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Abstract
We propose a novel, fast, reliable and non-destructive method based on Raman spectroscopy and chemometrics for the analysis and authentication of rocky meteorites. We use the spectral information obtained from rocky samples to discriminate between ordinary terrestrial rocks (with morphology and observable characteristics like meteorites) and authentic meteorites. Applying unsupervised statistical methods, such as Principal Component Analysis, we can discriminate between both samples. Main discriminator being the bands ascribed to hematite, which is present in all the terrestrial samples. A classification model for the authentication of meteorites is calibrated using supervised methods, such as partial least square regression under the discriminant analysis modality (PLS-DA). The calibrated model was able to correctly classify meteorites and ordinary rocks with sensitivity and specificity values of 93 % and 90 %, respectively.
References
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Copyright (c) 2026 Alejandro González-Sánchez, Cuauhtemoc Araujo-Andrade, Claudio Frausto-Reyes, Edgar Esparza-Ibarra, Alejandro Gutierrez Rodríguez