2018
DOI: 10.1093/jxb/ery367
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Modelling grape growth in relation to whole-plant carbon and water fluxes

Abstract: This study developed and used an advanced whole-plant grapevine model to unravel factors affecting water and carbon fluxes during fleshy fruit growth.

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Cited by 52 publications
(48 citation statements)
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“…This is an oversimplification, but a useful one, and is not intended to supersede more rigorous attempts at modeling vine water use ( Lebon et al , 2003 ; Peccoux et al , 2018 ; Zhu et al, 2018 , 2019 ). Using this framework in a simplified thought experiment gives insight into the relative importance of the various traits.…”
Section: Introductionmentioning
confidence: 99%
“…This is an oversimplification, but a useful one, and is not intended to supersede more rigorous attempts at modeling vine water use ( Lebon et al , 2003 ; Peccoux et al , 2018 ; Zhu et al, 2018 , 2019 ). Using this framework in a simplified thought experiment gives insight into the relative importance of the various traits.…”
Section: Introductionmentioning
confidence: 99%
“…Present knowledge about berry developmental biology derives essentially from the destructive analysis of sequential random samples taken as "representative". The average population at plot level is implicitly conceived as an ideal berry, whose gene expression and metabolic pathways are modulated by the G x E x M interaction, which has straightforward consequences on wine quality, explaining terroir and millesime effects (Fasoli et al, 2018;Zhu et al, 2019, among many others). However, density sorting (Singleton et al, 1966) has unambiguously showed that this "average" berry is a mixture of developmental stages (Zouid et al, 2013;Carbonell-Bejerano et al, 2016;Friedel et al, 2016;Liu et al, 2016;Bigard et al, 2019).…”
Section: Discussionmentioning
confidence: 99%
“…The dynamic approach was implemented based on L-Py, a programming language for Lindenmayer-systems. One of the latest functional-structural models for grapevine was designed to simulate berry quality based on carbon and water fluxes (e.g., [22,25,26], for GrapevineXL). This was achieved by linking a biomechanical gas exchange model and a complex water status model to local plant architectural conditions.…”
Section: Introductionmentioning
confidence: 99%