coefficient and SEC were 0.990 and 0.070,respectively;(3) The identification accuracy for the test samples was 100%.It was suggested that NIR can be used to rapidly and accurately identify softwood and hardwood samples.It also provides a new approach to identifying wood species.