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A new image-based tool for the high throughput phenotyping of pollen viability: evaluation of inter- and intra-cultivar diversity in grapevine

Overview of attention for article published in Plant Methods, January 2018
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
A new image-based tool for the high throughput phenotyping of pollen viability: evaluation of inter- and intra-cultivar diversity in grapevine
Published in
Plant Methods, January 2018
DOI 10.1186/s13007-017-0267-2
Pubmed ID
Authors

Javier Tello, María Ignacia Montemayor, Astrid Forneck, Javier Ibáñez

Abstract

Low pollen viability may limit grapevine yield under certain conditions, causing relevant economic losses to grape-growers. It is usually evaluated by the quantification of the number of viable and non-viable pollen grains that are present in a sample after an adequate pollen grain staining procedure. Although the manual counting of both types of grains is the simplest and most sensitive approach, it is a laborious and time-demanding process. In this regard, novel image-based approaches can assist in the objective, accurate and cost-effective phenotyping of this trait. Here, we introduce PollenCounter, an open-source macro implemented as a customizable Fiji tool for the high-throughput phenotyping of pollen viability. This tool splits RGB images of stained pollen grains into its primary channels, retaining red and green color fractionated images (which contain information on total and only viable pollen grains, respectively) for the subsequent isolation and counting of the regions of interest (pollen grains). This framework was successfully used for the analysis of pollen viability of a high number of samples collected in a large collection of grapevine cultivars. Results revealed a great genetic variability, from cultivars having very low pollen viability (like Corinto Bianco; viability: 14.1 ± 1.3%) to others with a very low presence of sterile pollen grains (Cuelga; viability: 98.2 ± 0.5%). A wide range of variability was also observed among several clones of cv. Tempranillo Tinto (from 97.9 ± 0.9 to 60.6 ± 5.9%, in the first season). Interestingly, the evaluation of this trait in a second season revealed differential genotype-specific sensitivity to environment. The use of PollenCounter is expected to aid in different areas, including genetics research studies, crop improvement and breeding strategies that need of fast, precise and accurate results. Considering its flexibility, it can be used not only in grapevine, but also in other species showing a differential staining of viable and non-viable pollen grains. The wide phenotypic diversity observed at a species level, together with the identification of specific cultivars and clones largely differing in this trait, pave the way of further analyses aimed to understand the physiological and genetic causes driving to male sterility in grapevine.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 105 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 18%
Researcher 17 16%
Student > Ph. D. Student 11 10%
Student > Doctoral Student 7 7%
Student > Bachelor 5 5%
Other 12 11%
Unknown 34 32%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 40%
Biochemistry, Genetics and Molecular Biology 11 10%
Environmental Science 4 4%
Computer Science 4 4%
Engineering 3 3%
Other 5 5%
Unknown 36 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 04 June 2020.
All research outputs
#6,035,575
of 23,015,156 outputs
Outputs from Plant Methods
#343
of 1,088 outputs
Outputs of similar age
#121,611
of 443,107 outputs
Outputs of similar age from Plant Methods
#7
of 31 outputs
Altmetric has tracked 23,015,156 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 1,088 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 gotten more attention than average, scoring higher than 68% 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 443,107 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 72% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.