Antlers are the fastest-growing osseous tissue in mammals, undergoing periodic regeneration associated with the mating season. Their high strength and resistance to fracture have made them a valuable material for the manufacture of hunting tools, artifacts, furniture, and traditional medicines. The growing demand for antlers and derived products has fueled illegal trade, contributing to a significant decline in deer populations. Therefore, the present study aims to identify and differentiate antler samples from three deer species (spotted deer, sambar deer, and swamp deer) using ATR-FTIR spectroscopy coupled with chemometrics. Initial visual comparison of antler spectra failed to distinguish species due to their similar chemical compositions. However, the PCA model achieved partial separation with an accuracy of 93.33%, limited by some spectral misclustering. To improve differentiation, a PLS-DA model was developed, which distinguished antler spectra with 100% accuracy. External validation and a blind test further confirmed the model's predictive performance, yielding 100% accuracy. The findings demonstrate that ATR-FTIR spectroscopy combined with PLS-DA provides a reliable and efficient approach for species-level identification of antler samples. This approach will offer a valuable tool for wildlife forensic investigations and assist law enforcement agencies in monitoring and curbing the illegal antler trade.
Sharma et al. (Mon,) studied this question.