Potato Tuber Shape Phenotyping Using RGB Imaging

Abstract

Potato tuber shape is an important quality trait for breeding and variety development. Length to width (L/W) ratio is a commonly used method to score potato tubers for suitability for different markets and is relatively easy to measure, though labor intensive when done manually. L/W also does not adequately capture secondary growth and other tuber malformations that contribute to tuber shape. Tuber shape has a genetic component and is a prime target for early breeding selection. In the current study we developed an image analysis pipeline to extract tuber shape statistics from images taken using inexpensive, commercially available cameras. The image processing pipeline was used to evaluate greenhouse grown tubers from 32 unique crosses. Tubers from greenhouse grown plants were then grown in a field located in Vauxhall, AB, Canada, and evaluated for tuber shape. Randomly selected tuber images were also shown to industry agronomists and potato growers located in Southern Alberta and their shape scored for suitability for processing (French fry and chipping) markets. Based on measurements taken from greenhouse grown tubers we were able to classify whether mean tuber shape from field grown plants were within ideal shape parameters for processing markets with ~76–86% accuracy. Based on performance of progeny we identified parents which show higher breeding value for tuber shape.

Keywords

• potato
• plant phenotyping
• remote sensing
• imaging
• plant breeding