Development of high-precision measurement method of fruit color based on digital image analysis

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In breeding and in pre- and postharvest studies of fruit color, an effective method for evaluating color is needed to replace subjective evaluations by eye. We used a series of data processing and statistical analyses used in content-based image retrieval to evaluate melon and strawberry flesh color, and assessed the efficacy of this approach. This method relies on summarizing color information from images into color signatures, calculating the earth mover's distance (EMD) between color signatures, and multi-dimensional scaling based on an EMD matrix. This method revealed important color features, such as the yellowish-green strength in green-fleshed melons, the relative size of the green and red parts in red-fleshed melons, and the relative size of the white and red parts in strawberry flesh, without the need for an explicit definition of these features. Moreover, this new method performed better at detecting color differences among cultivars than traditional evaluation methods. The method provides effective, objective indicators of fruit color, and shows considerable promise for use in research and breeding programs.