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Quantitative trait loci from identification to exploitation for crop improvement

Overview of attention for article published in Plant Cell Reports, March 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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11 X users
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1 Wikipedia page

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73 Dimensions

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124 Mendeley
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Title
Quantitative trait loci from identification to exploitation for crop improvement
Published in
Plant Cell Reports, March 2017
DOI 10.1007/s00299-017-2127-y
Pubmed ID
Authors

Jitendra Kumar, Debjyoti Sen Gupta, Sunanda Gupta, Sonali Dubey, Priyanka Gupta, Shiv Kumar

Abstract

Advancement in the field of genetics and genomics after the discovery of Mendel's laws of inheritance has led to map the genes controlling qualitative and quantitative traits in crop plant species. Mapping of genomic regions controlling the variation of quantitatively inherited traits has become routine after the advent of different types of molecular markers. Recently, the next generation sequencing methods have accelerated the research on QTL analysis. These efforts have led to the identification of more closely linked molecular markers with gene/QTLs and also identified markers even within gene/QTL controlling the trait of interest. Efforts have also been made towards cloning gene/QTLs or identification of potential candidate genes responsible for a trait. Further new concepts like crop QTLome and QTL prioritization have accelerated precise application of QTLs for genetic improvement of complex traits. In the past years, efforts have also been made in exploitation of a number of QTL for improving grain yield or other agronomic traits in various crops through markers assisted selection leading to cultivation of these improved varieties at farmers' field. In present article, we reviewed QTLs from their identification to exploitation in plant breeding programs and also reviewed that how improved cultivars developed through introgression of QTLs have improved the yield productivity in many crops.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 124 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 24%
Researcher 21 17%
Student > Master 17 14%
Student > Doctoral Student 9 7%
Student > Postgraduate 5 4%
Other 14 11%
Unknown 28 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 51%
Biochemistry, Genetics and Molecular Biology 22 18%
Environmental Science 3 2%
Immunology and Microbiology 2 2%
Unspecified 1 <1%
Other 3 2%
Unknown 30 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 30 April 2022.
All research outputs
#4,213,360
of 23,655,983 outputs
Outputs from Plant Cell Reports
#253
of 2,237 outputs
Outputs of similar age
#72,991
of 309,580 outputs
Outputs of similar age from Plant Cell Reports
#5
of 46 outputs
Altmetric has tracked 23,655,983 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,237 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 88% of its peers.
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 309,580 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.