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Validation of a PCR test to predict the presence of flavor volatiles mesifurane and γ-decalactone in fruits of cultivated strawberry (Fragaria × ananassa)

Overview of attention for article published in Molecular Breeding, October 2017
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Title
Validation of a PCR test to predict the presence of flavor volatiles mesifurane and γ-decalactone in fruits of cultivated strawberry (Fragaria × ananassa)
Published in
Molecular Breeding, October 2017
DOI 10.1007/s11032-017-0732-7
Pubmed ID
Authors

Eduardo Cruz-Rus, Rafael Sesmero, José A. Ángel-Pérez, José F. Sánchez-Sevilla, Detlef Ulrich, Iraida Amaya

Abstract

Flavor improvement is currently one of the most important goals for strawberry breeders. At the same time, it is one of the most complex traits to improve, involving the balanced combination of several desired characteristics such as high sweetness, moderate acidity, and the appropriate combination of aroma compounds that are beginning to be delineated in consumer tests. DNA-informed breeding will expedite the selection of complex traits, such as flavor, over traditional phenotypic evaluation, particularly when markers linked to several traits of interests are combined during the breeding process. Natural variation in mesifurane and γ-decalactone, two key volatile compounds providing sweet Sherry and fresh peach-like notes to strawberry fruits, is controlled by the FaOMT and FaFAD1 genes, respectively. In this study, we have optimized a simple PCR test for combined analysis of these genes and determined a prediction accuracy above 91% using a set of 71 diverse strawberry accessions. This high accuracy in predicting the presence of these important volatiles combined with the simplicity of the analytical methodology makes this DNA test an efficient tool for its implementation in current strawberry-breeding programs for the selection of new strawberry cultivars with superior flavor.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 18%
Researcher 6 18%
Student > Ph. D. Student 6 18%
Other 2 6%
Student > Bachelor 1 3%
Other 3 9%
Unknown 10 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 50%
Biochemistry, Genetics and Molecular Biology 3 9%
Computer Science 1 3%
Chemistry 1 3%
Engineering 1 3%
Other 0 0%
Unknown 11 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 03 October 2017.
All research outputs
#15,481,147
of 23,005,189 outputs
Outputs from Molecular Breeding
#387
of 545 outputs
Outputs of similar age
#202,147
of 322,939 outputs
Outputs of similar age from Molecular Breeding
#5
of 6 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 545 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.