[PhD’s corner] Mario Serouart: Characterization of maize response to competition: effects of stand structure and regularity on crop performance

Mario is one of the #DigitAg co-funded PhDs

Mario Serouart

Characterization of maize response to the competition: effects of stand structure and regularity on crop performance

  • Start Date: 3rd May 2021
  • University: AE2 – ED 536 Agrosciences & Sciences
  • PhD School: I2S – Avignon University
  • Field(s): Agronomy, Computer/ Data Science
  • Doctoral Thesis Advisor: Frédéric Baret, Inrae, UMR Emmah
  • Co-supervisors: Raul Lopez-Lozano, Inrae, UMR Emmah | Jean-Charles Deswarte & Benoît de Solan, Acta, Arvalis Institut du végétal
  • Funding: CIFRE Arvalis | Acta
  • #DigitAg: Funded PhD – Axis 6: Modelling and simulation (agricultural production systems), Axis 2: Innovations in digital agriculture, Axis 3: Sensors, data acquisition and management, Challenge 1: ICT and the agroecology challenge, Challenge 2: Digital solutions to optimize the genotype in changing production systems and markets

Keywords: Deep Learning, LiDAR, Feature extraction, High-throughput phenotyping, Light detection, Plant phenotyping

Abstract: The main goal of the thesis is to understand and model the architectural plasticity of maize genotypes in response to intraspecific competition. Then relate these determinants to plant performance in terms of pollen production, yield and total biomass. The project focuses on various issues related to optimizing stand structure to improve maize yield. Indeed, several determinants induce an inter-species competition in the plant canopy, particularly in light capture, which will be the subject of particular attention in this thesis, i.e. the estimation of the quantity and quality perceived/reflected of red far-red radiation. More precisely, the study of the relationship between these two terms, depending on the proximity of photosynthetic organs between neighbouring plants and thus on a struggle for available resources. Maize will thus modify its morphology as a consequence by reorienting the leaves or lengthening the stem. The interest of the CIFRE thesis is to draw patterns or advice to maximize production, inter-row density, and research real field conditions, an axis that differs greatly from the controlled character, usually done in research, certainly facilitating studies hardly reflecting the reality in the field.

Contact: mario.serouart [AT] inrae.fr

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