研究目的
To test the capacity of confocal microscopy and quantitative texture analysis for correctly grouping experimental tools used for working eight types of materials: bone, antler, wood, fresh hide, dry hide, wild cereals, domestic cereals, and reeds, and to demonstrate its potential for identifying worked materials in prehistoric tool analysis.
研究成果
Confocal microscopy and quantitative texture analysis can consistently identify tools used for working different materials (bone, antler, wood, hide, domestic cereals, wild cereals/reeds) with good accuracy, demonstrating a significant advance in use-wear analysis. The method shows promise for improving precision in archaeological functional studies but requires further research to address limitations such as polish development stages and material humidity effects.
研究不足
The method requires well-developed polishes (covering >90% of the surface), limiting analysis to advanced wear stages. Discrimination between fresh and dry hide, and between wild cereals and reeds, was poor due to overlapping textures. The study did not account for less developed polishes or post-depositional alterations. Results may be influenced by the humidity state of materials (e.g., soaked antler vs. fresh bone), and the small sample size (50 × 50 μm areas) for some materials like bone. Not applicable to all rock types beyond fine-grained flint.
1：Experimental Design and Method Selection:
The study used confocal microscopy to quantitatively analyze use-wear micropolish on experimental lithic tools. A quadratic discriminant function analysis was employed to build a predictive model for group membership based on texture parameters.
2：Sample Selection and Data Sources:
Thirty experimental tools were used, made from fine-grained flint (Barrika, Trevi?o, Charente sources), worked on eight materials (wood, bone, antler, fresh hide, dry hide, domestic cereal, wild cereal, reeds). Tools were cleaned with soapy water or mild chemicals to remove residues.
3：List of Experimental Equipment and Materials:
Sensofar Plu Neox white-light scanning confocal microscope with a ×20 objective, Mountain 7 software from Digital Surf for data processing, and various flint tools.
4：Experimental Procedures and Operational Workflow:
Six areas of 650 × 500 μm were measured per tool using confocal microscopy, with samples of 50 × 50 μm selected for analysis. Surfaces were leveled and filtered to isolate texture from background noise. Texture parameters (e.g., Sq, Sz, Sp, Sv, Sal, Str, Sdq, Sds, S5p, Spc, Spd, Sdc, Sbi, Sci, Svi, MDF, MDenF) were measured.
5：Data Analysis Methods:
Quadratic discriminant function analysis was used to classify samples into material groups, with outliers removed and missing values replaced by group means. Classification success was evaluated based on sample proportions.
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