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Attention Score in Context
| Title |
Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize
|
|---|---|
| Published in |
Plant Methods, June 2015
|
| DOI | 10.1186/s13007-015-0078-2 |
| Pubmed ID | |
| Authors |
M Zaman-Allah, O Vergara, J L Araus, A Tarekegne, C Magorokosho, P J Zarco-Tejada, A Hornero, A Hernández Albà, B Das, P Craufurd, M Olsen, B M Prasanna, J Cairns |
| Abstract |
Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement. We present the use of a UAP equipped with sensors for multispectral imaging in spatial field variability assessment and phenotyping for low-nitrogen (low-N) stress tolerance in maize. Multispectral aerial images were used to (1) characterize experimental fields for spatial soil-nitrogen variability and (2) derive indices for crop performance under low-N stress. Overall, results showed that the aerial platform enables to effectively characterize spatial field variation and assess crop performance under low-N stress. The Normalized Difference Vegetation Index (NDVI) data derived from spectral imaging presented a strong correlation with ground-measured NDVI, crop senescence index and grain yield. This work suggests that the aerial sensing platform designed for phenotyping studies has the potential to effectively assist in crop genetic improvement against abiotic stresses like low-N provided that sensors have enough resolution for plot level data collection. Limitations and future potential uses are also discussed. |
X Demographics
The data shown below were collected from the profiles of 75 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 | 19 | 25% |
| United Kingdom | 7 | 9% |
| Australia | 4 | 5% |
| Argentina | 3 | 4% |
| Spain | 3 | 4% |
| Netherlands | 2 | 3% |
| Venezuela, Bolivarian Republic of | 2 | 3% |
| Italy | 2 | 3% |
| Ecuador | 2 | 3% |
| Other | 7 | 9% |
| Unknown | 24 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 61 | 81% |
| Scientists | 10 | 13% |
| Science communicators (journalists, bloggers, editors) | 4 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 424 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Belgium | 3 | <1% |
| Colombia | 1 | <1% |
| Australia | 1 | <1% |
| Brazil | 1 | <1% |
| Indonesia | 1 | <1% |
| Canada | 1 | <1% |
| Benin | 1 | <1% |
| Mexico | 1 | <1% |
| Czechia | 1 | <1% |
| Other | 4 | <1% |
| Unknown | 409 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 82 | 19% |
| Student > Ph. D. Student | 73 | 17% |
| Student > Master | 70 | 17% |
| Student > Bachelor | 27 | 6% |
| Student > Doctoral Student | 22 | 5% |
| Other | 62 | 15% |
| Unknown | 88 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 167 | 39% |
| Engineering | 50 | 12% |
| Environmental Science | 29 | 7% |
| Earth and Planetary Sciences | 23 | 5% |
| Computer Science | 17 | 4% |
| Other | 29 | 7% |
| Unknown | 109 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 56. 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 30 March 2017.
All research outputs
#747,307
of 25,253,876 outputs
Outputs from Plant Methods
#16
of 1,243 outputs
Outputs of similar age
#8,503
of 270,300 outputs
Outputs of similar age from Plant Methods
#2
of 4 outputs
Altmetric has tracked 25,253,876 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,243 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done particularly well, scoring higher than 98% 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 270,300 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 96% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.