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.
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The authors give their thanks to research vineyard managers John Thull, Jennifer Thull, and Colin Zumwalde for maintaining our populations, to undergraduate assistants Stien Iverson and David Tork who helped with data collection, and to Dr. Soon Li Teh and Dr. James Luby, who curated the GE1025 linkage map. This work was supported by the VitisGen2 project, which is funded by a Specialty Crop Research Initiative (SCRI) Competitive Grant [Award No. 2017-51181-26829] of the United States Department of Agriculture-National Institute of Food and Agriculture (USDA-NIFA). Funding was also provided by the Minnesota Agricultural Experiment Station.
Copyright © 2020 A. N. Underhill et al. Exclusive Licensee Nanjing Agricultural University. Distributed under a Creative Commons Attribution License (CC BY 4.0).