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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Investigation of the Influence of Leaf Thickness on Canopy Reflectance and Physiological Traits in Upland and Pima Cotton Populations
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|---|---|
| Published in |
Frontiers in Plant Science, August 2017
|
| DOI | 10.3389/fpls.2017.01405 |
| Pubmed ID | |
| Authors |
Duke Pauli, Jeffrey W White, Pedro Andrade-Sanchez, Matthew M Conley, John Heun, Kelly R Thorp, Andrew N French, Douglas J Hunsaker, Elizabete Carmo-Silva, Guangyao Wang, Michael A Gore |
| Abstract |
Many systems for field-based, high-throughput phenotyping (FB-HTP) quantify and characterize the reflected radiation from the crop canopy to derive phenotypes, as well as infer plant function and health status. However, given the technology's nascent status, it remains unknown how biophysical and physiological properties of the plant canopy impact downstream interpretation and application of canopy reflectance data. In that light, we assessed relationships between leaf thickness and several canopy-associated traits, including normalized difference vegetation index (NDVI), which was collected via active reflectance sensors carried on a mobile FB-HTP system, carbon isotope discrimination (CID), and chlorophyll content. To investigate the relationships among traits, two distinct cotton populations, an upland (Gossypium hirsutum L.) recombinant inbred line (RIL) population of 95 lines and a Pima (G. barbadense L.) population composed of 25 diverse cultivars, were evaluated under contrasting irrigation regimes, water-limited (WL) and well-watered (WW) conditions, across 3 years. We detected four quantitative trait loci (QTL) and significant variation in both populations for leaf thickness among genotypes as well as high estimates of broad-sense heritability (on average, above 0.7 for both populations), indicating a strong genetic basis for leaf thickness. Strong phenotypic correlations (maximum r = -0.73) were observed between leaf thickness and NDVI in the Pima population, but not the RIL population. Additionally, estimated genotypic correlations within the RIL population for leaf thickness with CID, chlorophyll content, and nitrogen discrimination ([Formula: see text] = -0.32, 0.48, and 0.40, respectively) were all significant under WW but not WL conditions. Economically important fiber quality traits did not exhibit significant phenotypic or genotypic correlations with canopy traits. Overall, our results support considering variation in leaf thickness as a potential contributing factor to variation in NDVI or other canopy traits measured via proximal sensing, and as a trait that impacts fundamental physiological responses of plants. |
X Demographics
The data shown below were collected from the profiles of 8 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 | 2 | 25% |
| Mexico | 1 | 13% |
| United Kingdom | 1 | 13% |
| Unknown | 4 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 50% |
| Scientists | 3 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 71 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 21% |
| Student > Master | 10 | 14% |
| Researcher | 8 | 11% |
| Student > Bachelor | 6 | 8% |
| Student > Doctoral Student | 3 | 4% |
| Other | 1 | 1% |
| Unknown | 28 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 35% |
| Biochemistry, Genetics and Molecular Biology | 7 | 10% |
| Environmental Science | 4 | 6% |
| Mathematics | 1 | 1% |
| Business, Management and Accounting | 1 | 1% |
| Other | 3 | 4% |
| Unknown | 30 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 05 September 2017.
All research outputs
#5,738,865
of 22,997,544 outputs
Outputs from Frontiers in Plant Science
#2,964
of 20,486 outputs
Outputs of similar age
#90,847
of 318,832 outputs
Outputs of similar age from Frontiers in Plant Science
#75
of 497 outputs
Altmetric has tracked 22,997,544 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 20,486 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 85% 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 318,832 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 71% of its contemporaries.
We're also able to compare this research output to 497 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.