Palm-leaf manuscripts are cultural artifacts from South and Southeast Asia, yet diverse preparation methods and degradation histories complicate material characterization and comparison. We use a multimodal synchrotron approach combining small- and wide-angle X-ray scattering with X-ray fluorescence to extract structural and compositional descriptors from unprocessed leaves, writing supports, and manuscripts. Supervised learning evaluates differences related to genus, processing stage, and geographical origin. The processing stage is classified reliably, whereas genus separation is clearer in processed materials than in unprocessed leaves. Origin classification shows partial separability, with distinct regional profiles and overlaps reflecting shared preparation traditions, class imbalance, and botanical and degradation-related factors. Classification relies on multivariate combinations of crystallinity, fibril orientation, and elemental descriptors. This scalable, non-destructive framework supports comparison of collections and investigation of material similarities among traditions. The classifications represent comparative material profiles rather than definitive provenance assignments and must be combined with codicological and historical evidence.
Gallardo, L., Busch, M., Poliakova, A., Ciotti, G., Huber, P. (2026). Multimodal synchrotron X-ray analysis of palm-leaf manuscripts: structural and compositional signatures of botanical genus, manufacture, and provenance. NPJ HERITAGE SCIENCE, 14(1), 1-17 [10.1038/s40494-026-03023-3].
Multimodal synchrotron X-ray analysis of palm-leaf manuscripts: structural and compositional signatures of botanical genus, manufacture, and provenance
Ciotti, Giovanni;
2026
Abstract
Palm-leaf manuscripts are cultural artifacts from South and Southeast Asia, yet diverse preparation methods and degradation histories complicate material characterization and comparison. We use a multimodal synchrotron approach combining small- and wide-angle X-ray scattering with X-ray fluorescence to extract structural and compositional descriptors from unprocessed leaves, writing supports, and manuscripts. Supervised learning evaluates differences related to genus, processing stage, and geographical origin. The processing stage is classified reliably, whereas genus separation is clearer in processed materials than in unprocessed leaves. Origin classification shows partial separability, with distinct regional profiles and overlaps reflecting shared preparation traditions, class imbalance, and botanical and degradation-related factors. Classification relies on multivariate combinations of crystallinity, fibril orientation, and elemental descriptors. This scalable, non-destructive framework supports comparison of collections and investigation of material similarities among traditions. The classifications represent comparative material profiles rather than definitive provenance assignments and must be combined with codicological and historical evidence.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



