The use of digital cameras in plant phenotyping studies using RGB sensors has increased. However, the need for standardization has become apparent because of the diverse analytical approaches used by individual researchers. In this study, we optimized the image acquisition conditions for apples, including scaling tool positioning, lighting conditions, and background color selection. In addition, we developed an ImageJ-based automated image acquisition and analysis program. We generated 240 images of four apple cultivars (Hongan, Hongro, Fuji, and Hwangok) and used 12 image indices to analyze the fruit size, width, length, and shape. We measured the accuracy by comparing the results with actual measurements. Significantly high correlation values were observed between fruit width and the major index (R2=0.947-0.993) as well as between fruit length and the height index (R2=0.964-0.984) based on the analysis using R-squared values to assess accuracy. These findings are expected to enhance the efficiency of apple fruit sorting in the future and can be applied to investigate the shapes of other fruits.
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