| Title |
Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets
|
|---|---|
| Published in |
BMC Research Notes, July 2018
|
| DOI | 10.1186/s13104-018-3508-1 |
| Pubmed ID | |
| Authors |
Naser AlKhalifah, Darwin A. Campbell, Celeste M. Falcon, Jack M. Gardiner, Nathan D. Miller, Maria Cinta Romay, Ramona Walls, Renee Walton, Cheng-Ting Yeh, Martin Bohn, Jessica Bubert, Edward S. Buckler, Ignacio Ciampitti, Sherry Flint-Garcia, Michael A. Gore, Christopher Graham, Candice Hirsch, James B. Holland, David Hooker, Shawn Kaeppler, Joseph Knoll, Nick Lauter, Elizabeth C. Lee, Aaron Lorenz, Jonathan P. Lynch, Stephen P. Moose, Seth C. Murray, Rebecca Nelson, Torbert Rocheford, Oscar Rodriguez, James C. Schnable, Brian Scully, Margaret Smith, Nathan Springer, Peter Thomison, Mitchell Tuinstra, Randall J. Wisser, Wenwei Xu, David Ertl, Patrick S. Schnable, Natalia De Leon, Edgar P. Spalding, Jode Edwards, Carolyn J. Lawrence-Dill |
| Abstract |
Crop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids. G2F's genotype by environment project has released 2014 and 2015 datasets to the public, with 2016 and 2017 collected and soon to be made available. Datasets include DNA sequences; traditional phenotype descriptions, as well as detailed ear, cob, and kernel phenotypes quantified by image analysis; weather station measurements; and soil characterizations by site. Data are released as comma separated value spreadsheets accompanied by extensive README text descriptions. For genotypic and phenotypic data, both raw data and a version with outliers removed are reported. For weather data, two versions are reported: a full dataset calibrated against nearby National Weather Service sites and a second calibrated set with outliers and apparent artifacts removed. |
X Demographics
The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 41% |
| United Kingdom | 2 | 12% |
| Argentina | 1 | 6% |
| Brazil | 1 | 6% |
| Unknown | 6 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 59% |
| Scientists | 6 | 35% |
| Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 53 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 21% |
| Researcher | 11 | 21% |
| Professor > Associate Professor | 6 | 11% |
| Student > Master | 5 | 9% |
| Student > Doctoral Student | 4 | 8% |
| Other | 6 | 11% |
| Unknown | 10 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 58% |
| Arts and Humanities | 1 | 2% |
| Unspecified | 1 | 2% |
| Mathematics | 1 | 2% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 5 | 9% |
| Unknown | 13 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 14 August 2018.
All research outputs
#4,158,511
of 25,721,020 outputs
Outputs from BMC Research Notes
#576
of 4,525 outputs
Outputs of similar age
#72,780
of 340,696 outputs
Outputs of similar age from BMC Research Notes
#12
of 141 outputs
Altmetric has tracked 25,721,020 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,525 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done well, scoring higher than 87% 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 340,696 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 78% of its contemporaries.
We're also able to compare this research output to 141 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.