Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/2647
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dc.contributor.authorBalaban, Murat Ömer-
dc.contributor.authorChombeau, Melanie-
dc.contributor.authorCırban, Dilşat-
dc.contributor.authorGümüş, Bahar-
dc.date.accessioned2016-12-22T07:26:56Z
dc.date.available2016-12-22T07:26:56Z
dc.date.issued2010-10
dc.identifier.citationBalaban, M. Ö., Chombeau, M., Cırban, D., and Gümüş, B. (2010). Prediction of the weight of Alaskan Pollock using image analysis. Journal of Food Science, 75(8), E552-E556. doi:10.1111/j.1750-3841.2010.01813.xen_US
dc.identifier.issn0022-1147
dc.identifier.issn0022-1147-
dc.identifier.urihttp://doi.org/10.1111/j.1750-3841.2010.01813.x
dc.identifier.urihttp://hdl.handle.net/11147/2647
dc.description.abstractDetermining the size and quality attributes of fish by machine vision is gaining acceptance and increasing use in the seafood industry. Objectivity, speed, and record keeping are advantages in using this method. The objective of this work was to develop the mathematical correlations to predict the weight of whole Alaskan Pollock (Theragra chalcogramma) based on its view area from a camera. One hundred and sixty whole Pollock were obtained fresh, within 2 d after catch from a Kodiak, Alaska, processing plant. The fish were first weighed, then placed in a light box equipped with a Nikon D200 digital camera. A reference square of known surface area was placed by the fish. The obtained image was analyzed to calculate the view area of each fish. The following equations were used to fit the view area (X) compared with weight (Y) data: linear, power, and 2nd-order polynomial. The power fit (Y = A·XB) gave the highest R2 for the fit (0.99). The effect of fins and tail on the accuracy of the weight prediction using view area were evaluated. Removing fins and tails did not improve prediction accuracy. Machine vision can accurately predict the weight of whole Pollock. © 2010 Institute of Food Technologists®.en_US
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Inc.en_US
dc.relation.ispartofJournal of Food Scienceen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectZlaskan pollocken_US
dc.subjectImage processingen_US
dc.subjectView areaen_US
dc.subjectRegression analysisen_US
dc.subjectBody weighten_US
dc.titlePrediction of the weight of Alaskan Pollock using image analysisen_US
dc.typeArticleen_US
dc.institutionauthorCırban, Dilşat-
dc.departmentİzmir Institute of Technology. Food Engineeringen_US
dc.identifier.volume75en_US
dc.identifier.issue8en_US
dc.identifier.startpageE552en_US
dc.identifier.endpageE556en_US
dc.identifier.wosWOS:000282878200031en_US
dc.identifier.scopus2-s2.0-77958609033en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1111/j.1750-3841.2010.01813.x-
dc.identifier.pmid21535495en_US
dc.relation.doi10.1111/j.1750-3841.2010.01813.xen_US
dc.coverage.doi10.1111/j.1750-3841.2010.01813.xen_US
dc.identifier.wosqualityQ2-
dc.identifier.scopusqualityQ1-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairetypeArticle-
Appears in Collections:Food Engineering / Gıda Mühendisliği
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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