ArticleApplications in plant sciences
A pipeline for the rapid collection of color data from photographs.
Article in Applications in plant sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Integrating Genomics, Collections, and Community Science to Delimit Species Clarifies the Taxonomy of a Variable Monitor Lizard (Varanus tristis).Systematic biology · 2026Article
- Using large-scale community science data and computer vision to evaluate thermoregulation as an adaptive driver of physiological color change in Anolis carolinensis.Frontiers in zoology · 2025Article
- Delayed flowering phenology of red-flowering plants in response to hummingbird migration.Current biology : CB · 2025Article
- A pipeline for the rapid collection of color data from photographs.Applications in plant sciencesArticle
- Spatially resolved detection of small molecules from press-dried plant tissue using MALDI imaging.Applications in plant sciencesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Premise: There are relatively few studies of flower color at landscape scales that can address the relative importance of competing mechanisms (e.g., biotic: pollinators; abiotic: ultraviolet radiation, drought stress) at landscape scales. Methods: We developed an R shiny pipeline to sample color from images that were automatically downloaded using query results from a search using iNaturalist or the Global Biodiversity Information Facility (GBIF). The pipeline was used to sample ca. 4800 North American wallflower ( Results: Flower color was strongly non-randomly distributed spatially, but did not correlate strongly with climate, with most of the variation explained instead by spatial autocorrelation. However, finer-scale patterns including local correlations between elevation and color were observed. Analyses using color-calibrated and raw images revealed similar results. Discussion: This pipeline provides users the ability to rapidly capture color data from iNaturalist images and can be a useful tool in detecting spatial or temporal changes in color using citizen science data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.