Density measurements as a non-destructive approach to investigate the heat treatment of siliceous lithic artefacts

Santaniello, Fabio; Berloffa, Angela; Grimaldi, Stefano; Maffei, Simona; Pedrotti, Annaluisa; Gialanella, Stefano

doi:10.1016/j.culher.2020.10.004

Cited by 5 publications

(7 citation statements)

References 22 publications

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“…Agam and colleagues [28] apply UV Raman spectroscopy to determine the temperature at which archaeological specimens from Qesem Cave, Israel were heated. Santaniello et al [30] show that it is possible to identify heat-treated chert based on density measurements using an Archimedes balance and an experimental reference curve.…”

Section: Identifying Heat-treated Silcretementioning

confidence: 99%

Portable, non-destructive colorimetry and visible reflectance spectroscopy paired with machine learning can classify experimentally heat-treated silcrete from three South African sources

2022

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The objective of this study was to determine if visible reflectance spectroscopy and quantitative colorimetry represent viable approaches to classifying the heat treatment state of silcrete. Silcrete is a soil duricrust that has been used as toolstone since at least the Middle Stone Age. The ancient practice of heat treating silcrete prior to knapping is of considerable interest to paleolithic archaeologists because of its implications for early modern human complex cognition generally and the ability to manipulate the material properties of stone specifically. Here, we demonstrate that our quantitative, non-invasive, and portable approach to measuring color, used in conjunction with k-Nearest Neighbors “lazy” machine learning, is a highly promising method for heat treatment detection. Traditional, expert human analyst approaches typically rely upon subjective assessments of color and luster and comparison to experimental reference collections. This strongly visual method can prove quite accurate, but difficult to reproduce between different analysts. In this work, we measured percent reflectance for the visible spectrum (1018 variables) and standardized color values (CIEL*a*b*) in unheated and experimentally heat-treated silcrete specimens from three sources in South Africa. k-NN classification proved highly effective with both the spectroscopy and colorimetry data sets. An important innovation was using the heat treatment state predicted by the k-NN model for the majority of replicate observations of a single specimen to predict the heat treatment state for the specimen overall. When this majority voting approach was applied to the 746 individual observations in this study, associated with 94 discrete silcrete flakes, both spectroscopy and colorimetry k-NN models yielded 0% test set misclassification rates at the specimen level.

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Section: Identifying Heat-treated Silcretementioning

confidence: 99%

Portable, non-destructive colorimetry and visible reflectance spectroscopy paired with machine learning can classify experimentally heat-treated silcrete from three South African sources

2022

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“…The density values of the heated samples have been measured according to the same procedure described above. Density decreases with increasing heating temperature for all the geological samples (see Santaniello et al, 2021: 119). Consequently, mean values with standard deviation for each temperature have been measured (Table S3) for a comparison with the density values of archaeological samples here considered.…”

Section: Methodsmentioning

confidence: 87%

“…For the density measurements, we used as reference the values for the maiolica chert, discussed already in Santaniello et al, 2021. Geological samples were collected from six outcrops of maiolica (MN1, MN4, Veja1, Veja4, CIM9, S.MIC2, see relevant geological description in Barbieri et al, 2013) and then prepared by knapping.…”

Section: Methodsmentioning

confidence: 99%

“…A major contribution to the evaluation of the heat treatment of siliceous lithic materials comes from Fourier Transform Infra‐red (FT‐IR) spectroscopy (Schmidt et al, 2011, 2012; Schmidt, Léa, et al, 2013; Schmidt, Nash, et al, 2017; Schmidt, Porraz, et al, 2013; Schmidt, Spinelli Sanchez, & Kind, 2017; Weiner et al, 2015). The approach can be profitably strengthened when combined with other measurements, like scanning electron microscopy (SEM) observations (Santaniello et al, 2016), density (Santaniello et al 2021), and roughness tests (Bachellerie & Schmidt, 2022). The FT‐IR analyses are quite fast and easy to be conducted nondestructively.…”

Section: Introductionmentioning

confidence: 99%

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An integrated approach to reconstruct the role of the heat treatment within the reduction sequence of chert artefacts: The case of the early Neolithic site of Lugo di Grezzana (north‐eastern Italy)

et al. 2023

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The lithic assemblage from the well-known site of Lugo di Grezzana (Italy) attributable to the Fiorano group (5,300-4,900 BC cal) is analysed to shed new insights on the early Neolithic lithic technology in North-Eastern Italy. Techno-typological data are discussed allowing detailed reconstruction of the reduction sequence, thanks also to several refittings. A complex laminar production with several technical objectives has been identified. Whereas clues for the heat treatment of lithic materials have been identified, we verified it by a combined experimental approach. In the first place, we used density measurements, which already proved to be useful for prescreening analysis, to detect potentially heated artefacts. Afterward, we performed Fourier Transform Infrared (FT-IR) spectroscopy tests to assess the actual (de)hydration condition of the siliceous materials. Reflectance spectra have been acquired, analysing any item and avoiding any constraint related to both morphology and thickness of the sample. The archaeometric results, combined with the reduction sequence reconstruction, provide new indications on the technical capabilities and knowledge of the human groups that inhabited the region during the early Neolithic.

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“…The heating history of chert artefacts, without making statements on intentionality, can be investigated through physical and chemical approaches. Several analytical techniques have been developed to do this (e.g., Borradaile et al, 1993;Melcher & Zimmerman, 1977;Santaniello et al, 2021;Toyoda et al, 1993). Near infrared spectroscopy (NIR) is today the most often used method to investigate the heat treatment of artefacts (Bachellerie & Schmidt, 2020;Santaniello et al, 2015;Schmidt et al, 2013Schmidt et al, , 2017; for a similar related approach, see Weiner et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Recognizing heat‐treated chert: A comparison between infrared spectroscopy and fracture surface analysis

Bachellerie

Schmidt

2021

Archaeometry

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Heat treatment of lithic raw material is used for the first time in Europe in the Solutrean of the upper Paleolithic. The study of which heating technique was used by these groups requires analytical methods to understand and recognize the chemical and physical processes involved. Roughness measurements were tested as a tool for recognizing heat treatment and to compare them to infrared spectroscopy. We measure the surface topography of geological samples to observe its evolution as a function of heating and then compare the results with those obtained on Solutrean artefacts. We also measured ear infrared analyses was carried out for comparing the effectiveness of surface roughness measurements. This work complements our knowledge about the heating environment used by Solutrean groups by confirming the use of controlled heating. In addition, our roughness measurements provide promising results for the recognition of heat treatment through the quantification of the surface luster.

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Density measurements as a non-destructive approach to investigate the heat treatment of siliceous lithic artefacts

Cited by 5 publications

References 22 publications

Portable, non-destructive colorimetry and visible reflectance spectroscopy paired with machine learning can classify experimentally heat-treated silcrete from three South African sources

Portable, non-destructive colorimetry and visible reflectance spectroscopy paired with machine learning can classify experimentally heat-treated silcrete from three South African sources

An integrated approach to reconstruct the role of the heat treatment within the reduction sequence of chert artefacts: The case of the early Neolithic site of Lugo di Grezzana (north‐eastern Italy)

Recognizing heat‐treated chert: A comparison between infrared spectroscopy and fracture surface analysis

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