| Title |
Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat
|
|---|---|
| Published in |
Theoretical and Applied Genetics, October 2018
|
| DOI | 10.1007/s00122-018-3206-3 |
| Pubmed ID | |
| Authors |
Philomin Juliana, Osval A. Montesinos-López, José Crossa, Suchismita Mondal, Lorena González Pérez, Jesse Poland, Julio Huerta-Espino, Leonardo Crespo-Herrera, Velu Govindan, Susanne Dreisigacker, Sandesh Shrestha, Paulino Pérez-Rodríguez, Francisco Pinto Espinosa, Ravi P. Singh |
X Demographics
The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 7% |
| Spain | 2 | 7% |
| China | 1 | 4% |
| Turkey | 1 | 4% |
| United States | 1 | 4% |
| Germany | 1 | 4% |
| Netherlands | 1 | 4% |
| Brazil | 1 | 4% |
| United Kingdom | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 15 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 15 | 56% |
| Members of the public | 11 | 41% |
| Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 158 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 158 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 34 | 22% |
| Researcher | 28 | 18% |
| Student > Master | 15 | 9% |
| Student > Doctoral Student | 13 | 8% |
| Student > Bachelor | 7 | 4% |
| Other | 19 | 12% |
| Unknown | 42 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 88 | 56% |
| Biochemistry, Genetics and Molecular Biology | 8 | 5% |
| Computer Science | 4 | 3% |
| Engineering | 3 | 2% |
| Nursing and Health Professions | 1 | <1% |
| Other | 6 | 4% |
| Unknown | 48 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 27 December 2018.
All research outputs
#2,296,094
of 23,794,258 outputs
Outputs from Theoretical and Applied Genetics
#169
of 3,565 outputs
Outputs of similar age
#49,770
of 351,110 outputs
Outputs of similar age from Theoretical and Applied Genetics
#11
of 66 outputs
Altmetric has tracked 23,794,258 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% 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 particularly well, scoring higher than 95% 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 351,110 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 85% of its contemporaries.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.