DOI: https://doi.org/10.55373/mjchem.v27i4.117

Keywords: Spectroscopy; leather; chemometric; principal component analysis

Abstract

This study presents a novel approach for leather classification utilizing Fourier Transform Infrared (FTIR) spectroscopy coupled with an unsupervised chemometric technique. The effectiveness of FTIR in capturing the chemical profiles of various leather types was investigated, and principal component analysis (PCA) was applied to categorize these profiles. Animal leather samples, specifically cow, buffalo, goat, and pig skin, were compared with polyurethane. All samples were analysed by FTIR without any pre-treatment, followed by a principal component analysis (PCA). The combination of FTIR spectral data and advanced multivariate techniques enabled precise differentiation among the leather samples, offering a robust method for quality control and authenticity verification in the leather industry. Our findings demonstrate that this integrated approach significantly enhanced the accuracy of leather classification, paving the way for improved materials analysis and classification standards.