ArticlePlant phenomics (Washington, D.C.)2020
Evaluating and Mapping Grape Color Using Image-Based Phenotyping.
Article in Plant phenomics (Washington, D.C.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 24 citations in OpenAlex.
- Two noir juice color-associated markers identified from a 'Chambourcin'-based population demonstrate broad applicability acrossFrontiers in plant science · 2026Article
- Multi-objective RGB-D fusion network for non-destructive strawberry trait assessment.Frontiers in plant science · 2025Article
- Computer Vision-Based Fire-Ice Ion Algorithm for Rapid and Nondestructive Authentication of Ziziphi Spinosae Semen and Its Counterfeits.Foods (Basel, Switzerland) · 2024Article
- Tracing the color: quantitative trait loci analysis reveals new insights into red-flesh pigmentation in apple (Horticulture research · 2024Article
- Image analysis and polyphenol profiling unveil red-flesh apple phenotype complexity.Plant methods · 2024Article
- Segment Anything for Comprehensive Analysis of Grapevine Cluster Architecture and Berry Properties.Plant phenomics (Washington, D.C.) · 2024Article
- A high-density linkage map construction in guava (Frontiers in plant science · 2024Article
- Leaf Color Classification and Expression Analysis of Photosynthesis-Related Genes in Inbred Lines of Chinese Cabbage Displaying Minor Variations in Dark-Green Leaves.Plants (Basel, Switzerland) · 2023Article
- Image-Based High-Throughput Phenotyping in Horticultural Crops.Plants (Basel, Switzerland) · 2023Review
- Multi-Source Data Fusion Improves Time-Series Phenotype Accuracy in Maize under a Field High-Throughput Phenotyping Platform.Plant phenomics (Washington, D.C.) · 2023Article
- Image-based phenotyping to estimate anthocyanin concentrations in lettuce.Frontiers in plant science · 2023Article
- Phenotyping Key Fruit Quality Traits in Olive Using RGB Images and Back Propagation Neural Networks.Plant phenomics (Washington, D.C.) · 2023Article
- Zinc Biofortification inPlants (Basel, Switzerland) · 2022Article
- Quantitative dissection of color patterning in the foliar ornamental coleus.Plant physiology · 2021Article
- Review
- Evaluation of Biochemical Juice Attributes and Color-Related Traits in Muscadine Grape Population.Foods (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Grape berry color is an economically important trait that is controlled by two major genes influencing anthocyanin synthesis in the skin. Color is often described qualitatively using six major categories; however, this is a subjective rating that often fails to describe variation within these six classes. To investigate minor genes influencing berry color, image analysis was used to quantify berry color using different color spaces. An image analysis pipeline was developed and utilized to quantify color in a segregating hybrid wine grape population across two years. Images were collected from grape clusters immediately after harvest and segmented by color to determine the red, green, and blue (RGB); hue, saturation, and intensity (HSI); and lightness, red-green, and blue-yellow values (L∗a∗b∗) of berries. QTL analysis identified known major QTL for color on chromosome 2 along with several previously unreported smaller-effect QTL on chromosomes 1, 5, 6, 7, 10, 15, 18, and 19. This study demonstrated the ability of an image analysis phenotyping system to characterize berry color and to more effectively capture variability within a population and identify genetic regions of interest.
Identifiers
What OpenQuestion holds
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.