The current plant breeding strategies for water stress management are fragmented, as they do not cover the whole complexity of the soil-plant continuum. Current breeding strategies focus on a limited number of structural root phenes such as the insertion angle (1-2). The quantification of functional phenes (e.g. root radial conductivity) is more complex to include into the phenotyping process than other phenes because there is no direct access to it (3). To increase plant performance in specific environment, we need a new methodology to quantify functional phenes. The methodology proposed here is supported by current functional-structural plant models (FSPM) and with the coupling of those models. It consists in the characterization of "in silico" phenotypes in a large range of scenarios, based on preliminary experiments. It will provide insight to some traits that improve plant performance in specific environment. It will also allow for the estimation of the traits characterization that are difficult to measure directly, thanks to a set of low-cost measurements accessible in the field. The goal of the study is to benchmark the results from the experiment in the controlled environment and in the field with the ones from the models.
Heymans, A., Larue, T., Paez-Garcia, A., & Lobet, G. (2020). GRANAR: a R package to better understand the functional importance of root anatomy. NSABS 2020, National Symposium for Applied Biological Sciences, Gembloux Agro-Bio Tech. https://hdl.handle.net/2078.5/239115