The management of farmed livestock frequently creates situations of stress because of the periodical necessity for handling procedures (weight and linear measurements, veterinary procedures etc). Some of these practices can be avoided using technologies that obviate the need for direct handling. This can improve animal welfare and reduce risks to the handlers. Video image analysis is a technique that can be used for linear measurements and morphological evaluations required for growth trials, genetic studies or herd-book records. This paper describes the application of video image analysis to linear measurement and shape assessment in horses and cattle with minimal disturbance to the animals.

This work represents the first contribution for the application of the video image analysis (VIA) technology in predicting lean meat and fat composition in the equine species. Images of left sides of the carcass (n=42) were captured from the dorsal, lateral and medial views using a high-resolution digital camera. A total of 41 measurements (angles, lengths, widths and areas) were obtained by VIA. The variation of percentage of lean meat obtained from the forequarter (FQ) and hindquarter (HQ) carcass ranged between 5.86% and 7.83%. However, the percentage of fat (FAT) obtained from the FQ and HQ carcass presented a higher variation (CV between 41.34% and 44.58%). By combining different measurements and using prediction models with cold carcass weight (CCW) and VIA measurement the coefficient of determination (k-fold-R2) were 0.458 and 0.532 for FQ and HQ, respectively. On the other hand, employing the most comprehensive model (CCW plus all VIA measurements), the k-fold-R2 increased from 0.494 to 0.887 and 0.513 to 0.878 with respect to the simplest model (only with CCW), while precision increased with the reduction in the root mean square error (2.958 to 0.947 and 1.841 to 0.787) for the hindquarter fat and lean percentage, respectively. With CCW plus VIA measurements is possible to explain the wholesale value cuts yield variation (k-fold-R2 between 0.533 and 0.889). Overall, the VIA technology performed in the present study could be considered as an accurate method to assess the horse carcass composition which could have a role in breeding programmes and research studies to assist in the development of a value-based marketing system for horse carcass.

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 R2 of 0.60, 0.31 and 0.47, respectively, whereas the current EUROP system predicted lean yield with an R2 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.

A quantitative trait locus (QTL) for increased loin muscularity (TM-QTL) has previously been identified in purebred Texel sheep. Crossbred lambs born out of Mule ewes mated to heterozygous Texel sires for the TM-QTL were evaluated for a range of carcass traits. Lambs were genotyped and classified as carriers (n = 62) of a single copy of the TM-QTL and non-carriers (n = 49). In this study, the effects of the TM-QTL on carcass attributes were investigated using subjective classification scores for conformation and fatness, and measurements from a video image analysis (VIA) system. In addition, refined prediction equations to estimate weights of primal joints (leg, chump, loin, breast and shoulder) were obtained by calibrating the VIA system against computer tomography (CT) measurements in the loin region. The new refined prediction models increased the accuracy of prediction of all primal cuts on an average of 16% compared to previously derived standard VIA prediction equations. The coefficient of determination (R2) of the VIA system to predict in vivo CT measurements ranged from 0.39 to 0.72 for measurements of Musculus longissimus lumborum (MLL) area, width and depth, lumbar spine length, loin muscle volume and loin muscularity index. Using VIA estimates of CT-measured loin muscle traits, a significant increase in depth (+2.7%) of the MLL was found to be associated with the TM-QTL. Conformation and fatness scores and the shape of the carcass measured as individual lengths, widths and areas by VIA were not significantly influenced by the TM-QTL. Primal meat yields estimated using both standard and refined VIA prediction equations were not significantly affected by the TM-QTL. However, carcass ‘compactness’ was found to have significantly increased in carrier lambs. The weight of the dissected MLL estimated using VIA information was greater (+2.6%) for carriers compared to non-carriers. To conclude, neither the current industry carcass evaluation system for conformation and fatness nor the standard VIA system is able to identify the effect of the TM-QTL in the loin region in the moment. However, the calibration of the VIA system against CT measurements resulted in improved VIA prediction equations for primal meat yields and also showed moderate potential to estimate loin muscle traits measured by CT and to detect, partially, the effect of the TM-QTL on these traits.

Video image analysis (VIA), carcass shape and colour data were collected for 1211 lambs of known gender, breed type and carcass weight over a 1-week period using the VIAscan® system developed by the Australian Meat Research Corporation. Classification data (thickness of soft tissue over the 12th rib (GR measurement) and subjective conformation scores on a five-point scale of the leg, loin and shoulder) were assessed by an Agriculture and Agri-Food Canada grader after carcasses had chilled at 5°C for 3 to 6 h. Dissections into saleable meat yield (no. = 58) were performed after carcasses had chilled an additional 24 h. The timing of this study, which was dependent on availability of the VIA equipment, influenced the age and type of lambs available for analysis. The majority of lambs evaluated were wool-breed wethers, age > 10 months, of average GR (15·7 (s.d. 0·2) mm) and muscle conformation (3·0, s.d. 0·1). VIA improved the prediction of saleable meat yield (R2 = 0·71, residual s.d. = 14g/kg) compared with the current classification system (R2 = 0·52, residual s.d. = 18 g/kg). Although prediction ofGR measurement by VIA resulted in a large residual error (residual s.d. = 2·4 mm), the proportion of waste fat (perirenal and subcutaneous) and bone dissected from the carcass was accurately predicted (R2 = 0·62, residual s.d. = 11 g/kg). Proportions of leg (R2 = 0·71, residual s.d. = 7 g/kg) and shoulder (R2 = 0·62, residual s.d. = 9 g/kg) primals were also accurately predicted by VIA, although there were no significant predictors for the proportion of the loin (P > 0·15). VIA improved the prediction of saleable meat yield compared with the current classification system. However collection of additional data including some from extremely lean or well muscled animals would be required before VIA could be recommended to classify lamb carcasses