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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 419086
Title 3D modelling of branching in plants
Author(s) Evers, J.B.
Source In: Proceedings of the MODSIM2011, 19th International Congress on Modelling and Simulation, 12-16 December 2011, Perth, Australia. - Modelling and Simulation Society of Australia and New Zealand - ISBN 9780987214317 - p. 982 - 988.
Event MODSIM 2011 : Sustaining our future : understanding and living with uncertainty, Perth, Australia, 2011-12-12/2011-12-16
Department(s) Crop and Weed Ecology
Publication type Contribution in proceedings
Publication year 2011
Abstract Shoot branching is a key determinant of overall aboveground plant form. During plant development, the number of branches formed strongly influences the amount of light absorbed by the plant, and thus the plant’s competitive strength in terms of light capture in relation to neighbouring plants. Branching is regulated by multiple internal factors which are modulated by different environmental signals. A key environmental signal in the context of a plant population is a low red / far-red intensity ratio (R:FR) of the light reflected by neighbouring plants. For instance, low R:FR results in suppression of branching in favour of elongation growth, which is a key aspect of shade avoidance. Shade avoidance enables plants to anticipate future competition by preventing being shaded, rather than to react to prevailing shade conditions. Internally, branching is regulated by a finely tuned plant hormone network. The interactions within this network are modified by environmental cues such as R:FR which is perceived by specific photoreceptors. Combined, internal and external signals enable regulation of branch formation under the influence of environmental conditions. The different aspects of branching control act at different levels of biological organization (organ, whole plant, plant community). These aspects can be integrated in one modelling approach, called functional-structural plant modelling (FSPM), explicitly considering spatial 3D plant development. An FSP model typically contains detailed information at any moment in development of the plant on the number, size, location and orientation of all organs that make up the plant. In FSP models, physiological and physical processes occur within the plant (e.g. photosynthesis and transport of assimilates), and interaction with the environment occurs at the interface of organ and environment (e.g. light absorption by a leaf). Explicit simulation of absorption and scattering of light at the level of the plant organ is an important aspect of FSPM. In combination with dedicated experiments, this modelling tool can be used to analyse the response of plants to (imminent) competition, simulate the competitive advantage of shade avoidance for plants of different architecture, and predict plant form in various light environments. To assess the effect of plant population density through R:FR signalling on tillering (branching) in spring wheat (Triticum aestivum L.), an FSPM study was conducted (Figure 1). A simple descriptive relationship was used to link R:FR as perceived by the plant to extension growth of tiller buds and probability of a bud to form a tiller. A further study included a complete sub-model of branching regulation, aiming at simulating branching as an emergent property in Arabidopsis (Arabidopsis thaliana) under the influence of R:FR. These and other studies show that FSPM is a promising tool to simulate aspects of plant development, such as branching, under the influence of environmental factors. In close combination with dedicated experiments, FSPM can shape our ideas of the mechanisms controlling plant development, can integrate existing knowledge on plant development, and can predict plant development in untested conditions.
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