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Article

Methodology for Determining the Main Physical Parameters of Apples by Digital Image Analysis

by
Jakhfer Alikhanov
1,
Aidar Moldazhanov
1,
Akmaral Kulmakhambetova
1,
Dimitriy Zinchenko
1,
Alisher Nurtuleuov
1,
Zhandos Shynybay
2,
Tsvetelina Georgieva
3 and
Plamen Daskalov
3,*
1
Department of Energy Saving and Automation, Kazakh National Agrarian Research University, 8 Abay St., Almaty 050010, Kazakhstan
2
Department of Power Supply and Electric Drive, Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev (AUPET), Baitursynov St. office 126/1, Almaty 050013, Kazakhstan
3
Department of Automatics and Electronics, University of Ruse, 8 Studentska St., 7017 Ruse, Bulgaria
*
Author to whom correspondence should be addressed.
AgriEngineering 2025, 7(3), 57; https://doi.org/10.3390/agriengineering7030057
Submission received: 17 December 2024 / Revised: 9 February 2025 / Accepted: 18 February 2025 / Published: 25 February 2025
(This article belongs to the Collection Exploring the Application of Artificial Intelligence and Image Processing in Agriculture)
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Abstract

This paper presents the validation of a digital image analysis method for the quantitative determination of physical quality parameters of apples by comparative analysis with a traditional measurement method. The method was used to determine the quality indicators of apples based on digital image analysis in accordance with standard requirements. Five popular apple varieties from Kazakhstan were selected for the study: Aport Alexander, Ainur, Sinap Almaty, Nursat and Kazakhskij Yubilejnyj. The parameters of the five apple varieties were measured both manually and digitally, which revealed close agreement between the obtained values. The analysis of the results of measuring the geometric parameters of the apples and the percentage of red color in the images was carried out. The maximum relative errors in determining the diameters (d, D) and height (h) were 2.99%, 3.03% and 4.12%, respectively. Regression models were developed to predict the weight and volume of apples. The best results in weight prediction were obtained for the Sinap Almatinsky variety using stepwise linear regression (R2 = 0.96), and volume prediction showed the best results for the Nursat variety (R2 = 0.92). This study lays the foundation for the development of automated systems for sorting apples by commercial varieties.
Keywords: apple; fruit; variety; apple physical parameters; methodology; digital image analysis apple; fruit; variety; apple physical parameters; methodology; digital image analysis

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MDPI and ACS Style

Alikhanov, J.; Moldazhanov, A.; Kulmakhambetova, A.; Zinchenko, D.; Nurtuleuov, A.; Shynybay, Z.; Georgieva, T.; Daskalov, P. Methodology for Determining the Main Physical Parameters of Apples by Digital Image Analysis. AgriEngineering 2025, 7, 57. https://doi.org/10.3390/agriengineering7030057

AMA Style

Alikhanov J, Moldazhanov A, Kulmakhambetova A, Zinchenko D, Nurtuleuov A, Shynybay Z, Georgieva T, Daskalov P. Methodology for Determining the Main Physical Parameters of Apples by Digital Image Analysis. AgriEngineering. 2025; 7(3):57. https://doi.org/10.3390/agriengineering7030057

Chicago/Turabian Style

Alikhanov, Jakhfer, Aidar Moldazhanov, Akmaral Kulmakhambetova, Dimitriy Zinchenko, Alisher Nurtuleuov, Zhandos Shynybay, Tsvetelina Georgieva, and Plamen Daskalov. 2025. "Methodology for Determining the Main Physical Parameters of Apples by Digital Image Analysis" AgriEngineering 7, no. 3: 57. https://doi.org/10.3390/agriengineering7030057

APA Style

Alikhanov, J., Moldazhanov, A., Kulmakhambetova, A., Zinchenko, D., Nurtuleuov, A., Shynybay, Z., Georgieva, T., & Daskalov, P. (2025). Methodology for Determining the Main Physical Parameters of Apples by Digital Image Analysis. AgriEngineering, 7(3), 57. https://doi.org/10.3390/agriengineering7030057

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