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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using Nectar-Related Traits to Enhance Crop-Pollinator Interactions
|
|---|---|
| Published in |
Frontiers in Plant Science, June 2018
|
| DOI | 10.3389/fpls.2018.00812 |
| Pubmed ID | |
| Authors |
Jarrad R. Prasifka, Rachel E. Mallinger, Zoe M. Portlas, Brent S. Hulke, Karen K. Fugate, Travis Paradis, Marshall E. Hampton, Clay J. Carter |
| Abstract |
Floral nectar and other reward facilitate crop pollination, and in so doing, increase the amount and breadth of food available for humans. Though abundance and diversity of pollinators (particularly bees) have declined over the past several decades, a concomitant increase in reliance on pollinators presents a challenge to food production. Development of crop varieties with specific nectar or nectar-related traits to attract and retain pollinating insects is an appealing strategy to help address needs of agriculture and pollinators for several reasons. First, many crops have specific traits which have been identified to enhance crop-pollinator interactions. Also, an improved understanding of mechanisms that govern nectar-related traits suggest simplified phenotyping and breeding are possible. Finally, the use of nectar-related traits to enhance crop pollination should complement other measures promoting pollinators and will not limit options for crop production or require any changes by growers (other than planting varieties that are more attractive or rewarding to pollinators). In this article, we review the rationale for improving crop-pollinator interactions, the effects of specific plant traits on pollinator species, and use cultivated sunflowers as a case study. Recent research in sunflower has (i) associated variation in bee visitation with specific floral traits, (ii) quantified benefits of pollinators to hybrid yields, and (iii) used genetic resources in sunflower and other plants to find markers associated with key floral traits. Forthcoming work to increase pollinator rewards should enable sunflower to act as a model for using nectar-related traits to enhance crop-pollinator interactions. |
X Demographics
The data shown below were collected from the profiles of 15 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 | 6 | 40% |
| Sweden | 1 | 7% |
| Australia | 1 | 7% |
| Unknown | 7 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 60% |
| Scientists | 6 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 109 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 20 | 18% |
| Student > Ph. D. Student | 17 | 16% |
| Researcher | 16 | 15% |
| Student > Bachelor | 11 | 10% |
| Student > Doctoral Student | 6 | 6% |
| Other | 8 | 7% |
| Unknown | 31 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 44 | 40% |
| Environmental Science | 9 | 8% |
| Biochemistry, Genetics and Molecular Biology | 9 | 8% |
| Earth and Planetary Sciences | 3 | 3% |
| Computer Science | 2 | 2% |
| Other | 4 | 4% |
| Unknown | 38 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 13 August 2020.
All research outputs
#3,350,575
of 24,008,549 outputs
Outputs from Frontiers in Plant Science
#1,723
of 22,380 outputs
Outputs of similar age
#66,449
of 331,704 outputs
Outputs of similar age from Frontiers in Plant Science
#48
of 470 outputs
Altmetric has tracked 24,008,549 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,380 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 92% 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 331,704 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 79% of its contemporaries.
We're also able to compare this research output to 470 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 90% of its contemporaries.