A study regarding the fertility discrimination of eggs by using ultrasound

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dc.authorid0000-0002-2967-213X
dc.authorid0000-0001-7700-3742
dc.authorscopusid57194625723
dc.authorscopusid24773282700
dc.authorscopusid6507512220
dc.authorscopusid6603188754
dc.authorwosidBOYNUKARA, banur/ABA-3405-2020
dc.authorwosidÖnler, Eray/ABA-3381-2020
dc.authorwosidCELEN, ILKER H/A-8683-2018
dc.contributor.authorÖnler, Eray
dc.contributor.authorÇelen, İlker Hüseyin
dc.contributor.authorGülhan, Timur
dc.contributor.authorBoynukara, Banur
dc.date.accessioned2022-05-11T14:14:14Z
dc.date.available2022-05-11T14:14:14Z
dc.date.issued2017
dc.departmentFakülteler, Veteriner Fakültesi, Klinik Öncesi Bilimler Bölümü, Mikrobiyoloji Ana Bilim Dalı
dc.departmentFakülteler, Ziraat Fakültesi, Biyosistem Mühendisliği Bölümü
dc.description.abstractThe aim of this research was to track the growth of chicken eggs, and make a decision as to whether the egg was fertilized or not. A digital imaging system has been developed in order to take an image from six different points without damaging the egg shell. All the images were transferred to a PC and turned into binary images. All the images were reduced to 1024 pixels and fed directly into the classification algorithm. The logistic regression method was used to discriminate the fertility of the eggs. Python programming language and the scikit-learn machine learning library was used to carry out the classifications. True positive, true negative, wrong positive, and wrong negative detection numbers in the trials were 350, 344, 56, and 50, respectively. Negative indicates the egg was infertile, and positive indicated that the egg was fertilized. The model accuracy was measured as 0.8675.
dc.description.sponsorshipNamik Kemal University Scientific Research [NKUBAP.00.24:AR.14.27]
dc.description.sponsorshipThis research was supported by a grant from Namik Kemal University Scientific Research Project (Project No: NKUBAP.00.24:AR.14.27.)
dc.identifier.doi10.18805/ijar.v0iOF.4561
dc.identifier.endpage326
dc.identifier.issn0367-6722
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85021292186
dc.identifier.scopusqualityQ2
dc.identifier.startpage322
dc.identifier.urihttps://doi.org/10.18805/ijar.v0iOF.4561
dc.identifier.urihttps://hdl.handle.net/20.500.11776/5833
dc.identifier.volume51
dc.identifier.wosWOS:000400881900022
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorÖnler, Eray
dc.institutionauthorÇelen, İlker Hüseyin
dc.institutionauthorBoynukara, Banur
dc.language.isoen
dc.publisherAgricultural Research Communication Centre
dc.relation.ispartofIndian Journal of Animal Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectFertility
dc.subjectPoultry egg
dc.subjectUltrasound
dc.subjectUnincubated Chicken Egg
dc.subjectDetecting Fertility
dc.subjectMachine Vision
dc.subjectGerminal Disc
dc.subjectLocalization
dc.titleA study regarding the fertility discrimination of eggs by using ultrasound
dc.typeArticle

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