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Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping

Overview of attention for article published in Frontiers in Plant Science, June 2017
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Title
Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping
Published in
Frontiers in Plant Science, June 2017
DOI 10.3389/fpls.2017.00858
Pubmed ID
Authors

Jean-Baptiste Durand, Alix Allard, Baptiste Guitton, Eric van de Weg, Marco C. A. M. Bink, Evelyne Costes

Abstract

Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS) were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI) with an autoregressive coefficient (γ g ) efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γ g and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Netherlands 1 3%
Unknown 34 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 31%
Researcher 9 25%
Student > Master 4 11%
Student > Bachelor 3 8%
Student > Doctoral Student 3 8%
Other 3 8%
Unknown 3 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 69%
Biochemistry, Genetics and Molecular Biology 3 8%
Environmental Science 1 3%
Nursing and Health Professions 1 3%
Computer Science 1 3%
Other 2 6%
Unknown 3 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 July 2017.
All research outputs
#15,418,269
of 22,988,380 outputs
Outputs from Frontiers in Plant Science
#10,741
of 20,449 outputs
Outputs of similar age
#198,400
of 317,340 outputs
Outputs of similar age from Frontiers in Plant Science
#370
of 593 outputs
Altmetric has tracked 22,988,380 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,449 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,340 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 593 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.