Quantitative NIR spectroscopy for determination of degree of polymerisation of historical paper

Yun Liu, Tom Fearn, Matija Strlič
2021 Chemometrics and Intelligent Laboratory Systems  
This paper discusses the development of a near infrared (NIR) spectroscopic method coupled with multivariate analysis to characterise historical paper. Specifically, partial least squares (PLS) regression was used to predict one of the most important properties of paper as a condition indicatordegree of polymerisation (DP). Supported by a set of model cellulose samples, the NIR-PLS method for DP prediction was validated and the modelling approach that led to the best prediction of DP of paper
more » ... s established. The coefficient of variation of the NIR-PLS models were found to be approximately 8% and 20% of the DP of model cellulose and historical paper, respectively. The variance of the reference DP, the variance of the predicted DP, and the model bias were identified as the main sources of the total expected generalisation error of prediction. For both model cellulose and historical paper, the variance of the predicted DP by the NIR-PLS models contributed the most to the total error of prediction. This suggests that improving the instrumentation and the operation procedure is essential to improve model performance. Furthermore, the effect of water content of the samples on model performance was investigated. The model for historical paper was proven to be robust to relative humidity fluctuations between 30% and 70%, indicating the applicability of the model for collection surveys in a range of environments.
doi:10.1016/j.chemolab.2021.104337 fatcat:ovjy5mzhivdp5a7kq2kcs7hoce