Using numerical plant models and phenotypic correlation space to design achievable ideotypes

Abstract

1Numerical plant models can predict the outcome of plant traits modifications resulting from genetic variations, on plant performance, by simulating physiological processes and their interaction with the environment. Optimization methods complement those models to design ideotypes, i.e. ideal values of a set of plant traits resulting in optimal adaptation for given combinations of environment and management, mainly through the maximization of a performance criteria (e.g. yield, light interception). As use of simulation models gains momentum in plant breeding, numerical experiments must be carefully engineered to provide accurate and attainable results, rooting them in biological reality. Here, we propose a multi-objective optimization formulation that includes a metric of performance, returned by the numerical model, and a metric of feasibility, accounting for correlations between traits based on field observations. We applied this approach to two contrasting models: a process-based crop model of sunflower and a functional-structural plant model of apple trees. In both cases, the method successfully characterized key plant traits and identified a continuum of optimal solutions, ranging from the most feasible to the most efficient. The present study thus provides successful proof of concept for this enhanced modeling approach, which identified paths for desirable trait modification, including direction and intensity.

Corner's rules as a framework for plant morphology, architecture and functioning – issues and steps forward

“…Recent attempts that aim at designing plant ideotypes to improve light interception using plant numerical models conclude on the interest of ideotypes with long internodes (e.g. tomato, Sarlikioti et al ., ; Chen et al ., ; apple, Picheny et al ., ) possibly combined with high leaf area (apple, Picheny et al ., ) and/or with narrow leaves, that is, high length to width ratio (e.g. tomato, Sarlikioti et al ., ).…”

“…For example, in the apple case, increasing both stem length and leaf area as proposed by Picheny et al . () is biologically realistic and agronomically relevant only up to a critical value of stem slenderness.…”

Impact of the Genetic–Environment Interaction on the Dynamic of Nitrogen Pools in Arabidopsis

“…These G × E interactions require considerable experimental effort to identify the persistent traits that contribute to NUE increases across many environments. Computer-based modelling approaches have recently emerged as a method to save time, labor, and resources, and to infer trait values beyond field experiments [24]. Early models focused on leaf to canopy assimilation, with emphasis on light interception and canopy architecture [25].…”

Heliaphen, an outdoor high-throughput phenotyping platform designed to integrate genetics and crop modeling

“…Globally, the SUNFLO crop model has about 50 equations and 64 parameters: 43 plant-related traits, among which eight are genotype-dependent, and 21 environment-related. A report that summarizes the equations and parameters used in the model is available as supplementary information in Picheny et al (2017). The source code is available on INRA software repository [https://forgemia.inra.fr/record/sunflo.git].…”