Data-intensive scientific workflows for model-assisted high-throughput phenotyping

High-throughput phenotyping platforms allow the study of the form and function of a large number of genotypes subjected to different growing conditions (GxE). Automatic computational pipelines for phenotyping are able to characterize the structure and the development of plants at an unprecedent resolution. Scientific workflows are way to schedule these complex pipelines on distributed cloud infrastructure, to manage the huge amount of data and to enhance the reproducibility of such experiments. In this presentation, I will discuss the recent developments in root and shoot phenotyping methods, how it challenges FSPM formalisms and platforms, and how scientific workflows management system can help to improve the connection between phenotyping and modelling communities while reducing the processing and environmental cost of the computation.