{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T03:03:33Z","timestamp":1760151813800,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T00:00:00Z","timestamp":1662681600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Portuguese Foundation for Science and Technology (FCT)","award":["UIDB\/CVT\/00772\/2020","LA\/P\/0059\/2020"],"award-info":[{"award-number":["UIDB\/CVT\/00772\/2020","LA\/P\/0059\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Animals"],"abstract":"<jats:p>Senegalese 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 \u00b1 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\u2019 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 \u2264 R2 \u2264 0.615). Single RTU partial volumes showed poor to very high accuracy (0.395 \u2264 R2 \u2264 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\u20135 + V6\u20139, 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\u2019s fillet volume, either used in regression models or as direct predictors.<\/jats:p>","DOI":"10.3390\/ani12182357","type":"journal-article","created":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T04:54:41Z","timestamp":1662699281000},"page":"2357","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["In Vivo Ultrasound Prediction of the Fillet Volume in Senegalese Sole (Solea senegalensis)"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3907-5117","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Afonso","sequence":"first","affiliation":[{"name":"Faculdade de Medicina Veterin\u00e1ria, ULisboa, Avenida da Universidade T\u00e9cnica, 1300-477 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8390-4907","authenticated-orcid":false,"given":"Cristina","family":"Guedes","sequence":"additional","affiliation":[{"name":"Veterinary and Animal Research Centre (CECAV) and Associate Laboratory of Animal and Veterinary Science (AL4AnimalS), University of Tr\u00e1s-os-Montes e Alto Douro, Quinta de Prados, 5000-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4607-4796","authenticated-orcid":false,"given":"Alfredo","family":"Teixeira","sequence":"additional","affiliation":[{"name":"Centro de Investiga\u00e7\u00e3o de Montanha (CIMO), Instituto Polit\u00e9cnico de Braganc\u0327a, Campus de Santa Apol\u00f3nia, 5300-253 Braganc\u0327a, Portugal"},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4933-8769","authenticated-orcid":false,"given":"Paulo","family":"Rema","sequence":"additional","affiliation":[{"name":"CIIMAR\u2014Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Novo Edif\u00edcio do Terminal de Cruzeiros de Leix\u00f5es, Avenida General Norton de Matos, s\/n, 4450-208 Matosinhos, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7045-2075","authenticated-orcid":false,"given":"Severiano","family":"Silva","sequence":"additional","affiliation":[{"name":"Veterinary and Animal Research Centre (CECAV) and Associate Laboratory of Animal and Veterinary Science (AL4AnimalS), University of Tr\u00e1s-os-Montes e Alto Douro, Quinta de Prados, 5000-801 Vila Real, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.marpol.2019.02.045","article-title":"Aquaculture subsidies in the European Union: Evolution, impact and future potential for growth","volume":"104","author":"Guillen","year":"2019","journal-title":"Mar. 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