Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

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....

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Bibliographic Details
Main Authors: Andrzej Przybylak, Radosław Kozłowski, Ewa Osuch, Andrzej Osuch, Piotr Rybacki, Przemysław Przygodziński
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Agriculture
Subjects:
artificial neural network
image analysis
potato tubers quality
neural classification
Online Access:https://www.mdpi.com/2077-0472/10/4/112
Description
Summary: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.
ISSN:2077-0472

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