title: The ability of video image analysis to predict lean meat yield and EUROP score of lamb carcasses.
abstract: A total of 862 lamb carcasses that were evaluated by both the VIAscan® and the current EUROP classification system were deboned and the actual yield was measured. Models were derived for predicting lean meat yield of the legs (Leg%), loin (Loin%) and shoulder (Shldr%) using the best VIAscan® variables selected by stepwise regression analysis of a calibration data set (n=603). The equations were tested on validation data set (n=259). The results showed that the VIAscan® predicted lean meat yield in the leg, loin and shoulder with an R 2 of 0.60, 0.31 and 0.47, respectively, whereas the current EUROP system predicted lean yield with an R 2 of 0.57, 0.32 and 0.37, respectively, for the three carcass parts. The VIAscan® also predicted the EUROP score of the trial carcasses, using a model derived from an earlier trial. The EUROP classification from VIAscan® and the current system were compared for their ability to explain the variation in lean yield of the whole carcass (LMY%) and trimmed fat (FAT%). The predicted EUROP scores from the VIAscan® explained 36% of the variation in LMY% and 60% of the variation in FAT%, compared with the current EUROP system that explained 49% and 72%, respectively. The EUROP classification obtained by the VIAscan® was tested against a panel of three expert classifiers (n=696). The VIAscan® classification agreed with 82% of conformation and 73% of the fat classes assigned by a panel of expert classifiers. It was concluded that VIAscan® provides a technology that can directly predict LMY% of lamb carcasses with more accuracy than the current EUROP classification system. The VIAscan® is also capable of classifying lamb carcasses into EUROP classes with an accuracy that fulfils minimum demands for the Icelandic sheep industry. Although the VIAscan® prediction of the Loin% is low, it is comparable to the current EUROP system, and should not hinder the adoption of the technology to estimate the yield of Icelandic lambs as it delivered a more accurate prediction for the Leg%, Shldr% and overall LMY% with negligible prediction bias.
authors.affiliation: 1The Agricultural University of Iceland,Hvanneyri,311 Borgarnes,Iceland.
authors.forename: E
authors.initials: E
authors.lastname: Einarsson
authors.affiliation: 1The Agricultural University of Iceland,Hvanneyri,311 Borgarnes,Iceland.
authors.forename: E
authors.initials: E
authors.lastname: Eythórsdóttir
authors.affiliation: 2Cedar Creek Company Unit,10/11 62 Bishop St,Kelvin Grove,Brisbane,QLD 4059,Australia.
authors.forename: C R
authors.initials: CR
authors.lastname: Smith
authors.affiliation: 3The Farmers Association of Iceland,Hagatorgi 1,107 Reykjavik,Iceland.
authors.forename: J V
authors.initials: JV
authors.lastname: Jónmundsson
mesh_terms: D000818:Animals; D001823:Body Composition; D007091:Image Processing, Computer-Assisted; D008460:Meat / Q000032:analysis*; D012756:Sheep