A technique for judging whether a common mineral was formed through biological activity could aid the search for ancient life on Earth and Mars. Apatite is a ubiquitous phosphate mineral found in terrestrial and extraterrestrial environments. It is a major component of teeth and bones, but it also occurs in igneous rocks and sedimentary phosphorites. Robert M. Hazen and colleagues developed a method to distinguish biologically formed apatite from abiotic apatite using Raman spectroscopy, an analytical technique incorporated into several recent Mars missions. Determining the origin of a sample involves assessing multiple independently varying features of a Raman spectrum, including band positions, widths, and relative intensities, the type of multivariate analysis well suited to machine learning. The authors compiled 331 Raman spectra of apatite from biotic and abiotic sources and trained a random forest classifier to identify the most diagnostic features. The intensity of the carbonate band and the width of the dominant phosphate band, reflecting chemical composition and crystal structure, respectively, emerged as the strongest indicators of origin. The resulting model distinguished biotic from abiotic apatite with classification accuracy exceeding 96%. According to the authors, minerals such as apatite can preserve evidence of biological activity over long geological timescales and the approach could thus help future planetary missions identify minerals that retain records of ancient life on rocky worlds.
PNAS Nexus
Mineral biosignature identification from Raman spectroscopy using machine learning
14-Jul-2026