Bjarnestad Sofia, Dahlman Olof
Swedish Pulp and Paper Research Institute, P.O. Box 5604, SE, 114 86 Stockholm, Sweden.
Anal Chem. 2002 Nov 15;74(22):5851-8. doi: 10.1021/ac025926z.
In the present study, hardwood and softwood pulps were characterized by employing Fourier transform infrared photoacoustic spectroscopy (FT-IR-PAS). The pulp samples examined originated from Swedish sulfite and kraft pulp mills, which utilize different cooking processes and modern bleaching technologies. Partial least-squares (PLS) analysis was used to correlate the spectral data obtained with the kappa (K) numbers and carbohydrate compositions of the pulp samples determined by enzymatic hydrolysis and subsequent capillary zone electrophoresis. Using four principal components, the present PLS model based on photoacoustic FT-IR spectra could explain 85% of the variance in the X matrix and 81% of the variance in the Y matrix. The FT-IR-PAS technique in combination with PLS was found to accurately predict the contents of carbohydrates, i.e., xylose, glucose, mannose, arabinose, galactose, and hexenuronic acid residues, as well as the content of lignin measured in terms of K numbers and corrected K numbers of the pulps. From these predictions, the contents of xylan, glucomannan, and cellulose can also be predicted. The content of 4-O-methylglucuronic acid residues is, however, more difficult to predict accurately, using this approach.
在本研究中，采用傅里叶变换红外光声光谱法（FT-IR-PAS）对阔叶木浆和针叶木浆进行了表征。所检测的纸浆样品来自瑞典的亚硫酸盐法和硫酸盐法造纸厂，这些工厂采用不同的蒸煮工艺和现代漂白技术。使用偏最小二乘法（PLS）分析将获得的光谱数据与通过酶水解及随后的毛细管区带电泳测定的纸浆样品的卡伯值（K值）和碳水化合物组成相关联。基于光声傅里叶变换红外光谱，利用四个主成分，当前的PLS模型能够解释X矩阵中85%的方差以及Y矩阵中81%的方差。结果发现，FT-IR-PAS技术与PLS相结合能够准确预测碳水化合物的含量，即木糖、葡萄糖、甘露糖、阿拉伯糖、半乳糖和己糖醛酸残基的含量，以及根据纸浆的K值和校正K值测定的木质素含量。通过这些预测，还可以预测木聚糖、葡甘露聚糖和纤维素的含量。然而，采用这种方法准确预测4-O-甲基葡萄糖醛酸残基的含量则较为困难。
