MicroCT technology has been used to determine the 3D microscale morphology of organic remains within pottery sherds. In contrast to surface impressions, microCT provides images of the entire organic remains of specific cereals preserved within the pottery, including the abscission scar characteristic of domesticated rice. Researches on the discrimination of domesticated and wild plants requires well-shaped plant samples, which brings the subsampling of organic remains within the pottery sherds a great challenge.

Based on the 3D microCT referenced datasets, this project aims to develop an automated, robotic microdrill stage to enable the subsampling of the inclusions as well as develop a machine learning algorithm/platform to discriminate between domesticated and wild plant remains such as rice, sorghum and pear millet.