Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy

Abstract

This research addressed a rapid method to monitor hardwood chemical composition by applying Fourier transform infrared (FT-IR) spectroscopy, with particular interest in model performance for interpretation and prediction. Partial least squares (PLS) and principal components regression (PCR) were chosen as the primary models for comparison. Standard laboratory chemistry methods were employed on a mixed genus/species hardwood sample set to collect the original data. PLS was found to provide better predictive capability while PCR exhibited a more precise estimate of loading peaks and suggests that PCR is better for model interpretation of key underlying functional groups. Specifically, when PCR was utilized, an error in peak loading of ±15 cm−1 from the true mean was quantified. Application of the first derivative appeared to assist in improving both PCR and PLS loading precision. Research results identified the wavenumbers important in the prediction of extractives, lignin, cellulose, and hemicellulose and further demonstrated the utility in FT-IR for rapid monitoring of wood chemistry.

Predicting the chemical composition of juvenile and mature woods in Scots pine (Pinus sylvestris L.) using FTIR spectroscopy

“…Aside from the RMSEP, the most widely used statistics for evaluating the performance of predictive models are the standard error of prediction (SEP), which measures the precision of the predictions (i.e. the difference between repeated measurements); the ratio of performance to deviation (RPD), which is the ratio of the standard error in prediction to the standard deviation; and the bias, which is the average difference between the predicted and real values, indicating under-or overestimation (Acquah et al 2015;Chen et al 2010;Kutner et al 2005;Zhou et al 2015).…”

“…3 and S1, respectively), which follow nearly straight lines along the whole spectral region, confirm that raw spectra are suboptimal and that a suitable pre-processing procedure, conducted with the aim of making spectra compatible with one another, is desired when FTIR-based predictive models are constructed (see Conrad and Bonello 2016 for a review). For instance, a first derivative treatment (Owen 1995) substantially decreased RMSEP values across response variables in a study by Zhou et al (2015), in particular in extractives (from 1.19 to 0.34) and in lignin (from 1.05 to 0.50), with superior results reported by Acquah et al (2016b) as well. In the present case, the standardization accentuated differences in IR absorbance intensities among individuals at most wavenumbers for the four variables Lig, Cel, Hem and Ext in both juvenile and mature woods (Figs.…”

“…The great advantage of these techniques is that chemical composition needs to be determined only for a small subset of samples, while those of the remaining ones will be predicted from the corresponding IR or Raman spectral profiles. Principal component regression (PCR), soft independent modelling of class analogy (SIMCA) and partial least squares regression (PLSR) belong to the most widely employed statistical methods in this context (Cozzolino 2014;Zhou et al 2015).…”

Rapid Quantitative Analysis of Forest Biomass Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Regression

“…The tool has also been used to model the ash, volatile matter, fixed carbon, and higher heating value (HHV) of sweetgum, loblolly pine, and switchgrass torrefied at different temperatures [4]. For some studies on the raw biomass, FTIR spectroscopy was employed in characterizing several agricultural residues and their extractives content [5], in the qualitative analysis of lignin from five timber species [6], and in predicting the chemical composition of hardwoods [7]. FTIR-based models have also been employed for discriminant and classification analysis of biomass feedstocks and plant materials [8–12].…”

The Biofungicide Activity of Some Plant Essential Oils for the Cleaner Production of Model Linen Fibers Similar to Those Used in Ancient Egyptian Mummification

“…The assignment of OH stretching appeared at 3300-3400 cm −1 , which is characteristic of OH stretching in alcohols and phenols of cellulose, lignin, or hemicellulose [11,44,[51][52][53][54][55]. The band at 3423 cm −1 (-OH groups bending) in the spectrum of decayed and original samples became wider than the standard linen spectrum, and its peak shifted to a high wave, wherein hydroxyl groups on the backbone of the hemicelluloses were found.…”