{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T05:33:46Z","timestamp":1777354426619,"version":"3.51.4"},"reference-count":35,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,5,12]],"date-time":"2021-05-12T00:00:00Z","timestamp":1620777600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Animals"],"abstract":"<jats:p>Carcass 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.<\/jats:p>","DOI":"10.3390\/ani11051368","type":"journal-article","created":{"date-parts":[[2021,5,12]],"date-time":"2021-05-12T10:59:12Z","timestamp":1620817152000},"page":"1368","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Evaluation of an Image Analysis Approach to Predicting Primal Cuts and Lean in Light Lamb Carcasses"],"prefix":"10.3390","volume":"11","author":[{"given":"Ana Catharina","family":"Batista","sequence":"first","affiliation":[{"name":"Veterinary and Animal Research Center (CECAV), 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"}]},{"given":"Virg\u00ednia","family":"Santos","sequence":"additional","affiliation":[{"name":"Veterinary and Animal Research Center (CECAV), 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\/0000-0003-3907-5117","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Afonso","sequence":"additional","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 Center (CECAV), 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\/0000-0003-2383-5206","authenticated-orcid":false,"given":"Jorge","family":"Azevedo","sequence":"additional","affiliation":[{"name":"Veterinary and Animal Research Center (CECAV), 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":"Mountain Research Centre (CIMO), Escola Superior Agr\u00e1ria, Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus Sta Apol\u00f3nia Apt 1172, 5301-855 Bragan\u00e7a, Portugal"}]},{"given":"Severiano","family":"Silva","sequence":"additional","affiliation":[{"name":"Veterinary and Animal Research Center (CECAV), 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":[[2021,5,12]]},"reference":[{"key":"ref_1","unstructured":"Maltin, C., Craigie, C., and B\u00fcnger, L. (2015). Australian view on lamb carcass and meat quality\u2013the role of measurement technologies in the Australian sheep industry. Farm Animal Imaging\u2014A Summary Report, SRUC."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Silva, S., Guedes, C., Rodrigues, S., and Teixeira, A. (2020). Non-destructive imaging and spectroscopic techniques for assessment of carcass and meat quality in sheep and goats: A review. Foods, 9.","DOI":"10.3390\/foods9081074"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/j.meatsci.2012.05.028","article-title":"A review of the development and use of video image analysis (VIA) for beef carcass evaluation as an alternative to the current EUROP system and other subjective systems","volume":"92","author":"Craigie","year":"2012","journal-title":"Meat Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/bs.afnr.2018.09.002","article-title":"Advances and sheep and goat meat products research","volume":"Volume 87","author":"Toldra","year":"2019","journal-title":"Advances in Food and Nutrition Research"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0921-4488(97)00143-0","article-title":"Methods of predicting lamb carcass composition: A review","volume":"29","author":"Stanford","year":"1998","journal-title":"Small Rumin. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1250","DOI":"10.1017\/S1751731115000336","article-title":"Non-invasive methods for the determination of body and carcass composition in livestock: Dual energy X-ray absorptiometry, computed tomography, magnetic resonance imaging and ultrasound: Invited review","volume":"9","author":"Scholz","year":"2015","journal-title":"Animal"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.meatsci.2003.10.015","article-title":"Video image analysis in the Australian meat industry\u2013precision and accuracy of predicting lean meat yield in lamb carcasses","volume":"67","author":"Hopkins","year":"2004","journal-title":"Meat Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.smallrumres.2019.106024","article-title":"Relationships among carcass shape, tissue composition, primal cuts and meat quality traits in lambs: A PLS path modeling approach","volume":"182","author":"Lima","year":"2020","journal-title":"Small Rumin. Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2194","DOI":"10.1017\/S1751731120001019","article-title":"Dual energy X-ray absorptiometry precisely and accurately predicts lamb carcass composition at abattoir chain speed across a range of phenotypic and genotypic variables","volume":"14","author":"Connaughton","year":"2020","journal-title":"Animal"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1559","DOI":"10.1071\/AN17775","article-title":"The value of objective online measurement technology: Australian red meat processor perspective","volume":"58","author":"Toohey","year":"2018","journal-title":"Anim. Prod. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"771","DOI":"10.1016\/j.tifs.2020.12.016","article-title":"Objective carcass measurement technologies: Latest developments and future trends","volume":"111","author":"Allen","year":"2021","journal-title":"Trends Food Sci. Tech."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kerry, J.P., and Ledward, D. (2009). Automated grading of beef carcasses. Improving the Sensory and Nutritional Quality of Fresh Meat, Woodhead Publishing.","DOI":"10.1533\/9781845695439"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.livsci.2010.10.012","article-title":"Use of digital images to predict carcass cut yields in cattle","volume":"137","author":"Pabiou","year":"2011","journal-title":"Livest. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.meatsci.2015.10.012","article-title":"Post-mortem prediction of primal and selected retail cut weights of New Zealand lamb from carcass and animal characteristics","volume":"112","author":"Ngo","year":"2016","journal-title":"Meat Sci."},{"key":"ref_15","unstructured":"(2021, April 05). Commission Regulation (EC) No 1107\/96 of 12 June 1996 on the Registration of Geographical Indications and Designations of Origin under the Procedure Laid down in Article 17 of Council Regulation (EEC) No 2081\/92, Available online: https:\/\/www.legislation.gov.uk\/eur\/1996\/1107."