Abstract

The combination of advanced techniques with multivariate analysis methods are being used with great confidence by forensics experts due to their high precision and accuracy. The prime objective of present work was to explore the potential of chemometric tools in discriminating and predicting the blue pen inks when applied on Attenuated total reflectance Fourier transform infrared (ATR-FTIR) data of pen strokes of different brands and models commercially available in Pakistani markets. The pen strokes on fine A4 paper and recycled A4 paper were obtained from 86 samples including ballpoints, gel, oil- gel and roller ball pens. ATR-FTIR spectra were first characterized for different functional groups present in ink pigments however, they were apparently indistinguishable having some common functional groups. After spectra preprocessing the principal component analysis (PCA) and agglomerative hierarchical cluster analysis (AHC) showed that pen strokes could be distinguished. Both PCA and AHC analyses showed that ballpoints and gel pen could be discriminated and grouped separately. PCA analyses also showed the discrimination between local and foreign brands of ballpoints. Finally, classification method partial least squares-discriminant analysis (PLS-DA) was successfully applied for the classification and subsequently for the identification of type of pen used in personnel’s signature to mimic a forensic case. To evaluate PLS-DA classification performance, the classification parameters such as sensitivity, specificity, accuracy and precision were also derived from confusion matrix. Overall, this work emphasized the worth of multivariate analysis in classification and prediction of type of writing pen in a document as a forensic study.

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