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Micro-contextual identification of archaeological lipid biomarkers using resin-impregnated sediment slabs.

Authors :
Rodríguez de Vera, Caterina
Herrera-Herrera, Antonio V.
Jambrina-Enríquez, Margarita
Sossa-Ríos, Santiago
González-Urquijo, Jesús
Lazuen, Talia
Vanlandeghem, Marine
Alix, Claire
Monnier, Gilliane
Pajović, Goran
Tostevin, Gilbert
Mallol, Carolina
Source :
Scientific Reports; 11/25/2020, Vol. 10 Issue 1, pN.PAG-N.PAG, 1p
Publication Year :
2020

Abstract

Characterizing organic matter preserved in archaeological sediment is crucial to behavioral and paleoenvironmental investigations. This task becomes particularly challenging when considering microstratigraphic complexity. Most of the current analytical methods rely on loose sediment samples lacking spatial and temporal resolution at a microstratigraphic scale, adding uncertainty to the results. Here, we explore the potential of targeted molecular and isotopic biomarker analysis on polyester resin-impregnated sediment slabs from archaeological micromorphology, a technique that provides microstratigraphic control. We performed gas chromatography–mass spectrometry (GC–MS) and gas chromatography–isotope ratio mass spectromety (GC–IRMS) analyses on a set of samples including drill dust from resin-impregnated experimental and archaeological samples, loose samples from the same locations and resin control samples to assess the degree of interference of polyester resin in the GC–MS and Carbon-IRMS signals of different lipid fractions (n-alkanes, aromatics, n-ketones, alcohols, fatty acids and other high polarity lipids). The results show that biomarkers within the n-alkane, aromatic, n-ketone, and alcohol fractions can be identified. Further work is needed to expand the range of identifiable lipid biomarkers. This study represents the first micro-contextual approach to archaeological lipid biomarkers and contributes to the advance of archaeological science by adding a new method to obtain behavioral or paleoenvironmental proxies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20452322
Volume :
10
Issue :
1
Database :
Complementary Index
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
147203936
Full Text :
https://doi.org/10.1038/s41598-020-77257-x