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Reference: Simulating organ biomass variability and carbohydrate distribution in perennial fruit crops- a comparison between the common assimilate pool and phloem carbohydrate transport models
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Abstract-

Variability in fruit quality greatly impedes the profitability of an orchard. Modelling can help find the causes of quality variability. However, studies suggest that the common assimilate pool model is inadequate in terms of describing variability in organ biomass. The aim of the current study was to compare the performances of the common assimilate pool and phloem carbohydrate transport models in simulating phloem carbohydrate concentration and organ biomass variability within the whole-plant functional-structural grapevine (Vitis vinifera L.) model that we developed previously. A statistical approach was developed for calibrating the model with a detailed potted experiment that entails three levels of leaf area per vine during the fruit ripening period. Global sensitivity analysis illustrated that carbohydrate allocation changed with the amount of leaf area as well as the limiting factors for organ biomass development. Under a homogenous canopy architecture where all grape bunches were equally close to the carbohydrate sources, the common assimilate pool and phloem transport models produced very similar results. However, under a heterogeneous canopy architecture with variable distance between bunches and carbohydrate sources, the coefficient of variation for fruit biomass rose from 0.01 to 0.17 as crop load increased. These results indicate that carbohydrate allocation to fruits is affected by both the size of crop load and fruit distribution, which is not adequately described by the common assimilate pool model. The new grapevine model can also simulate dynamic canopy growth and be adapted to help optimise canopy architecture and quality variability of other perennial fruit crops.

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Link to paper-

https://academic.oup.com/insilicoplants/advance-article/doi/10.1093/insilicoplants/diab024/6349132

https://doi.org/10.1093/insilicoplants/diab024


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Publication Details

Published: 2021
Publication: in silico Plants
Issue: 2021 Online August 2021
Author: Zhu J 2021
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