JANNIN Marine

PhD student
in Plant Ecophysiology

Team: MAGE

I hold a Master’s degree in Agro-Sciences – Plant and Microbiological Sciences for Agro-environment from the University of Montpellier (IDIL graduate program). During my Master’s internships within the MAGE research team, I worked on representing the genetic variability of wheat growth responses under water deficit. These experiences strengthened my interest in plant growth dynamics and their modelling.

Since October 2024, I have been a PhD student in the MAGE team, where I study the phenotypic space of organ growth dynamics under water deficit and how it can be represented in a simplified and operational way to capture genetic variability in modelling.

Start of PhD: 1.10.2014

Subject: Modeling the trade-off between transpiration and carbon sink of vegetative growth in wheat under water deficit and elevated CO₂ Conditions

Abstract
Improving wheat tolerance to water constraints is a major challenge in the context of climate change, characterized by increasing drought frequency and rising atmospheric CO₂ concentrations (eCO₂). Under water deficit, plants adjust their vegetative growth by reducing tillering and leaf expansion, in ways that are specific to each genotype. These adjustments influence water availability during reproductive stages and, through the formation and dynamics of carbon sinks, the balance between growth and photosynthetic assimilation. However, under future eCO₂ conditions, the decreased carbon demand associated with reduced growth could enhance photosynthetic acclimation, thereby altering which varieties are best suited to different water scenarios.
This thesis aims to characterize and model the genetic variability of vegetative growth responses to water deficit. The approach is based on the identification of robust “meta-parameters” derived from the analysis of a genetic diversity panel, in order to reduce the phenotypic space and extract general rules describing genotypic variability. These meta-parameters will summarize the different responses and enable high-throughput analyses of genetic variability in both controlled platforms and field conditions. The formalization of this knowledge into simplified ecophysiological models will be integrated into the SiriusQuality crop model. This integration will provide a predictive tool to identify, across current and future environments, the optimal trade-offs in reducing vegetative growth that promote wheat resilience and yield.

Key words: abiotic stress, ecophysiology, climate change, modelling, plant growth, time series, water deficit, wheat.

Supervisors
UMR LEPSE, MAGE team: Boris Parent (PhD supervisor)
UMR LEPSE, MAGE team: Pierre Martre (PhD supervisor)