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In vivo ultrasound prediction of the fillet volume in senegalese sole (Solea senegalensis)

dc.contributor.authorAfonso, João
dc.contributor.authorGuedes, Cristina M.
dc.contributor.authorTeixeira, Alfredo
dc.contributor.authorRema, Paulo
dc.contributor.authorSilva, Severiano
dc.date.accessioned2023-02-03T12:16:59Z
dc.date.available2023-02-03T12:16:59Z
dc.date.issued2022
dc.description.abstractSenegalese sole (Solea senegalensis) has been considered a promising new flatfish species for Mediterranean marine fish farming. Accurate prediction of fillet traits in live animals may allow for more efficient control of muscle deposition in fish. In this sense, this study was undertaken to develop a non-invasive method to predict in vivo fish fillet volume and yield using real-time ultrasonography (RTU). The trial was conducted with 44 market weight Senegalese sole (298.54 ± 87.30 g). Fish were scanned with an Aloka SSD 500V with a 7.5 MHz probe. Ten RTU cross-sectional images were taken from the operculum to the caudal fin at regular intervals. These images were analyzed using Fiji software. These data were then used to estimate the partial volumes of the fillet. Actual fillet volume was determined using Archimedes’ principle. Simple and stepwise multiple regression analyses were then used to develop prediction models of fillet volume and yield. The most cranial RTU sections of the fish fillet were the best single predictors of both fillet volume and fillet yield and were the ones included in the best stepwise models. The best RTU slice area explained 82% of the variation observed in fillet volume, but the other RTU slice areas used as predictors of fillet volume showed poor to moderate accuracy (0.035 ≤ R2 ≤ 0.615). Single RTU partial volumes showed poor to very high accuracy (0.395 ≤ R2 ≤ 0.970) as predictors of fillet volume. The best stepwise model based on the RTU slice areas included three independent variables and explained 88.3% of the observed variation. The best stepwise models based on RTU partial volumes (single volumes and/or combinations of single volumes) explained about 97% of the variation observed in fillet volume. Two RTU volume traits, V1–5 + V6–9, and V1+()+9, showed to be practically direct predictors of the actual fillet volume, explaining, respectively, 97% and 96% of the variation observed in the actual fillet volume. The fillet yields show lower correlations with slice areas (r between 0.044 and 0.601) than with volumes (r between 0.288 and 0.637). While further studies are clearly necessary to better understand the potential of RTU for the estimation of fillet yield in fish in general and Senegalese sole in particular, the present results showed that RTU traits can be very good predictors of Senegalese sole’s fillet volume, either used in regression models or as direct predictors.pt_PT
dc.description.sponsorshipThis work was supported by European Food Safety Authority under grant OC/EFSA/SCER/2017/02; FCT pro- vided financial support by national funds (FCT/MCTES) to CFE (UIDB/04004/2020) and CIMO (UIDB/00690/2020); NC was financed by FCT under PhD grant SFRH/BD/133352/2017; YLD by DCE (Danish Centre for Environment and Energy) under grant 21628-82105.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAfonso, João; Guedes, Cristina M.; Teixeira, Alfredo; Rema, Paulo; Silva, Severiano. (2022). In vivo ultrasound prediction of the fillet volume in senegalese sole (Solea senegalensis). Animals. ISSN 2076-2615. 12:18, p. 1-13pt_PT
dc.identifier.issn2076-2615
dc.identifier.urihttp://hdl.handle.net/10198/26733
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectFillet volumept_PT
dc.subjectFillet yieldpt_PT
dc.subjectUltrasoundpt_PT
dc.subjectSolea senegalensispt_PT
dc.titleIn vivo ultrasound prediction of the fillet volume in senegalese sole (Solea senegalensis)pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleAnimalspt_PT
person.familyNameTeixeira
person.givenNameAlfredo
person.identifier958487
person.identifier.ciencia-id2A1A-FF0C-185B
person.identifier.orcid0000-0003-4607-4796
person.identifier.ridG-4118-2011
person.identifier.scopus-author-id56195849200
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication27cc89a2-6661-4d8d-a727-21109c04a74e
relation.isAuthorOfPublication.latestForDiscovery27cc89a2-6661-4d8d-a727-21109c04a74e

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