Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/52614
DC FieldValueLanguage
dc.contributor.authorNavarro, Anaen_US
dc.contributor.authorLee-Montero, Ivonneen_US
dc.contributor.authorSantana Vega, Dulce Mªen_US
dc.contributor.authorHenríquez, Patriciaen_US
dc.contributor.authorFerrer, Miguel A.en_US
dc.contributor.authorMorales Moreno, Aythamien_US
dc.contributor.authorSoula, Mohameden_US
dc.contributor.authorBadilla, Rodrigoen_US
dc.contributor.authorNegrín-Báez, Daviniaen_US
dc.contributor.authorZamorano, Maria J.en_US
dc.contributor.authorAfonso, Juan M.en_US
dc.contributor.otherFerrer, Miguel A
dc.contributor.otherMorales, Aythami
dc.contributor.otherZamorano, Maria Jesus
dc.date.accessioned2018-12-05T09:23:50Z-
dc.date.available2018-12-05T09:23:50Z-
dc.date.issued2016en_US
dc.identifier.issn0168-1699en_US
dc.identifier.urihttp://hdl.handle.net/10553/52614-
dc.description.abstractA fast and fully automated software for image analysis (named IMAFISH_ML) was developed to measure 27 fish morphometric traits (technological traits) on three commercially relevant fish species: gilthead seabream (Sparus aurata L., from 12.5 to 36.6 cm length), meagre (Argyrosomus regius, from 17.5 to 58.4 cm length) and red porgy (Pagrus pagrus, from 16.3 to 29 cm length). This analysis was performed by using two images of each fish from different angles (lateral and dorsal). The computer vision algorithm was programmed in MATLAB® v.7.5 and is freely available to aquaculture industry and research, and it is possible to modify or combine traits in order to obtain new ones, according to specific interests and competence. Additionally, an appropriate, easy-to-perform and reproducible protocol to take photographs was also described. In order to validate the software, 500 fish of each species were laterally and dorsally photographed, and the images were processed by using the IMAFISH_ML. Each fish was manually processed to measure its fork length, body weight and fillet weight (phenotypic traits). Correlation coefficients between each fish technological and phenotypic traits were calculated, all of them were statistically significant (P<. 0.01). Fork length measured by technological and phenotypic methods showed correlation coefficients between 0.98 and 0.99. The average photograph processing time was 10. s and 9.7. s for lateral and dorsal images, respectively. IMAFISH_ML software provides fish farmers and researchers with an efficient, fast and automatic tool to objectively asses morphological and growth traits. It is a practical and economical way to evaluate products for industrial purposes. Moreover, it is an especially useful tool to be included within genetic breeding programs, as it provides a high number of fast, easy-to-perform and non-invasive traits measurements, which additionally can be correlated to other production traits.en_US
dc.languageengen_US
dc.relation.ispartofComputers and Electronics in Agricultureen_US
dc.sourceComputers And Electronics In Agriculture[ISSN 0168-1699],v. 121, p. 66-73en_US
dc.subject251092 Acuicultura marinaen_US
dc.subject.otherGenetic assessmenten_US
dc.subject.otherGilthead seabreamen_US
dc.subject.otherImage analysisen_US
dc.subject.otherMeagreen_US
dc.subject.otherMorphometric traitsen_US
dc.subject.otherRed porgyen_US
dc.titleIMAFISH_ML: A fully-automated image analysis software for assessing fish morphometric traits on gilthead seabream (Sparus aurata L.), meagre (Argyrosomus regius) and red porgy (Pagrus pagrus)en_US
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.1016/j.compag.2015.11.015
dc.identifier.scopus84951078562
dc.identifier.isi000372380100008
dcterms.isPartOfComputers And Electronics In Agriculture
dcterms.sourceComputers And Electronics In Agriculture[ISSN 0168-1699],v. 121, p. 66-73
dc.contributor.authorscopusid57212839113
dc.contributor.authorscopusid55644147300
dc.contributor.authorscopusid57014794000
dc.contributor.authorscopusid57027894900
dc.contributor.authorscopusid55636321172
dc.contributor.authorscopusid24476050500
dc.contributor.authorscopusid53164709800
dc.contributor.authorscopusid6507726451
dc.contributor.authorscopusid55644309600
dc.contributor.authorscopusid6701451831
dc.contributor.authorscopusid57201126472
dc.description.lastpage73-
dc.description.firstpage66-
dc.relation.volume121-
dc.investigacionCiencias de la Saluden_US
dc.type2Artículoen_US
dc.identifier.wosWOS:000372380100008
dc.contributor.daisngid2095438
dc.contributor.daisngid5976729
dc.contributor.daisngid16452226
dc.contributor.daisngid4265039
dc.contributor.daisngid1432987
dc.contributor.daisngid4545917
dc.contributor.daisngid233119
dc.contributor.daisngid1418808
dc.contributor.daisngid1874491
dc.contributor.daisngid8070891
dc.contributor.daisngid4127459
dc.contributor.daisngid1009633
dc.contributor.daisngid1136306
dc.identifier.investigatorRIDL-3863-2013
dc.identifier.investigatorRIDL-2529-2013
dc.identifier.investigatorRIDM-5052-2018
dc.contributor.wosstandardWOS:Navarro, A
dc.contributor.wosstandardWOS:Lee-Montero, I
dc.contributor.wosstandardWOS:Santana, D
dc.contributor.wosstandardWOS:Henriquez, P
dc.contributor.wosstandardWOS:Ferrer, MA
dc.contributor.wosstandardWOS:Morales, A
dc.contributor.wosstandardWOS:Soula, M
dc.contributor.wosstandardWOS:Badilla, R
dc.contributor.wosstandardWOS:Negrin-Baez, D
dc.contributor.wosstandardWOS:Zamorano, MJ
dc.contributor.wosstandardWOS:Afonso, JM
dc.date.coverdateFebrero 2016
dc.identifier.ulpgces
dc.description.sjr0,896
dc.description.jcr2,201
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.deptGIR Grupo de Investigación en Acuicultura-
crisitem.author.deptIU de Investigación en Acuicultura Sostenible y Ec-
crisitem.author.deptDepartamento de Patología Animal, Producción Animal, Bromatología y Tecnología de Los Alimentos-
crisitem.author.orcid0000-0002-2924-1225-
crisitem.author.orcid0000-0003-1569-9152-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU de Investigación en Acuicultura Sostenible y Ec-
crisitem.author.fullNameFerrer Ballester, Miguel Ángel-
crisitem.author.fullNameZamorano Serrano, María Jesús-
Appears in Collections:Artículos
Show simple item record

SCOPUSTM   
Citations

30
checked on Nov 17, 2024

WEB OF SCIENCETM
Citations

26
checked on Nov 17, 2024

Page view(s)

73
checked on May 19, 2024

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.