关键词: 近红外光谱, 预测模型, 苯醇抽提物, 木质素

Abstract: Acacia is a kind of fast-growing wood pulp. The content of benzene alcohol extract has certain influence on pulp yield of wood. Near infrared spectra analysis can rapidly detect the contents of chemical components in wood with low cost. The multi-model method is a kind of near infrared spectra analysis modeling method, which has good prediction  and is easy to master.  The multi-model method has been applied to establish the near infrared spectral prediction model for detecting the contents of chemical components of acacia, populus tomentosa and populus euramericana, and better modeling effect is obtained. In the paper, the near infrared spectra analysis model for benzene alcohol extract of acacia contents and that of the Klason lignin of acacia  were built by multi-model method at first. The results showed that the effect for predicting the contents of Klason lignin was better than that of the benzene alcohol extract. While, based on the multi-model method, the near infrared spectra analysis model for the benzene alcohol extract content was built optimally by the help of Klason lignin, whose prediction error was smaller than that of the content of benzene alcohol extract. It improved the prediction effect of the content of the benzene alcohol extract. The  fit goodness of the model raised from 0.792 8 to 0.827 1. Different from the existing multi-model method，it was not required in this paper, when optimization modeling that the relationship between the contents of the 2 chemical components used to be approximately linear. For the prediction model of content of the benzene alcohol extract was built optimally, by reducing the number of undetermined constants in each sub model, the model stability was enhanced in the paper, and the prediction effect of this model was further improved. With the increase of research work in this area, this modeling method was hopeful for predicting the contents of chemical components, whose prediction effects were generic, and was also expected to improve the effects of near infrared spectral analysis on detecting these contents of chemical components.

Key words: near infrared spectroscopy, prediction model, Benzene alcohol extract, Lignin