相思树酸溶木素含量近红外光谱分析的新方法

用迭代法分别建立了相思树样品的酸溶木素含量和克拉森木素含量近红外光谱分析模型。结果表明对克拉森木素含量的预测效果明显好于对酸溶木素含量的预测效果。不同于一般的近红外光谱分析建模方法，利用酸溶木素含量与克拉森木素含量之间的近似线性关系，结合多波长下的近红外光谱数据，用预测效果较好的克拉森木素含量帮助构建了预测效果欠佳的酸溶木素含量的二十个子预测模型。通过计算这些子模型预测值的加权平均值，最终得到了每个相思树样品酸溶木素含量的新预测值。新模型的预测误差明显小于用迭代法所建模型的预测误差。文中建模方法有望用于某些用通常方法预测效果欠佳的化学成分含量，使它们的近红外光谱分析效果得到改善。

New Method of Near Infrared Spectra Analysis for the Content of Acid Soluble Lignin of Acacia

The near infrared spectra analysis model of the content of the acid soluble lignin and the model of the content of the Klason lignin were built by the iterative method separately at first. The results show that the prediction effect of the content of the Klason lignin is obviously better than that of the acid soluble lignin. Different from usual methods of building near infrared spectra analysis model, the approximate linear relation between the contents of the acid soluble lignin and the contents of the Klason lignin was used. Combined with the near infrared spectroscopy data of multi-wavelength, twenty sub models of prediction of the content of the acid soluble lignin were built with the help of the Klason lignin content whose prediction effect is better than that of the acid soluble lignin. By calculating the weighted mean value of the prediction values of these sub models, the new prediction value of the content of the acid soluble lignin of each acacia specimen was obtained at last. The prediction error of the new model is obviously less than that of the model built by the iterative method. It is possible that the method of modeling in the paper can be used to some chemical component contents when the predictions of them by usual methods are not very effective, and the effects of the near infrared spectra analysis of them will be improved.