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Evaluation of an image analysis approach to predicting primal cuts and lean in light lamb carcasses

dc.contributor.authorBatista, Ana Catharina
dc.contributor.authorSantos, Virgínia
dc.contributor.authorAfonso, João
dc.contributor.authorGuedes, Cristina M.
dc.contributor.authorAzevedo, Jorge
dc.contributor.authorTeixeira, Alfredo
dc.contributor.authorSilva, Severiano
dc.date.accessioned2018-02-19T10:00:00Z
dc.date.accessioned2021-11-23T12:02:52Z
dc.date.available2018-01-19T10:00:00Z
dc.date.available2021-11-23T12:02:52Z
dc.date.issued2021
dc.description.abstractCarcass dissection is a more accurate method for determining the composition of a carcass; however, it is expensive and time-consuming. Techniques like VIA are of great interest once they are objective and able to determine carcass contents accurately. This study aims to evaluate the accuracy of a flexible VIA system to determine the weight and yield of the commercial value of carcass cuts of light lamb. Photos from 55 lamb carcasses are taken and a total of 21 VIA measurements are assessed. The half-carcasses are divided into six primal cuts, grouped according to their commercial value: high-value (HVC), medium-value (MVC), low-value (LVC) and all of the cuts (AllC). K-folds cross-validation stepwise regression analyses are used to estimate the weights of the cuts in the groups and their lean meat yields. The models used to estimate the weight of AllC, HVC, MVC and LVC show similar results and a k-fold coefficient of determination (k-fold-R2) of 0.99 is achieved for the HVC and AllC predictions. The precision of the weight and yield of the three prediction models varies from low to moderate, with k-fold-R2 results between 0.186 and 0.530, p lt 0.001. The prediction models used to estimate the total lean meat weight are similar and low, with k-fold-R2 results between 0.080 and 0.461, p lt 0.001. The results confirm the ability of the VIA system to estimate the weights of parts and their yields. However, more research is needed on estimating lean meat yield.en_EN
dc.description.sponsorshipThe authors acknowledge financial support from the research unit CECAV, which is financed by the National Funds from the Portuguese Foundation for Science and Technology (FCT), project number UIDB/CVT/00772/2020. Ana Catharina Batista also acknowledges financial support from the Brazilian agency Coordenação de Aperfeiçoamento de Pessoal de Ensino Superior (CAPES) (Process 1052/13-6).
dc.description.versioninfo:eu-repo/semantics/publishedVersionen_EN
dc.identifier.citationBatista, Ana Catharina; Santos, Virgínia; Afonso, João; Guedes, Cristina; Azevedo, Jorge; Teixeira, Alfredo; Silva, Severiano (2021). Evaluation of an image analysis approach to predicting primal cuts and lean in light lamb carcasses. Animals. ISSN 2076-2615. 11:5, p. 1-11en_EN
dc.identifier.doi10.3390/ani11051368en_EN
dc.identifier.urihttp://hdl.handle.net/10198/24354
dc.language.isoeng
dc.peerreviewedyesen_EN
dc.relationUIDB/CVT/00772/2020
dc.subjectCuten_EN
dc.subjectLight carcassen_EN
dc.subjectPredictionen_EN
dc.subjectVideo image analysisen_EN
dc.titleEvaluation of an image analysis approach to predicting primal cuts and lean in light lamb carcassesen_EN
dc.typejournal article
dspace.entity.typePublication
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.rightsopenAccessen_EN
rcaap.typearticleen_EN
relation.isAuthorOfPublication27cc89a2-6661-4d8d-a727-21109c04a74e
relation.isAuthorOfPublication.latestForDiscovery27cc89a2-6661-4d8d-a727-21109c04a74e

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