[Defending thesis] Girault-Bogue Gnanguenon-Guesse: Modelling and viewing relations between agrienvironmental time courses and product quality using a parsimonious Bayesian approach

Girault-Bogue Gnanguenon-Guesse is one of the #DigitAg co-funded PhDs

Girault will defend his thesis on 22nd October at 10 AM at Institut Agro (Amphithéâtre 2 – Institut Agro | Montpellier SupAgro – INRAE 2 Place Pierre Viala, 34060 Montpellier)
Attend to the defence by visio

Modelling and viewing relations between agrienvironmental time courses and product quality using a parsimonious Bayesian approach

  • Start Date: December 2017
  • University: MUSE Montpellier University of Excellence / Institut Agro-Montpellier SupAgro
  • PhD School: ED 166 I2S – Information, Structures, Systèmes
  • Field(s): Biostatistics
  • Doctoral Thesis Advisor: Nadine Hilgert (Inrae, UMR Mistea)
  • Co-supervisors : Bénédicte Fontez (Institut Agro, UMR Mistea) et Thierry Simonneau (Inrae, Lepse)
  • Funding: #DigitAg – Inrae
  • #DigitAg: Confunded PhD – Axis 5 & 6 – Challenges 1, 5 & 7

Keywords: Factor models, Latent factor models, parsimonious approach, Bayesian inference, Application in Agronomy

Abstract:: Traditional knowledge plays an important role in agricultural practices. For instance, in the vine and wine food chain, decisions taken in vineyards mainly rely on expert knowledge-based approaches.Confronted with new challenges, stakeholders in agricultural production chains need advanced quantitative-based decision support tools. The aims of this PhD are i) to propose a knowledge discovery method to deal with big data from time courses, ii) to explain and predict product quality. Data integration should deal with high resolution data from sensors or agronomic models, low resolution observations and expert knowledge. It requires taking into account the reliability of all sources and data uncertainties. This calls for a coupling between informatics and data analysis, and constitutes the core of the PhD. The main application concerns the vine and wine food chain, in close relation with industrial partners (consulting professionals: ITK, Fruition Sciences, technical institute IFV) and public research laboratories (Joint Units LEPSE and SPO).

Jury compound

Élodie BRUNEL-PICCININI, Maître de conférences, Université de Montpellier : Examinatrice

Bénédicte FONTEZ, Maître de conférences, Institut Agro – Montpellier SupAgro : Co-Encadrante de thèse

Romain GLÈLÈ KAKAÏ, Professeur des universités, Université d’Abomey-Calavi : Examinateur

Nadine HILGERT, Directrice de recherche, INRAE – Montpellier : Directrice de thèse

Patrice LOISEL, Chargé de recherche, INRAE – Montpellier : Co-Encadrant de thèse

Tristan MARY-HUARD, Chargé de recherche, INRAE – Le Moulon : Rapporteur

Philippe PIERI, Chargé de recherche, INRAE – Bordeaux : Examinateur

Thierry SIMONNEAU, Directeur de recherche, INRAE – Montpellier : Co-Directeur de thèse

Nancy TERRIER, Chargée de recherche, INRAE – Montpellier : Invitée

Anne-Françoise YAO, Professeur des universités, Université Clermont-Auvergne : Rapporteure

Contact: girault-bogues.gnanguenon-guesse [AT] inrae.fr​ – Tél : +33 (0)499612595

Networks: LinkedIn


Papers at international conferences

GNANGUENON GUESSE G, LOISEL P, FONTEZ B, SIMONNEAU T, HILGERT N. An exploratory penalized regression to identify combined effects of functional agri-environmental variables, 6 – 31 August 2020. The 30th “virtual” International Biometric Conference, Séoul, International Biometric Society, 2020

GNANGUENON GUESSE G, LOISEL P, FONTEZ B, SIMONNEAU T, HILGERT N. Explorer l’influence conjointe de prédicteurs fonctionnels sur une réponse réelle via une régression pénalisée. Recueil des soumissions de la 52èmes Journées de Statistiques, Société Française de Statistique (SfdS), 2020, pp 375-380, sciencesconf.org :jds2020:319910