Image Analysis Methods in Classifying Selected Malting Barley Varieties by Neural Modelling

Quality evaluation of products is a critical stage in the process of production. It also applies to the production of beer and its main ingredients, i.e., hops, yeast, malting barley and other components. The research described in this paper deals with the multifaceted quality evaluation of malting...

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Main Authors: Agnieszka A. Pilarska, Piotr Boniecki, Małgorzata Idzior-Haufa, Maciej Zaborowicz, Krzysztof Pilarski, Andrzej Przybylak, Hanna Piekarska-Boniecka
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Agriculture
Subjects:
Online Access:https://www.mdpi.com/2077-0472/11/8/732
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spelling doaj-1515713aacd34f458340213c6c57933c2021-08-26T13:25:05ZengMDPI AGAgriculture2077-04722021-08-011173273210.3390/agriculture11080732Image Analysis Methods in Classifying Selected Malting Barley Varieties by Neural ModellingAgnieszka A. Pilarska0Piotr Boniecki1Małgorzata Idzior-Haufa2Maciej Zaborowicz3Krzysztof Pilarski4Andrzej Przybylak5Hanna Piekarska-Boniecka6Department of Plant-Derived Food Technology, Poznań University of Life Sciences, ul. Wojska Polskiego 31, 60-624 Poznan, PolandDepartment of Biosystems Engineering, Poznan University of Life Sciences, ul. Wojska Polskiego 50, 60-627 Poznan, PolandDepartment of Gerodontology and Oral Pathology, Poznan University of Medical Sciences, ul. Bukowska 70, 60-812 Poznan, PolandDepartment of Biosystems Engineering, Poznan University of Life Sciences, ul. Wojska Polskiego 50, 60-627 Poznan, PolandDepartment of Biosystems Engineering, Poznan University of Life Sciences, ul. Wojska Polskiego 50, 60-627 Poznan, PolandDepartment of Biosystems Engineering, Poznan University of Life Sciences, ul. Wojska Polskiego 50, 60-627 Poznan, PolandFaculty of Horticulture and Landscape Architecture, Poznan University of Life Sciences, 60-637 Poznan, PolandQuality evaluation of products is a critical stage in the process of production. It also applies to the production of beer and its main ingredients, i.e., hops, yeast, malting barley and other components. The research described in this paper deals with the multifaceted quality evaluation of malting barley needed for the production of malt. The project aims to elaborate on the original methodology used for identifying grain varieties, grain contamination degree and other visual characteristics of malting barley employing new computer technologies, including artificial intelligence (AI) and neural image analysis. The neural modelling and digital image analysis assist in identifying the quality of barley varieties. According to the study, information concerning the colour of barley varieties presented in digital images is sufficient for this purpose. The multi-layer perceptron (MLP)-type neural network generated using a data set describing the colour of kernels presented in digital images was the best model for recognising the analysed malting barley varieties. The proposed procedure may bring specific benefits to malthouses, influencing the beer production quality in the future.https://www.mdpi.com/2077-0472/11/8/732malting barleyvariety classificationneural processing of imageartificial intelligence methods
collection DOAJ
language English
format Article
sources DOAJ
author Agnieszka A. Pilarska
Piotr Boniecki
Małgorzata Idzior-Haufa
Maciej Zaborowicz
Krzysztof Pilarski
Andrzej Przybylak
Hanna Piekarska-Boniecka
spellingShingle Agnieszka A. Pilarska
Piotr Boniecki
Małgorzata Idzior-Haufa
Maciej Zaborowicz
Krzysztof Pilarski
Andrzej Przybylak
Hanna Piekarska-Boniecka
Image Analysis Methods in Classifying Selected Malting Barley Varieties by Neural Modelling
Agriculture
malting barley
variety classification
neural processing of image
artificial intelligence methods
author_facet Agnieszka A. Pilarska
Piotr Boniecki
Małgorzata Idzior-Haufa
Maciej Zaborowicz
Krzysztof Pilarski
Andrzej Przybylak
Hanna Piekarska-Boniecka
author_sort Agnieszka A. Pilarska
title Image Analysis Methods in Classifying Selected Malting Barley Varieties by Neural Modelling
title_short Image Analysis Methods in Classifying Selected Malting Barley Varieties by Neural Modelling
title_full Image Analysis Methods in Classifying Selected Malting Barley Varieties by Neural Modelling
title_fullStr Image Analysis Methods in Classifying Selected Malting Barley Varieties by Neural Modelling
title_full_unstemmed Image Analysis Methods in Classifying Selected Malting Barley Varieties by Neural Modelling
title_sort image analysis methods in classifying selected malting barley varieties by neural modelling
publisher MDPI AG
series Agriculture
issn 2077-0472
publishDate 2021-08-01
description Quality evaluation of products is a critical stage in the process of production. It also applies to the production of beer and its main ingredients, i.e., hops, yeast, malting barley and other components. The research described in this paper deals with the multifaceted quality evaluation of malting barley needed for the production of malt. The project aims to elaborate on the original methodology used for identifying grain varieties, grain contamination degree and other visual characteristics of malting barley employing new computer technologies, including artificial intelligence (AI) and neural image analysis. The neural modelling and digital image analysis assist in identifying the quality of barley varieties. According to the study, information concerning the colour of barley varieties presented in digital images is sufficient for this purpose. The multi-layer perceptron (MLP)-type neural network generated using a data set describing the colour of kernels presented in digital images was the best model for recognising the analysed malting barley varieties. The proposed procedure may bring specific benefits to malthouses, influencing the beer production quality in the future.
topic malting barley
variety classification
neural processing of image
artificial intelligence methods
url https://www.mdpi.com/2077-0472/11/8/732
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