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Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Author

Listed:
  • Andrzej Przybylak

    (Institute of Biosystems Engineering, Faculty of Agronomy and Bioengineering, Poznan University of Life Sciences, ul. Wojska Polskiego 28, 60-637 Poznan, Poland)

  • Radosław Kozłowski

    (Institute of Biosystems Engineering, Faculty of Agronomy and Bioengineering, Poznan University of Life Sciences, ul. Wojska Polskiego 28, 60-637 Poznan, Poland)

  • Ewa Osuch

    (Institute of Biosystems Engineering, Faculty of Agronomy and Bioengineering, Poznan University of Life Sciences, ul. Wojska Polskiego 28, 60-637 Poznan, Poland)

  • Andrzej Osuch

    (Institute of Biosystems Engineering, Faculty of Agronomy and Bioengineering, Poznan University of Life Sciences, ul. Wojska Polskiego 28, 60-637 Poznan, Poland)

  • Piotr Rybacki

    (Institute of Biosystems Engineering, Faculty of Agronomy and Bioengineering, Poznan University of Life Sciences, ul. Wojska Polskiego 28, 60-637 Poznan, Poland)

  • Przemysław Przygodziński

    (Institute of Biosystems Engineering, Faculty of Agronomy and Bioengineering, Poznan University of Life Sciences, ul. Wojska Polskiego 28, 60-637 Poznan, Poland)

Abstract

This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room.

Suggested Citation

  • Andrzej Przybylak & Radosław Kozłowski & Ewa Osuch & Andrzej Osuch & Piotr Rybacki & Przemysław Przygodziński, 2020. "Quality Evaluation of Potato Tubers Using Neural Image Analysis Method," Agriculture, MDPI, vol. 10(4), pages 1-11, April.
    • Handle: RePEc:gam:jagris:v:10:y:2020:i:4:p:112-:d:341404
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    References listed on IDEAS

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    1. Piotr Boniecki & Krzysztof Koszela & Krzysztof Świerczyński & Jacek Skwarcz & Maciej Zaborowicz & Jacek Przybył, 2020. "Neural Visual Detection of Grain Weevil ( Sitophilus granarius L.)," Agriculture, MDPI, vol. 10(1), pages 1-9, January.
    2. Tomasz Jakubowski & Jolanta B. Królczyk, 2020. "Method for the Reduction of Natural Losses of Potato Tubers During their Long-Term Storage," Sustainability, MDPI, vol. 12(3), pages 1-12, February.
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    Cited by:

    1. Alper Taner & Yeşim Benal Öztekin & Hüseyin Duran, 2021. "Performance Analysis of Deep Learning CNN Models for Variety Classification in Hazelnut," Sustainability, MDPI, vol. 13(12), pages 1-13, June.
    2. Yang Li & Xuewei Chao, 2020. "ANN-Based Continual Classification in Agriculture," Agriculture, MDPI, vol. 10(5), pages 1-15, May.

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