TY - JOUR
T1 - Setting the morphologic quality limits enabling accurate classification of charred archaeological grape seeds
AU - Landa, Vlad
AU - Shapira, Yekaterina
AU - Eliyahu-Behar, Adi
AU - Ben-Arie, Reut Levitan
AU - Weiss, Ehud
AU - Reuveni, Yuval
AU - Drori, Elyashiv
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/7/12
Y1 - 2024/7/12
N2 - This study investigates the morphological changes in grape pips resulting from various charring conditions. Employing high-resolution scanning combined with morphometric measurements for morphological analysis, we aimed to understand the effects of charring on grape pips. Our morphometric analysis demonstrated significant alterations in seed shape above 250 °C. The length–width ratio and the occurrence of cracks notably changed, providing a basis for assessing charring conditions. In addition, applying a machine learning classification method, we determined that accurate classification of grape varieties by the morphometric analysis method is feasible for seeds charred at up to 250 °C and 8 h. Integrating the morphometric changes and temperature ranges suitable for classification, we developed a sorting model for archaeological seeds. By projecting length–width ratios onto a curve calculated from controlled conditions, we estimated charring temperatures. Approximately 50% of archaeological seeds deviated from the model, indicating drastic charring conditions. This sorting model facilitates a stringent selection of seeds fit for classification, enhancing the accuracy of our machine learning-based methodology. In conclusion, combining machine learning with morphometric sorting enables the identification of charred grape seeds suitable for identification by the morphometric method. This comprehensive approach provides a valuable tool for future research for the identification of charred grape seeds found in archaeological contexts, enhancing our understanding of ancient viticulture practices and grape cultivation.
AB - This study investigates the morphological changes in grape pips resulting from various charring conditions. Employing high-resolution scanning combined with morphometric measurements for morphological analysis, we aimed to understand the effects of charring on grape pips. Our morphometric analysis demonstrated significant alterations in seed shape above 250 °C. The length–width ratio and the occurrence of cracks notably changed, providing a basis for assessing charring conditions. In addition, applying a machine learning classification method, we determined that accurate classification of grape varieties by the morphometric analysis method is feasible for seeds charred at up to 250 °C and 8 h. Integrating the morphometric changes and temperature ranges suitable for classification, we developed a sorting model for archaeological seeds. By projecting length–width ratios onto a curve calculated from controlled conditions, we estimated charring temperatures. Approximately 50% of archaeological seeds deviated from the model, indicating drastic charring conditions. This sorting model facilitates a stringent selection of seeds fit for classification, enhancing the accuracy of our machine learning-based methodology. In conclusion, combining machine learning with morphometric sorting enables the identification of charred grape seeds suitable for identification by the morphometric method. This comprehensive approach provides a valuable tool for future research for the identification of charred grape seeds found in archaeological contexts, enhancing our understanding of ancient viticulture practices and grape cultivation.
KW - Archaeobotanical remains
KW - Grapevine
KW - Machine learning
KW - Morphometric analysis
UR - http://www.scopus.com/inward/record.url?scp=85198351008&partnerID=8YFLogxK
U2 - 10.1038/s41598-024-66896-z
DO - 10.1038/s41598-024-66896-z
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C2 - 38997329
AN - SCOPUS:85198351008
SN - 2045-2322
VL - 14
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 16148
ER -