Predicting meat yields and commercial meat cuts from carcasses of young bulls of Spanish breeds by the SEUROP method and an image analysis system |
| |
Authors: | A Oliver JA Mendizabal G Ripoll P Albertí A Purroy |
| |
Affiliation: | 1. Departamento de Producción Agraria, Universidad Pública de Navarra, Campus de Arrosadia, 31006 Pamplona, Spain;2. Centro de Investigación y Tecnología Agroalimentaria, Gobierno de Aragón, Montañana 930, 50059 Saragossa, Spain |
| |
Abstract: | The SEUROP system is currently in use for carcass classification in Europe. Image analysis and other new technologies are being developed to enhance and supplement this classification system. After slaughtering, 91 carcasses of local Spanish beef breeds were weighed and classified according to the SEUROP system. Two digital photographs (a side and a dorsal view) were taken of the left carcass sides, and a total of 33 morphometric measurements (lengths, perimeters, areas) were made. Commercial butchering of these carcasses took place 24 h postmortem, and the different cuts were grouped according to four commercial meat cut quality categories: extra, first, second, and third. Multiple regression analysis of carcass weight and the SEUROP conformation score (x variables) on meat yield and the four commercial cut quality category yields (y variables) was performed as a measure of the accuracy of the SEUROP system. Stepwise regression analysis of carcass weight and the 33 morphometric image analysis measurements (x variables) and meat yield and yields of the four commercial cut quality categories (y variables) was carried out. Higher accuracy was achieved using image analysis than using only the current SEUROP conformation score. The regression coefficient values were between R2 = 0.66 and R2 = 0.93 (P < 0.001) for the SEUROP system and between R2 = 0.81 and R2 = 0.94 (P < 0.001) for the image analysis method. These results suggest that the image analysis method should be helpful as a means of supplementing and enhancing the SEUROP system for grading beef carcasses. |
| |
Keywords: | Carcass quality Image analysis Prediction Young bulls |
本文献已被 ScienceDirect 等数据库收录! |
|