Literature DB >> 22621431

A virtual plant that responds to the environment like a real one: the case for chrysanthemum.

MengZhen Kang1, Ep Heuvelink2, Susana M P Carvalho2,3, Philippe de Reffye4.   

Abstract

• Plants respond to environmental change through alterations in organ size, number and biomass. However, different phenotypes are rarely integrated in a single model, and the prediction of plant responses to environmental conditions is challenging. The aim of this study was to simulate and predict plant phenotypic plasticity in development and growth using an organ-level functional-structural plant model, GreenLab. • Chrysanthemum plants were grown in climate chambers in 16 different environmental regimes: four different temperatures (15, 18, 21 and 24°C) combined with four different light intensities (40%, 51%, 65% and 100%, where 100% is 340 μmol m⁻² s⁻¹). Measurements included plant height, flower number and major organ dry mass (main and side-shoot stems, main and side-shoot leaves and flowers). To describe the basipetal flowering sequence, a position-dependent growth delay function was introduced into the model. • The model was calibrated on eight treatments. It was capable of simulating multiple plant phenotypes (flower number, organ biomass, plant height) with visual output. Furthermore, it predicted well the phenotypes of the other eight treatments (validation) through parameter interpolation. • This model could potentially serve to bridge models of different scales, and to link energy input to crop output in glasshouses.
© 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

Entities:  

Mesh:

Year:  2012        PMID: 22621431     DOI: 10.1111/j.1469-8137.2012.04177.x

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


  6 in total

Review 1.  Two decades of functional-structural plant modelling: now addressing fundamental questions in systems biology and predictive ecology.

Authors:  Gaëtan Louarn; Youhong Song
Journal:  Ann Bot       Date:  2020-09-14       Impact factor: 4.357

2.  Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

Authors:  Yuntao Ma; Youjia Chen; Jinyu Zhu; Lei Meng; Yan Guo; Baoguo Li; Gerrit Hoogenboom
Journal:  Ann Bot       Date:  2018-04-18       Impact factor: 4.357

Review 3.  Functional-Structural Plant Models Mission in Advancing Crop Science: Opportunities and Prospects.

Authors:  Soualihou Soualiou; Zhiwei Wang; Weiwei Sun; Philippe de Reffye; Brian Collins; Gaëtan Louarn; Youhong Song
Journal:  Front Plant Sci       Date:  2021-12-23       Impact factor: 5.753

4.  A functional and structural Mongolian Scots pine (Pinus sylvestris var. mongolica) model integrating architecture, biomass and effects of precipitation.

Authors:  Feng Wang; Véronique Letort; Qi Lu; Xuefeng Bai; Yan Guo; Philippe de Reffye; Baoguo Li
Journal:  PLoS One       Date:  2012-08-22       Impact factor: 3.240

5.  Predicting Plant Performance Under Simultaneously Changing Environmental Conditions-The Interplay Between Temperature, Light, and Internode Growth.

Authors:  Katrin Kahlen; Tsu-Wei Chen
Journal:  Front Plant Sci       Date:  2015-12-21       Impact factor: 5.753

6.  Elucidating the interaction between light competition and herbivore feeding patterns using functional-structural plant modelling.

Authors:  Jorad de Vries; Erik H Poelman; Niels Anten; Jochem B Evers
Journal:  Ann Bot       Date:  2018-04-18       Impact factor: 4.357

  6 in total

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