Research Article | Open Access
Volume 2020 |Article ID 8086309 | https://doi.org/10.34133/2020/8086309

Evaluating and Mapping Grape Color Using Image-Based Phenotyping

A. N. UnderhilliD ,1 C. D. HirschiD ,2 and M. D. Clark iD 1

1Department of Horticultural Science, University of Minnesota, St. Paul, MN, USA
2Department of Plant Pathology, University of Minnesota, St. Paul, MN, USA

Received 
25 Nov 2019
Accepted 
05 Apr 2020
Published
24 Apr 2020

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 () 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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