Evaluating and Mapping Grape Color Using Image-Based Phenotyping

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.

Plant phenotyping relevance

ブドウ果実色を画像解析で定量するパイプラインを開発・適用し、従来の主観評価より集団内変異を捉える手法が中心である。

Code and data availability

The paper's image-processing MATLAB script is publicly available on the authors' GitHub repository. The grape cluster images are deposited in DRUM but only available upon request, so they are not a public asset.