↓ Skip to main content

Increasing cotton lint yield and water use efficiency for subsurface drip irrigation without mulching

Overview of attention for article published in Frontiers in Plant Science, July 2024
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
2 X users
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Increasing cotton lint yield and water use efficiency for subsurface drip irrigation without mulching
Published in
Frontiers in Plant Science, July 2024
DOI 10.3389/fpls.2024.1433719
Pubmed ID
Authors

Nan-nan Li, Jun-hong Li, Xiao-juan Shi, Feng Shi, Yu Tian, Jun Wang, Xian-zhe Hao, Hong-hai Luo, Zhan-biao Wang

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 July 2024.
All research outputs
#17,989,033
of 26,398,142 outputs
Outputs from Frontiers in Plant Science
#13,093
of 25,196 outputs
Outputs of similar age
#77,166
of 157,804 outputs
Outputs of similar age from Frontiers in Plant Science
#44
of 186 outputs
Altmetric has tracked 26,398,142 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 25,196 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
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 157,804 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 50% of its contemporaries.
We're also able to compare this research output to 186 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.