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Multiple major QTL lead to stable yield performance of rice cultivars across varying drought intensities

Overview of attention for article published in BMC Genomic Data, February 2014
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Title
Multiple major QTL lead to stable yield performance of rice cultivars across varying drought intensities
Published in
BMC Genomic Data, February 2014
DOI 10.1186/1471-2156-15-16
Pubmed ID
Authors

Shalabh Dixit, Anshuman Singh, Ma Teresa Sta Cruz, Paul T Maturan, Modesto Amante, Arvind Kumar

Abstract

Availability of irrigation water is becoming a major limiting factor in rice cultivation. Production in rainfed areas is affected in particular by drought events, as these areas are commonly planted to high-yielding drought-susceptible rice (Oryza sativa L.) varieties. The use of bulk segregant analysis (BSA), taking grain yield (GY) as a selection criterion, has resulted in the identification of several large-effect QTL. A QTL mapping study was undertaken on a BC1F3:4 population developed from the cross IR55419-04/2*TDK1 with the aim of identifying large-effect QTL in the background of TDK1, a popular variety from Lao PDR.

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The data shown below were collected from the profile of 1 X user 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 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Philippines 1 <1%
Netherlands 1 <1%
United States 1 <1%
Benin 1 <1%
Unknown 102 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 28%
Researcher 15 14%
Student > Master 9 8%
Student > Bachelor 7 7%
Student > Postgraduate 7 7%
Other 19 18%
Unknown 19 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 65 61%
Biochemistry, Genetics and Molecular Biology 9 8%
Environmental Science 2 2%
Chemistry 2 2%
Unspecified 1 <1%
Other 5 5%
Unknown 22 21%
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 04 February 2014.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from BMC Genomic Data
#1,008
of 1,204 outputs
Outputs of similar age
#282,882
of 322,918 outputs
Outputs of similar age from BMC Genomic Data
#19
of 22 outputs
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