Classification of bovine carcasses: New biometric remote sensing tools


Submitted: 29 October 2019
Accepted: 30 March 2020
Published: 16 October 2020
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Slaughtering plants approved by the European Union have specific processes to guarantee that beef carcasses or halfcarcasses, of no less than eight months of age, are provided with health mark and then classified and identified according to the EU carcass classification grid. This classification is based on three criteria: i) Category, ii) Conformation (SEUROP) and iii) Fat Cover (FC). At the end of the classification process each carcass is given a code, consisting of two letters and a number: this operation is called Identification. The aim of our study was to evaluate how the European beef carcass quality classification is determined according to the experience of the personnel involved, then comparing the results with those yielded by the Android platform application. West Systems, through its West- Zootech division, has developed an Android platform application (SEUROP APP) that allows SEUROP and FC classification with a smart-phone. The photo taken with the smart-phone will yield the necessary angular parameters to determine the conformation class depending on the animal’s muscular mass and based on the convexity of some areas on the half-carcass. It also evaluates the ratio between surface of lean tissue and total carcass surface in order to determine the fat cover and complete the classification. The SEUROP APP was able to obtain objective measurements for as much as 84% of the assessments made during the research and development phase.


Allen P, 1999. Automatic beef classification. Drystock Farmer Autumn, 41.

Allen P, 2000. Automatic beef classification. Proceedings of Meat Automation Congress (MAC), 2000 June, Malaga, Spain.

Allen P, 2001. Accurate readings: Automated carcass grading system. Butchershop 3:1-13.

Allen P, 2009. Automated grading of beef carcasses. In: Improving the sensory and nutritional quality of fresh meat, pp 479-492. DOI: https://doi.org/10.1533/9781845695439.4.479

Allen P, Finnerty N, 2000. Objective beef carcass classification - A report of trial of three VIA classification systems. The National Food Centre, Dublin, 15.

Borggaard C, Madsen NT, Thodberg NH, 1996. In-line image analysis in the slaughter industry, illustrated by beef carcass classification. Meat Sci 43(S):S151-S163. DOI: https://doi.org/10.1016/0309-1740(96)00062-9

Costa C, Negretti P, Vandeputte M, Pallottino F, Antonucci F, Aguzzi J, Bianconi G, Menesatti P, 2014. Innovative automated landmark detection for food processing: the backwarping approach. Food Bioprocess Technol 7(8): 2291-2298. doi: 10.1007/s11947-013-1227-0. DOI: https://doi.org/10.1007/s11947-013-1227-0

Danish Meat Research Istitute (DMRI), 1996. BCC-2 Objective classification, Manuscript No. 1325 E, 3 April 1996.

European Commission, 2013. Regulation of the European Parliament and of the Council of 17 December 2013 establishing a common organisation of the markets in agricultural products and repealing Council Regulations (EEC) No 922/72, (EEC) No 234/79, (EC) No 1037/2001 and (EC) No 1234/2007, EU/1308/2013. In: Official Journal, L 347/671, 20/12/2013.

European Commission, 2017. Commission Delegated Regulation of 20 April 2017 supplementing Regulation (EU) No 1308/2013 of the European Parliament and of the Council as regards the Union scales for the classification of beef, pig and sheep carcasses and as regards the reporting of market prices of certain categories of carcasses and live animals, EU/2017/1182. In: Official Journal, L 171/74, 04/07/2017.

Ferguson DM, Thompson JM, Barrett-Lennard D, Sorensen B, 1995. Prediction of beef carcass yield using whole carcass VIAscan. Proceedings of the 41st International Congress of Meat science and Technology, 1995 Aug 20-25, San Antonio, USA, paper B16:183-184.

Keane MG, 1999. A comparison of carcass grades of streers in the Republic of Ireland, Northern Ireland and Great Britain. Farm and Food, Summer/Autumn 1999.

Meazza M, 2012. Analisi della normativa nazionale e comunitaria. In: Colavita G., Meazza M., Rea S, Nasali M. Frodi alimentari. Tecniche ispettive, aspetti tecnici e giuridici. Le Point Vètérinarie Italie.

Negretti P, Bianconi G, 2007. Brevetto Italiano per invenzione industriale: Apparecchiatura innovativa atta alle misurazioni morfo-ponderali di animali liberi e/o semiliberi da immagini fotografiche e/o video n. 1343431.

Negretti P, Bianconi G, 2015. Method and apparatus for the SEUROP classification of the conformation of carcasses of slaughtered cattle. Pub. No. US 2015/0146937 Al., 2015 May 28.

Negretti P, Bianconi G, 2019. Brevetto Europeo Method and apparatus for the SEUROP classification of the conformation of carcasses of slaughtered cattle. EP 2854555.

Rea S, 2012. Le frodi nelle diverse filiere dei prodotti alimentari d’origine animale. Edizione 2010-2012. In: Colavita G., Meazza M., Rea S, Nasali M. Frodi alimentari. Tecniche ispettive, aspetti tecnici e giuridici. Le Point Vètérinarie Italie, pp 37-72.

Semeraro AM, 2011. Frodi Alimentari: aspetti tecnici e giuridici. In: Rassegna di Diritto, Legislazione e Medicina Legale Veterinaria. 10:2. https://doi.org/10.13130//3190

Sonnichsen M, Augustini C., Dobrowolski A, Brandscheid W, 1998. Objective classification of beef carcasses and prediction of carcass composition by video image analysis. Proceedings of the 44th International Congress of Meat Science and Technology, 1998 Aug-Sep 30-4, Barcelona, Spain, paper C59:938-939.

Tong AKW, Richmond RJ, Jones SDM, Robinson DJ, Chabot BP, Zawadski SM, Robertson WM, Li X, Liu T, 1997. Development of the Lacombe computer vision system (Lacombe CVS) for beef carcass grading. Agriculture and Agri-food Canada, Lacombe Research Centre, AB, Canada.

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Stinga L, Bozzo G, Ficco G, Savarino AE, Barrasso R, Negretti P, Bianconi G, Tantillo G. Classification of bovine carcasses: New biometric remote sensing tools. Ital J Food Safety [Internet]. 2020 Oct. 16 [cited 2024 Apr. 26];9(3). Available from: https://www.pagepressjournals.org/ijfs/article/view/8645

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