| Title |
High-throughput phenotyping platforms enhance genomic selection for wheat grain yield across populations and cycles in early stage
|
|---|---|
| Published in |
Theoretical and Applied Genetics, February 2019
|
| DOI | 10.1007/s00122-019-03309-0 |
| Pubmed ID | |
| Authors |
Jin Sun, Jesse A. Poland, Suchismita Mondal, José Crossa, Philomin Juliana, Ravi P. Singh, Jessica E. Rutkoski, Jean-Luc Jannink, Leonardo Crespo-Herrera, Govindan Velu, Julio Huerta-Espino, Mark E. Sorrells |
X Demographics
The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 14% |
| United Kingdom | 2 | 14% |
| Australia | 1 | 7% |
| Finland | 1 | 7% |
| Turkey | 1 | 7% |
| United States | 1 | 7% |
| India | 1 | 7% |
| Sweden | 1 | 7% |
| Unknown | 4 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 50% |
| Members of the public | 6 | 43% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 142 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 29 | 20% |
| Researcher | 24 | 17% |
| Student > Master | 17 | 12% |
| Student > Bachelor | 8 | 6% |
| Professor > Associate Professor | 6 | 4% |
| Other | 19 | 13% |
| Unknown | 39 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 79 | 56% |
| Biochemistry, Genetics and Molecular Biology | 7 | 5% |
| Medicine and Dentistry | 3 | 2% |
| Engineering | 2 | 1% |
| Environmental Science | 1 | <1% |
| Other | 4 | 3% |
| Unknown | 46 | 32% |
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 09 September 2019.
All research outputs
#4,383,473
of 23,794,258 outputs
Outputs from Theoretical and Applied Genetics
#593
of 3,565 outputs
Outputs of similar age
#91,103
of 354,077 outputs
Outputs of similar age from Theoretical and Applied Genetics
#14
of 55 outputs
Altmetric has tracked 23,794,258 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,565 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 83% 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 354,077 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 55 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 72% of its contemporaries.