},{"key":"ref_16","unstructured":"Rasband, W.S., and ImageJ, U.S. (2019, January 01). National Institutes of Health, Bethesda, Maryland, USA, Available online: https:\/\/imagej.nih.gov\/ij\/."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"628","DOI":"10.1016\/j.meatsci.2009.10.022","article-title":"Predicting meat yields and commercial meat cuts from carcasses of young bulls of Spanish breeds by the SEUROP method and an image analysis system","volume":"84","author":"Oliver","year":"2010","journal-title":"Meat Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.livsci.2009.11.004","article-title":"Genetic parameters for carcass dimensional measurements from Video Image Analysis and their association with conformation and fat class scores","volume":"128","author":"Brotherstone","year":"2010","journal-title":"Livest. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.smallrumres.2015.07.008","article-title":"The effect of carcass weight and sex on carcass composition and meat quality of \u201cCordeiro Mirandes\u201d-Protected designation of origin lambs","volume":"130","author":"Santos","year":"2015","journal-title":"Small Rumin. Res."},{"key":"ref_20","first-page":"3","article-title":"Atlas of dissection of ruminant\u2019s carcass","volume":"108","author":"Panea","year":"2012","journal-title":"Inf. Tec. Econ. Agrar."},{"key":"ref_21","first-page":"130","article-title":"Breed and maturity effects on Churra Galega Bragan\u00e7ana and Suffolk lamb carcass characteristics: Killing-out proportion and composition","volume":"17","author":"Rodrigues","year":"2006","journal-title":"Meat. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.geoderma.2006.07.004","article-title":"Determining the composition of mineral-organic mixes using UV-vis-NIR diffuse reflectance spectroscopy","volume":"137","author":"McGlynn","year":"2006","journal-title":"Geoderma"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.meatsci.2007.05.019","article-title":"Live weight and sex effects on carcass and meat quality of \u201cBorrego terrincho-PDO\u201d suckling lambs","volume":"77","author":"Santos","year":"2007","journal-title":"Meat Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/S0309-1740(00)00026-7","article-title":"Carcass and meat quality in light lambs from different fat classes in the EU carcass classification system","volume":"56","author":"Alfonso","year":"2000","journal-title":"Meat Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.smallrumres.2005.04.007","article-title":"Body composition in relation to slaughter weight and gender in suckling lambs","volume":"64","author":"Diaz","year":"2006","journal-title":"Small Rumin. Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.meatsci.2005.11.002","article-title":"Carcass characteristics of suckling lambs protected by the PGI \u201cLechazo de Castilla y Leon\u201d European quality label: Effect of breed, sex and carcass weight","volume":"73","author":"Miguelez","year":"2006","journal-title":"Meat Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1170","DOI":"10.1017\/S1751731114000962","article-title":"The ability of video image analysis to predict lean meat yield and EUROP score of lamb carcasses","volume":"8","author":"Einarsson","year":"2014","journal-title":"Animal"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"108400","DOI":"10.1016\/j.meatsci.2020.108400","article-title":"Using dual energy X-ray absorptiometry to estimate commercial cut weights at abattoir chain-speed","volume":"173","author":"Gardner","year":"2021","journal-title":"Meat Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1488","DOI":"10.2527\/2003.8161488x","article-title":"An evaluation of the lamb vision system as a predictor of lamb carcass red meat yield percentage","volume":"81","author":"Brady","year":"2003","journal-title":"J. Anim. Sci."},{"key":"ref_30","unstructured":"Monteiro, A., Teixeira, A., Azevedo, J., and Silva, S. (2012, January 8\u201312). Determination of carcass composition of goats by video image analysis. Proceedings of the IV CIGR International Workshop on Computer Image Analysis and Spectroscopy in Agriculture, C0737, Valencia, Spain."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.meatsci.2008.12.009","article-title":"Evaluation of Video Image Analysis (VIA) technology to predict meat yield of sheep carcasses on-line under UK abattoir conditions","volume":"82","author":"Maltin","year":"2009","journal-title":"Meat Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2069","DOI":"10.2527\/2004.8272069x","article-title":"Development and validation of equations utilizing lamb vision system output to predict lamb carcass fabrication yields","volume":"82","author":"Cunha","year":"2004","journal-title":"J. Anim. Sci."},{"key":"ref_33","unstructured":"Normand, J., and Ferrand, M. (2011). Evaluation des performances de la machine \u00e0 classer les carcasses ovines VIASCAN\u00ae. Compte rendu n\u00b0 00 11 32 028, D\u00e9partement Techniques d\u2019Elevage et Qualit\u00e9, Institut de l\u2019Elevage, Institut de l\u2019\u00c9levage."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1017\/S1357729800010079","article-title":"Video image analysis for on-line classification of lamb carcasses","volume":"67","author":"Stanford","year":"1998","journal-title":"Anim. Sci."},{"key":"ref_35","first-page":"371","article-title":"Evaluation de la conformation, de l\u2019\u00e9tat d\u2019engraissement et du pourcentage de muscle des carcasses d\u2019agneau par analyse d\u2019image: Les performances de la machine \u00e0 classer ovine dans le contexte des abattoirs fran\u00e7ais","volume":"22","author":"Normand","year":"2015","journal-title":"Renc. Rech. Rumin."}],"container-title":["Animals"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-2615\/11\/5\/1368\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:59:32Z","timestamp":1760162372000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-2615\/11\/5\/1368"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,12]]},"references-count":35,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["ani11051368"],"URL":"https:\/\/doi.org\/10.3390\/ani11051368","relation":{},"ISSN":["2076-2615"],"issn-type":[{"value":"2076-2615","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,12]]}}}