Fecha
Inicio: 02/11/2020, Fin: 30/11/2023.
Objetivos
Objetivos del proyecto
Research on modern seeds has shown that their shape reflects the influence of environmental growth conditions, including cultivation regimes. However, no modern agronomical or archaeobotanical studies have so far exploited this immense potential of information encompassed in seed shape. The main reason is that shape in these disciplines is currently studied using geometric morphometrics (GMM) but, largely due to the small size of grains, this is...
Research on modern seeds has shown that their shape reflects the influence of environmental growth conditions, including cultivation regimes. However, no modern agronomical or archaeobotanical studies have so far exploited this immense potential of information encompassed in seed shape. The main reason is that shape in these disciplines is currently studied using geometric morphometrics (GMM) but, largely due to the small size of grains, this is limited to 2D and semi-3D landmark measurements that cannot take advantage of the full, complex shape of the crops. iShape3DSeed will tackle this problem by employing cutting-edge emerging technologies and a novel combination of high-resolution 3D modelling of seeds, geometric morphometrics and machine learning (ML). The aim is to develop a novel, non-destructive and low-cost methodological toolkit that will allow using the full 3D shape of seeds to provide in-depth interpretations on agricultural management and distinguish environmental impact. To do so iShape3DSeed will focus on cereals and will use material from the Greek Genetic Bank that includes pre-mechanisation crops with their growing information, experimental cultivation of traditional cereal varieties, and archaeological material from four Aegean Bronze Age sites. The modern material will be used to develop and test the new toolkit, and the ancient to allow and test its archaeological application. The modern material will be also experimentally charred to test preservation impact on shape. The seeds will be reconstructed using micro 3D photogrammetry and will then be subjected to 3D GMM and surface texture analyses. The data obtained will be fed into purposely developed ML algorithms to classify and match shape and agricultural data. iShape3DSeed will provide thus a new means to identify agricultural management regimes in archaeological seed assemblages solely using the full shape of cereal seeds, pushing the frontiers of archaeobotany.
ver más
Ambito
Comunidad autónoma: Se buscaba un proyecto en cooperación con un partner de CCAA especificas.
Este proyecto fue tramitado con éxito!.