2017
DOI: 10.1016/j.jasrep.2017.01.040
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Chemical paste characterization of Late Middle Preclassic-period ceramics from Holtun, Guatemala and its implications for production and exchange

Abstract: This study uses type: variety-mode classification, digital stereomicroscopy, and Neutron Activation Analysis (NAA) to characterize the paste composition of Late Middle Preclassic-period pottery at the site of Holtun, Guatemala. The sample consists of 98 sherds including unslipped utilitarian ware, slipped serving ware, and Mars Orange fine paste serving ware. NAA reveals four paste composition groups that approximate types produced through type: variety-mode classification and paste groups recognized by digita… Show more

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Cited by 5 publications
(12 citation statements)
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“…Comparison to the MURR database indicates a compositional similarity to ceramics collected from the Petén Lakes region of Guatemala and Middle Preclassic Mars Orange ceramics from Holtun, Guatemala (see Callaghan et al . 2017a & b, 2018).…”
Section: Resultsmentioning
confidence: 99%
“…Comparison to the MURR database indicates a compositional similarity to ceramics collected from the Petén Lakes region of Guatemala and Middle Preclassic Mars Orange ceramics from Holtun, Guatemala (see Callaghan et al . 2017a & b, 2018).…”
Section: Resultsmentioning
confidence: 99%
“…The materials for this study consisted of 97 samples of archeological ceramics from eight contexts dating to the Late Middle Preclassic-period at the Maya site of Holtun, Guatemala [6]. The archeological site of Holtun is an intermediate sized civic-ceremonial center with documented occupation beginning in the Late Middle Preclassic through Terminal Classic periods (600 BCE – AD 900) [14], [17], [7], [8], [9].…”
Section: Experimental Design Materials and Methodsmentioning
confidence: 99%
“…The interpretation of compositional data obtained from the analysis of archeological materials is discussed in detail elsewhere (e.g., [1], [2], [3], [11], [13], [16]). The approach used to interpret chemical data for pottery involves hierarchical cluster analysis (HCA) and principal component analysis (PCA) to establish initial groupings within the sample (see [6] Fig. 6).…”
Section: Experimental Design Materials and Methodsmentioning
confidence: 99%
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