Digital Methodology for Determining the Main Physical Parameters of Apple Fruits

Abstract

This paper presents the validation of a numerical method for quantifying the physical quality parameters of apples through a comparative analysis with a traditional measurement method. The numerical method was applied to determine the parameters of batches of Kazakh apples according to standard requirements, using image analysis of apples. Five common varieties of Kazakh apples were selected: Aport Alexander, Ainur, Sinap Almatynski, Nursat and Kazakhski Yubileinyi. The geometric parameters of the apples and the percentage of red in the images were determined. The parameters of the 5 apple varieties were processed and measured both manually and digitally, revealing a close agreement between the obtained values. The developed digital method achieved high accuracy in determining the (diameters (d) and (D) in two perpendicular planes and height (h) of each apple), with maximum relative errors of 2.99% for (d), 3.03%, and 4.12% for the (h), and (D) parameters, respectively. Regression models were developed to determine and predict the mass and volume of apples via the digital method. The best results for the apple weight prediction were obtained for Sinap Almatynski variety by stepwise linear regression, and for the apple volume prediction were obtained for Nursat variety by linear regression. Regression equations for mass, volume and geometric dimensions constitute the basis for the development of a small instrument for automatically sorting apples by commercial variety.

Plant phenotyping relevance

リンゴ果実の画像解析による形状・色・質量・体積推定法を開発し、手動測定と比較検証しており、植物器官の表現型取得が中心である。

Code and data availability

The paper describes apple image-based phenotyping (geometric parameters, redness percentage, mass/volume regression models) but provides no public dataset, images, code, or models. The Data Availability Statement explicitly withholds raw/processed data, offering it only upon request, and no public repository or URL for

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