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Models for Predicting the Architecture of Different Shoot Types in Apple
In apple, the first-order branch of a tree has a characteristic architecture constituting three shoot types: bourses (rosettes), bourse shoots, and vegetative shoots. Its overall architecture as well as that of each shoot thus determines the distribution of sources (leaves) and sinks (fruits) and co...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5285357/ https://www.ncbi.nlm.nih.gov/pubmed/28203241 http://dx.doi.org/10.3389/fpls.2017.00065 |
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author | Baïram, Emna Delaire, Mickaël Le Morvan, Christian Buck-Sorlin, Gerhard |
author_facet | Baïram, Emna Delaire, Mickaël Le Morvan, Christian Buck-Sorlin, Gerhard |
author_sort | Baïram, Emna |
collection | PubMed |
description | In apple, the first-order branch of a tree has a characteristic architecture constituting three shoot types: bourses (rosettes), bourse shoots, and vegetative shoots. Its overall architecture as well as that of each shoot thus determines the distribution of sources (leaves) and sinks (fruits) and could have an influence on the amount of sugar allocated to fruits. Knowledge of architecture, in particular the position and area of leaves helps to quantify source strength. In order to reconstruct this initial architecture, rules equipped with allometric relations could be used: these allow predicting model parameters that are difficult to measure from simple traits that can be determined easily, non-destructively and directly in the orchard. Once such allometric relations are established they can be used routinely to recreate initial structures. Models based on allometric relations have been established in this study in order to predict the leaf areas of the three different shoot types of three apple cultivars with different branch architectures: “Fuji,” “Ariane,” and “Rome Beauty.” The allometric relations derived from experimental data allowed us to model the total shoot leaf area as well as the individual leaf area for each leaf rank, for each shoot type and each genotype. This was achieved using two easily measurable input variables: total leaf number per shoot and the length of the biggest leaf on the shoot. The models were tested using a different data set, and they were able to accurately predict leaf area of all shoot types and genotypes. Additional focus on internode lengths on spurs contributed to refine the models. |
format | Online Article Text |
id | pubmed-5285357 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-52853572017-02-15 Models for Predicting the Architecture of Different Shoot Types in Apple Baïram, Emna Delaire, Mickaël Le Morvan, Christian Buck-Sorlin, Gerhard Front Plant Sci Plant Science In apple, the first-order branch of a tree has a characteristic architecture constituting three shoot types: bourses (rosettes), bourse shoots, and vegetative shoots. Its overall architecture as well as that of each shoot thus determines the distribution of sources (leaves) and sinks (fruits) and could have an influence on the amount of sugar allocated to fruits. Knowledge of architecture, in particular the position and area of leaves helps to quantify source strength. In order to reconstruct this initial architecture, rules equipped with allometric relations could be used: these allow predicting model parameters that are difficult to measure from simple traits that can be determined easily, non-destructively and directly in the orchard. Once such allometric relations are established they can be used routinely to recreate initial structures. Models based on allometric relations have been established in this study in order to predict the leaf areas of the three different shoot types of three apple cultivars with different branch architectures: “Fuji,” “Ariane,” and “Rome Beauty.” The allometric relations derived from experimental data allowed us to model the total shoot leaf area as well as the individual leaf area for each leaf rank, for each shoot type and each genotype. This was achieved using two easily measurable input variables: total leaf number per shoot and the length of the biggest leaf on the shoot. The models were tested using a different data set, and they were able to accurately predict leaf area of all shoot types and genotypes. Additional focus on internode lengths on spurs contributed to refine the models. Frontiers Media S.A. 2017-02-01 /pmc/articles/PMC5285357/ /pubmed/28203241 http://dx.doi.org/10.3389/fpls.2017.00065 Text en Copyright © 2017 Baïram, Delaire, Le Morvan and Buck-Sorlin. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Baïram, Emna Delaire, Mickaël Le Morvan, Christian Buck-Sorlin, Gerhard Models for Predicting the Architecture of Different Shoot Types in Apple |
title | Models for Predicting the Architecture of Different Shoot Types in Apple |
title_full | Models for Predicting the Architecture of Different Shoot Types in Apple |
title_fullStr | Models for Predicting the Architecture of Different Shoot Types in Apple |
title_full_unstemmed | Models for Predicting the Architecture of Different Shoot Types in Apple |
title_short | Models for Predicting the Architecture of Different Shoot Types in Apple |
title_sort | models for predicting the architecture of different shoot types in apple |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5285357/ https://www.ncbi.nlm.nih.gov/pubmed/28203241 http://dx.doi.org/10.3389/fpls.2017.00065 |
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