Microspectrophotometric Analysis of Yellow Polyester Fiber Dye Loadings with Chemometric Techniques

Abstract

Microspectrophotometry is a quick, accurate, and reproducible method to compare colored fibers for forensic purposes. Applying chemometric techniques to spectroscopic data can provide valuable information, especially when looking at a complex dataset. In this study, background subtracted and normalized visible spectra from ten yellow polyester exemplars dyed with different concentrations of the same dye ranging from 0.1% to 3.5% (w/w), were analyzed by agglomerative hierarchical clustering (AHC), principal component analysis (PCA), and discriminant analysis (DA). Systematic changes in the wavelength of maximum absorption, peak shape and signal-to-background ratio were noted as dye loading increased. In general, classifying the samples into ten groups (one for each exemplar) had poor accuracy (i.e., 51%). However, classification was much more accurate (i.e., 96%) using three classes of fibers that were identified by AHC as having low (0.10–0.20 wt%), medium (0.40–0.75 wt%), and high (1.5–3.5 wt%) dye loadings. An external validation with additional fibers and data generated by independent analysts confirmed these findings. Lastly, it was also possible to discriminating pairs of exemplars with small differences in dye loadings as a simulation of questioned (Q) versus known (K) comparisons.