Bi-dimensional Image Analysis for the Phenotypic Evaluation of Russet in Asian Pear (Pyrus spp.)

Abstract

Russet, one of the fruit skin colors of Asian pears, affects the fruit's commercial value.A precise phenotyping method is required because fruit skin colors occur irregularly in various pear cultivars.Here, we propose a bi-dimensional image analysis to evaluate the russet of pear skin accurately and effectively by comparing the results of image analysis with the Hunter a value.The fruits of 'Whangkeumbae' (non-russet), 'Minibae' (russet), and their F 1 individuals were used for russet evaluation.The Hunter a value was measured using a color-difference meter.The russet coverage (%) was calculated using Photoshop software.In F 1 individuals derived from 'Whangkeumbae' × 'Minibae', the Hunter a value represented normal distribution, and the russet coverage distributed variously.The positive correlation coefficients between the Hunter a value and russet coverage was confirmed (r > 0.7).Although several F 1 individuals showed abundant russet formation, they showed a negative Hunter a value.Therefore, the bi-dimensional image analysis more accurately evaluated russet in pear fruit skin than did the Hunter a value.The bi-dimensional image analysis could be used for high-throughput phenotyping in pears.

Plant phenotyping relevance

ナシ果皮のさび（russet）被覆率を画像解析で定量する手法を提案・比較検証しており、植物形質取得法が研究の中心である。

Code and data availability

The article describes russet phenotyping of pear fruits via Hunter a values and Photoshop-based image analysis, but contains no data availability statement, no public phenotype/image dataset, no deposited code or workflow, and no supplement reference. Analysis was done in Photoshop, RStudio, and Excel with no author-de

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