Determination of visual quality of tomato paste using computerized inspection system and artificial neural networks

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dc.authorid0000-0003-1333-060X
dc.authorid0000-0002-2366-514X
dc.authorwosidBOYACI, Ismail Hakki/A-5255-2013
dc.authorwosidKurultay, Şefik/ABA-9989-2020
dc.authorwosidVelioglu, Hasan Murat/P-8312-2015
dc.contributor.authorVelioğlu, Hasan Murat
dc.contributor.authorBoyacı, İsmail Hakkı
dc.contributor.authorKurultay, Şefik
dc.date.accessioned2022-05-11T14:14:18Z
dc.date.available2022-05-11T14:14:18Z
dc.date.issued2011
dc.departmentMeslek Yüksekokulları, Teknik Bilimler Meslek Yüksekokulu, Gıda İşleme Bölümü
dc.departmentFakülteler, Ziraat Fakültesi, Gıda Mühendisliği Bölümü
dc.description.abstractAn artificial neural network (ANN) integrated computerized inspection system (CIS) was developed to determine tomato paste color in CIE L*, a*, and le color format and the number and size of dark specks which exist in the product. The usability of CIS in the determination of the number and the size of dark specks in tomato paste were investigated by comparing the results of CIS and human inspectors. While the inspectors had difficulties not only in determination of the specks having a diameter less than 0.2 mm but also in correct diameter measurement for all specks, the CIS had good determination and measurement capability. In 99 tomato paste samples, the number of the specks having diameter more than 0.2 mm were found by human inspectors and CIS as 233 and 235, respectively. However, the manual inspection gave inaccurate results for the diameter measurement of the specks. In the color evaluation of the tomato paste, strong correlations (R) were found between the results estimated from ANN-integrated CIS and those obtained from colorimeter (0.889, 0.958, 0.907 and 0.987 for L*, a*, b* and a*/b*, respectively). The whole system is adapted to a graphical user interface (GUI) for use by a non-skilled person working in the tomato paste sector. While manual methods need approximately 5 min, GUI needs 20-25 s to determine, count and classify the dark specks and to measure the product color. (C) 2011 Elsevier B.V. All rights reserved.
dc.description.sponsorshipNamik Kemal UniversityNamik Kemal University [NKUBAP00.24.DR.09.01]
dc.description.sponsorshipThis work was supported by the Namik Kemal University Scientific Research Projects Fund (Project No. NKUBAP00.24.DR.09.01).
dc.identifier.doi10.1016/j.compag.2011.04.007
dc.identifier.endpage154
dc.identifier.issn0168-1699
dc.identifier.issn1872-7107
dc.identifier.issue2en_US
dc.identifier.startpage147
dc.identifier.urihttps://doi.org/10.1016/j.compag.2011.04.007
dc.identifier.urihttps://hdl.handle.net/20.500.11776/5855
dc.identifier.volume77
dc.identifier.wosWOS:000293263200003
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.institutionauthorVelioğlu, Hasan Murat
dc.institutionauthorKurultay, Şefik
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.ispartofComputers and Electronics in Agriculture
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectTomato paste
dc.subjectDark speck
dc.subjectColor
dc.subjectComputerized inspection system
dc.subjectArtificial neural networks
dc.subjectRheological Properties
dc.subjectColor
dc.subjectGrowth
dc.subjectDesign
dc.subjectTool
dc.titleDetermination of visual quality of tomato paste using computerized inspection system and artificial neural networks
dc.typeArticle

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