Abstract

The hemicellulose composition of a pulp significantly affects its chemical and physical properties and thus represents an important process control variable. However, complicated steps of sample preparation make standard methods for the carbohydrate analysis of pulp samples, such as high performance liquid chromatography (HPLC), expensive and time-consuming. In contrast, pulp analysis by attenuated total internal reflection Fourier transform infrared spectroscopy (ATR FT-IR) requires little sample preparation. Here we show that ATR FT-IR with discrete wavelet transform (DWT) and standard normal variate (SNV) spectral preprocessing offers a convenient means for the qualitative and quantitative analysis of hemicelluloses in bleached kraft pulp and alkaline treated kraft pulp. The pulp samples investigated include bleached softwood kraft pulps, bleached hardwood kraft pulps, and their mixtures, as obtained from Canadian industry mills or blended in a lab, and bleached kraft pulp samples treated with 0–6% NaOH solutions. In the principal component analysis (PCA) of these spectra, we find the potential both to differentiate all pulps on the basis of hemicellulose compositions and to distinguish bleached hardwood pulps by species. Partial least squares (PLS) multivariate analysis gives a 0.442 wt% root mean square errors of prediction (RMSEP) for the prediction of xylan content and 0.233 wt% RMSEP for the prediction of mannan content. These data all support the idea that ATR FT-IR has a great potential to rapidly and accurately predict the content of xylan and mannan for bleached kraft pulps (softwood, hardwood, and their mixtures) in industry. However, the prediction of xylan and mannan concentrations presented a difficulty for pulp samples with modified cellulose crystalline structure.

© 2016 The Author(s)

Rapid detection of cellulose and hemicellulose contents of corn stover based on near-infrared spectroscopy combined with chemometrics

Na Wang, Longwei Li, Jinming Liu, Jianfei Shi, Yang Lu, Bo Zhang, Yong Sun, and Wenzhe Li
Appl. Opt. 60(15) 4282-4290 (2021)

Evaluation of antibiotic effects on Pseudomonas aeruginosa biofilm using Raman spectroscopy and multivariate analysis

Gyeong Bok Jung, Seong Won Nam, Samjin Choi, Gi-Ja Lee, and Hun-Kuk Park
Biomed. Opt. Express 5(9) 3238-3251 (2014)

Multivariate quantitative analysis of metal elements in steel using laser-induced breakdown spectroscopy

Zhi Wang, Yanwu Chu, Feng Chen, Ziqian Sheng, and Lianbo Guo
Appl. Opt. 58(27) 7615-7620 (2019)

Sensitive and specific discrimination of pathogenic and nonpathogenic Escherichia coli using Raman spectroscopy—a comparison of two multivariate analysis techniques

Khozima Hamasha, Qassem I. Mohaidat, Russell A. Putnam, Ryan C. Woodman, Sunil Palchaudhuri, and Steven J. Rehse
Biomed. Opt. Express 4(4) 481-489 (2013)

Extraction of information from laser-induced breakdown spectroscopy spectral data by multivariate analysis

Nicole Labbé, Isabel Maya Swamidoss, Nicolas André, Madhavi Z. Martin, Timothy M. Young, and Timothy G. Rials
Appl. Opt. 47(31) G158-G165 (2008)