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Attention Score in Context
| Title |
Speed breeding for multiple quantitative traits in durum wheat
|
|---|---|
| Published in |
Plant Methods, May 2018
|
| DOI | 10.1186/s13007-018-0302-y |
| Pubmed ID | |
| Authors |
Samir Alahmad, Eric Dinglasan, Kung Ming Leung, Adnan Riaz, Nora Derbal, Kai P. Voss-Fels, Jason A. Able, Filippo M. Bassi, Jack Christopher, Lee T. Hickey |
| Abstract |
Plant breeding requires numerous generations to be cycled and evaluated before an improved cultivar is released. This lengthy process is required to introduce and test multiple traits of interest. However, a technology for rapid generation advance named 'speed breeding' was successfully deployed in bread wheat (Triticum aestivum L.) to achieve six generations per year while imposing phenotypic selection for foliar disease resistance and grain dormancy. Here, for the first time the deployment of this methodology is presented in durum wheat (Triticum durum Desf.) by integrating selection for key traits, including above and below ground traits on the same set of plants. This involved phenotyping for seminal root angle (RA), seminal root number (RN), tolerance to crown rot (CR), resistance to leaf rust (LR) and plant height (PH). In durum wheat, these traits are desirable in environments where yield is limited by in-season rainfall with the occurrence of CR and epidemics of LR. To evaluate this multi-trait screening approach, we applied selection to a large segregating F2 population (n = 1000) derived from a bi-parental cross (Outrob4/Caparoi). A weighted selection index (SI) was developed and applied. The gain for each trait was determined by evaluating F3 progeny derived from 100 'selected' and 100 'unselected' F2 individuals. Transgressive segregation was observed for all assayed traits in the Outrob4/Caparoi F2 population. Application of the SI successfully shifted the population mean for four traits, as determined by a significant mean difference between 'selected' and 'unselected' F3 families for CR tolerance, LR resistance, RA and RN. No significant shift for PH was observed. The novel multi-trait phenotyping method presents a useful tool for rapid selection of early filial generations or for the characterization of fixed lines out-of-season. Further, it offers efficient use of resources by assaying multiple traits on the same set of plants. Results suggest that when performed in parallel with speed breeding in early generations, selection will enrich recombinant inbred lines with desirable alleles and will reduce the length and number of years required to combine these traits in elite breeding populations and therefore cultivars. |
X Demographics
The data shown below were collected from the profiles of 44 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 8 | 18% |
| United Kingdom | 6 | 14% |
| United States | 3 | 7% |
| Mexico | 2 | 5% |
| Germany | 2 | 5% |
| Austria | 1 | 2% |
| Canada | 1 | 2% |
| Libya | 1 | 2% |
| Italy | 1 | 2% |
| Other | 6 | 14% |
| Unknown | 13 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 25 | 57% |
| Scientists | 16 | 36% |
| Practitioners (doctors, other healthcare professionals) | 2 | 5% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 169 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 29 | 17% |
| Researcher | 28 | 17% |
| Student > Bachelor | 17 | 10% |
| Student > Master | 12 | 7% |
| Student > Doctoral Student | 8 | 5% |
| Other | 11 | 7% |
| Unknown | 64 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 80 | 47% |
| Biochemistry, Genetics and Molecular Biology | 13 | 8% |
| Engineering | 3 | 2% |
| Psychology | 2 | 1% |
| Arts and Humanities | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 66 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 27. 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 26 May 2020.
All research outputs
#1,369,992
of 24,891,087 outputs
Outputs from Plant Methods
#52
of 1,215 outputs
Outputs of similar age
#29,515
of 333,076 outputs
Outputs of similar age from Plant Methods
#4
of 23 outputs
Altmetric has tracked 24,891,087 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,215 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. 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 333,076 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.