Unverified paper record
ColourQuant: A High-Throughput Technique to Extract and Quantify Color Phenotypes from Plant Images.
Methods in molecular biology (Clifton, N.J.) · 1 Jan 2022 · 10.1007/978-1-0716-2537-8_9
Abstract
Color patterning contributes to important plant traits that influence ecological interactions, horticultural breeding, and agricultural performance. High-throughput phenotyping of color is valuable for understanding plant biology and selecting for traits related to color during plant breeding. Here we present ColourQuant, an automated high-throughput pipeline that allows users to extract color phenotypes from images. This pipeline includes methods for color phenotyping using mean pixel values, a Gaussian density estimator of CIELAB color, and the analysis of shape-independent color patterning by circular deformation.
Plant phenotyping relevance
植物画像から色形質を自動抽出・定量する高スループット解析パイプラインの開発が研究の中心であり、植物表現型計測法に該当する。
abstractHere we present ColourQuant, an automated high-throughput pipeline that allows users to extract color phenotypes from images.
abstractThis pipeline includes methods for color phenotyping using mean pixel values, a Gaussian density estimator of CIELAB color, and the analysis of shape-independent color patterning by circular deformation.
Code and data availability
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