Print Email Facebook Twitter Quantification of bone surface textures Title Quantification of bone surface textures: exploring a new method of ontogenetic ageing Author de Rooij, Jimmy (Naturalis Biodiversity Center) Vintges, M.Q. (Naturalis Biodiversity Center; Universiteit Leiden) Zuidwijk, T. (TU Delft ImPhys/Pereira group) Heerkens, C.T.H. (TU Delft ImPhys/Hoogenboom group) Schulp, Anne S. (Universiteit Utrecht; Naturalis Biodiversity Center) Date 2023 Abstract Identification of ontogenetic age classes plays an important role in the fields of zoology, palaeontology and archaeology, where accurate age classifications of (sub)fossil remains are a crucial component for the reconstruction of past life. Textural ageing—the identification of age-related bone surface textures—provides a size-independent method for age assessment of vertebrate material. However, most of the work so far is limited to qualitative results. While qualitative approaches provide helpful insights on textural ageing patterns, they are heavily subject to observer bias and fall short of quantitative data relevant for detailed statistical analyses and cross-comparisons. Here, we present a pilot study on the application of 3D surface digital microscopy to quantify bone surface textures on the long bones of the grey heron (Ardea cinerea) and the Canada goose (Branta canadensis) using internationally verified roughness parameters. Using a standardised measuring protocol, computed roughness values show a strong correlation with qualitative descriptions of textural patterns. Overall, higher roughness values correspond to increased numbers of grooves and pits and vice versa. Most of the roughness parameters allowed distinguishing between different ontogenetic classes and closely followed the typical sigmoidal animal growth curve. Our results show that bone texture quantification is a feasible approach to identifying ontogenetic age classes. Subject BoneDigital microscopyOntogenyRoughnessSurfacesTaphonomyTopography To reference this document use: http://resolver.tudelft.nl/uuid:b6340365-5a29-4611-b1cb-814b7cfbea41 DOI https://doi.org/10.1186/s40543-023-00413-1 ISSN 2093-3134 Source Journal of Analytical Science and Technology, 14 (1) Part of collection Institutional Repository Document type journal article Rights © 2023 Jimmy de Rooij, M.Q. Vintges, T. Zuidwijk, C.T.H. Heerkens, Anne S. Schulp Files PDF s40543_023_00413_1.pdf 2.55 MB Close viewer /islandora/object/uuid:b6340365-5a29-4611-b1cb-814b7cfbea41/datastream/OBJ/view