DarkAegean departs from an innovative hypothesis: the shape of plant seeds reflects their growth conditions. While this is well studied in relation to certain material like human and animal bones, for grains this is far from established. In 2020, as part of the DarkRevisited project (PID2019-107605GB-I00) led by the PI, the first attempt to create a method for the automated co-relation between grain shape and agricultural regimes took place. This combined micro-3D reconstructions of experimentally cultivated barley grains, one of the most important cereal species in agriculture, automated measure extraction and machine learning. The first proofs of concept demonstrated that there are significant differences between the shape of barley grains grown under different irrigation and manure conditions, and that these can be identified using the methodology developed by the project with high success rates. DarkAegean will build upon and expand the previous project by creating a similar method to identify agricultural regimes of another pilar of ancient agriculture, that of wheat, to provide a more complete picture of cereal cultivation and agriculture in the past. This innovative methodology will be then applied on the analysis of the transition between the Late Bronze Age (LBA) and the Early Iron Age (EIA) in the Aegean. A highly debated period known as the Dark Ages given the lack of substantial information about it and the radical sociocultural changes that characterised the EIA in the Aegean. These changes transformed the whole social and economic system in a process that had already started in the LBA and culminated with the collapse of the Mycenean palatial societies. DarkAegean aims to continue the work of DarkRevisited by synthesising existing and producing new primary evidence from across the Aegean in a novel way to provide a fresh approach to these debates through an in-depth, evidence-based understanding of diet and agricultural economies in the LBA and EIA. The methodology of the project involves the experimental cultivations of wheat under a variety of controlled agricultural regimes using material from the Greek Gene Bank. The harvested grain will be analysed with 3D Machine Learning-aided Geometric Morphometrics and stable isotope analyses with the aim to develop a new algorithm that will allow the correlation of specific wheat shapes with specific agricultural management practices. This will then be applied to archaeological wheat from six sites across the Aegean to inform on past agriculture and economy. Stable isotope analyses of archaeological plants remains, animal bones, shells, and human bones from the same Aegean sites will provide important complementary information to obtain a holistic understanding of diet and resource management in the LBA and EIA Aegean. This interdisciplinary project has the potential to step change the discipline of archaeobotany but also impact cultural heritage management and the maintenance of food plant biodiversity.
Expected Scientific, Technical, and International Impact
The DarkAegean project is expected to have a significant scientific impact with international recognition. In particular, it aims to develop a new tool capable of transforming current approaches to the study of archaeobotanical remains and revolutionizing our understanding of the Aegean world during the Late Bronze Age (LBA) and the Early Iron Age (EIA). This new tool has real potential to be applied in the future to materials from a wide range of periods and geographical regions, thereby maximizing its impact across the discipline.
With regard to the Aegean, the combination of methodologies employed will enable a more detailed analysis of agricultural economies, subsistence strategies, and dietary practices between the LBA and the EIA. This will not only advance knowledge of the period but also generate new hypotheses concerning the nature of the so-called “Dark Age,” addressing one of the most debated research topics in archaeology. Furthermore, the creation of a 3D wheat seed database will constitute an outstanding resource not only for archaeology but also for disciplines concerned with agricultural products, such as agronomy, plant biology, and food studies, thereby extending the project’s impact well beyond archaeology.
Given the rapidly growing trend toward digitization and computational analysis, the project’s outcomes are expected to be highly valuable for archaeobotanical research and teaching alike. The project will develop, preserve, and disseminate one of the largest and most diverse reference collections of traditional crop varieties experimentally grown under controlled and well-documented conditions for archaeological purposes. This collection will become a unique resource for archaeologists seeking to understand not only past agricultural regimes and strategies but also the effects of climate on agriculture, resilience, and sustainability. It may also be used to assess and evaluate other methods commonly employed in archaeology, such as geometric morphometrics (GMM) and isotopic analyses.
The algorithms and code for 3D geometric morphometric measurements and 3D model analysis generated within the project may also contribute to methodological advances across a broad range of fields in which object shape contains valuable information, including several archaeological sub-disciplines (e.g., lithic and osteological analyses), agronomy, engineering, medicine, and others.
Finally, the project will expand the frontiers of digital heritage by continuing to develop 3D shape-analysis methods that move beyond simple digitization. It will also contribute to more holistic food-security management plans and policies by supporting the sustainable conservation and use of traditional wheat varieties according to their suitability for different geographical areas, microclimates, and cultivation regimes. Collaboration with an international research team, combined with the project’s dissemination strategy targeting both the scientific community and the wider public, will maximize and ensure its impact at both national and international levels.
Project funded by Ministerio de Ciencia e Innovación and European Union
