↓ Skip to main content

Genome-wide association mapping of soybean chlorophyll traits based on canopy spectral reflectance and leaf extracts

Overview of attention for article published in BMC Plant Biology, August 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
5 X users

Citations

dimensions_citation
42 Dimensions

Readers on

mendeley
58 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Genome-wide association mapping of soybean chlorophyll traits based on canopy spectral reflectance and leaf extracts
Published in
BMC Plant Biology, August 2016
DOI 10.1186/s12870-016-0861-x
Pubmed ID
Authors

Arun Prabhu Dhanapal, Jeffery D. Ray, Shardendu K. Singh, Valerio Hoyos-Villegas, James R. Smith, Larry C. Purcell, Felix B. Fritschi

Abstract

Chlorophyll is a major component of chloroplasts and a better understanding of the genetic basis of chlorophyll in soybean [Glycine max (L.) Merr.] might contribute to improving photosynthetic capacity and yield in regions with adverse environmental conditions. A collection of 332 diverse soybean genotypes were grown in 2 years (2009 and 2010) and chlorophyll a (eChl_A), chlorophyll b (eChl_B), and total chlorophyll (eChl_T) content as well as chlorophyll a/b ratio (eChl_R) in leaf tissues were determined by extraction and spectrometric determination. Total chlorophyll was also derived from canopy spectral reflectance measurements using a model of wavelet transformed spectra (tChl_T) as well as with a spectral reflectance index (iChl_T). A genome-wide associating mapping approach was employed using 31,253 single nucleotide polymorphisms (SNPs) to identify loci associated with the extract based eChl_A, eChl_B, eChl_R and eChl_T measurements and the two canopy spectral reflectance-based methods (tChl_T and iChl_T). A total of 23 (14 loci), 15 (7 loci) and 14 SNPs (10 loci) showed significant association with eChl_A, eChl_B and eChl_R respectively. A total of 52 unique SNPs were significantly associated with total chlorophyll content based on at least one of the three approaches (eChl_T, tChl_T and iChl_T) and likely tagged 27 putative loci for total chlorophyll content, four of which were indicated by all three approaches. Results presented here show that markers for chlorophyll traits can be identified in soybean using both extract-based and canopy spectral reflectance-based phenotypes, and confirm that high-throughput phenotyping-amenable canopy spectral reflectance measurements can be used for association mapping.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 29%
Researcher 10 17%
Student > Master 5 9%
Student > Bachelor 3 5%
Student > Postgraduate 3 5%
Other 7 12%
Unknown 13 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 52%
Biochemistry, Genetics and Molecular Biology 4 7%
Environmental Science 2 3%
Chemical Engineering 1 2%
Business, Management and Accounting 1 2%
Other 3 5%
Unknown 17 29%
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 18 November 2016.
All research outputs
#14,576,697
of 24,456,171 outputs
Outputs from BMC Plant Biology
#1,045
of 3,433 outputs
Outputs of similar age
#210,185
of 375,278 outputs
Outputs of similar age from BMC Plant Biology
#18
of 46 outputs
Altmetric has tracked 24,456,171 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,433 research outputs from this source. They receive a mean Attention Score of 3.0. This one has gotten more attention than average, scoring higher than 67% 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 375,278 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
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 gotten more attention than average, scoring higher than 63% of its contemporaries.