Evaluating and Mapping Grape Color Using Image-Based Phenotyping.

Area of Science:

• Plant genetics
• Agricultural science
• Bioinformatics

Background:

• Grape berry color is crucial for wine quality and is primarily controlled by major genes affecting anthocyanin synthesis.
• Qualitative color descriptions are subjective and fail to capture the full spectrum of variation within grape populations.
• Investigating minor genes is essential for a comprehensive understanding of berry color genetics.

Purpose of the Study:

• To develop and apply an image analysis pipeline for precise quantification of grape berry color.
• To identify quantitative trait loci (QTL) associated with minor genes influencing berry color variation.
• To demonstrate the utility of advanced phenotyping for genetic studies in grapes.

Main Methods:

• Developed an image analysis pipeline to quantify berry color using RGB, HSI, and L*a*b* color spaces.
• Collected and analyzed images from a segregating hybrid wine grape population over two years.
• Performed QTL analysis to map genetic regions influencing berry color.

Main Results:

• Identified known major QTL for grape color on chromosome 2.
• Discovered several novel, smaller-effect QTL for berry color on chromosomes 1, 5, 6, 7, 10, 15, 18, and 19.
• The image analysis system effectively captured berry color variability.

Conclusions:

• Image analysis provides a robust phenotyping method for grape berry color characterization.
• This approach enhances the ability to identify minor genes and genetic regions controlling complex traits like berry color.
• Advanced phenotyping is valuable for dissecting the genetic architecture of economically important traits in crops.