Yield analysis as a function of stochastic plant architecture: Case of Spilanthes acmella in the wet and dry season
2017
Vavitsara, Marie Elodie | Sabatier, Sylvie | Kang, Mengzhen | Ranarijaona, Hery Lisy Tiana | de Reffye, Philippe, Verchère de Reffye | Université de Mahajanga = University of Mahajanga | Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [Occitanie]) | Chinese Academy of Sciences [Changchun Branch] (CAS)
International audience
اظهر المزيد [+] اقل [-]إنجليزي. The number of organs produced by a plant varies among the individuals of a population. Taking these variations into account is an important step in understanding phenotypic variability. The aim of this study was to simulate stochastic development and growth in response to environmental change using GreenLab, an organ level functional-structural model. An annual herbaceous species, Spilanthes acmella L., was grown in pots in two climatic conditions corresponding to a wet and a dry season. Detailed records of plant development, plant architecture and organ growth were kept throughout the growing period. The concept of simple and compound organic series was introduced to target data for fitting. The model was calibrated using a mathematical model of stochastic plant development and growth. Here we describe (1) how a stochastic Functional Structural Plant Model is calibrated in two steps by first assessing the functioning parameters of meristems, and second the source-sink parameters of organs by fitting them on average organic series; (2) how dry conditions trigger the response of the plant both in the development of the inflorescence and in the allocation of biomass, quantified by model parameters. The calibration of a stochastic plant model opens a large window of opportunity to capture the common features of plant development and growth among stochastic individuals in a plant population, especially those with a branching structure. This extends the area of application of FSPM to analyzing food plants, or assisting breeding.
اظهر المزيد [+] اقل [-]المعلومات البيبليوغرافية
تم تزويد هذا السجل من قبل Institut national de la recherche agronomique