Scaling up phytolith preparation protocols for big data
Dudgeon, Kate (Universitat Autònoma de Barcelona. Institut de Ciència i Tecnologia Ambientals)
Mejía Ramón, Andrés (Universitat Autònoma de Barcelona. Institut de Ciència i Tecnologia Ambientals)
Gregorio-Rocasolano Garcia, Pau de (Universitat Autònoma de Barcelona. Institut de Ciència i Tecnologia Ambientals)
Lombardo, Umberto (Universitat Autònoma de Barcelona. Departament de Prehistòria)

Date:	2026
Abstract:	Analytical procedures in phytolith analysis are transforming with the potential of AI to automate phytolith identification and classification, facilitating the analysis of unprecedented large datasets. Currently, phytolith extraction protocols are inadequate for processing the large numbers of samples it is becoming possible to analyse. Digital microscope scanners make it possible digitise phytolith slides at a high resolution with minimal human intervention to produce large datasets. However, standard phytolith slide manufacture procedures require modification to produce the best results in a fully automated process. This research optimises standard phytolith extraction workflows to process large numbers of samples and assesses the best methodology for phytolith slide mounting adapted to digital scanning. Human-labour time was reduced by up to 33% in variations of standard phytolith extraction protocols and the extract quantitatively assessed to ensure the optimisation steps did not compromise quality. Phytoliths mounted in Norland 165H and left for 24 h before setting were best suited for digital scanning, compared with four other mounting media and procedures commonly used in phytolith slide preparation. Phytolith extraction and slide mounting workflows have been optimised to handle large data sets suitable for digital scanning and are fundamental in the development of automated phytolith identification.
Grants:	European Commission 101043738 Ministerio de Ciencia, Innovación y Universidades CEX2024-001506-M Generalitat de Catalunya 2021/SGR-00527
Note:	Unidad de excelencia María de Maeztu CEX2024-001506-M
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Artificial intelligence ; Automation ; Digital scanning ; Extraction ; Phytoliths
Published in:	Journal of archaeological science, Vol. 191 (July 2026) , art. 106595, ISSN 1095-9238

DOI: 10.1016/j.jas.2026.106595

11 p, 5.7 MB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Experimental sciences > Institut de Ciència i Tecnologia Ambientals (ICTA)
Articles > Research articles
Articles > Published articles