Evaluation of Video Image Analysis (VIA) technology to predict meat yield of sheep carcasses on-line under UK abattoir conditions

Genome wide association studies for carcass traits measured by video image analysis in crossbred lambs

This is the first UK genome wide association study investigating potential links between Video Image Analysis (VIA) carcass traits and molecular polymorphisms in crossbred sheep. Phenotypic and genotypic data were collected from two crossbred lamb populations: Texel x Scotch Mule (TxSM, n = 2330) and Texel x Lleyn (TxL, n = 3816). Traits measured included live weights at birth, eight weeks and weaning (∼15 weeks). VIA-predicted traits included total weights and weights of fat, muscle and bone in the whole carcass and primal (hind leg, saddle, shoulder) regions. Within-breed heritabilities estimated for the VIA traits ranged from 0.01 to 0.70, indicating potential for inclusion of some traits in breeding programmes. The two crossbred populations differed in SNPs associated with different traits. Two SNPs on chromosomes two (s74618.1) and eight (s68536.1), respectively, reached genome-wise significance for TxSM, explaining <1% of trait variance, for whole carcass fat and muscle weights, hind leg and saddle fat weights and shoulder bone weights. For TxL, four SNPs reached genome-wise significance, on chromosome two for hind leg muscle weight (OAR2_117,959,202 and OAR2_11804335), on chromosome 10 for whole carcass bone weight (OAR19_8,995,957.1), and on chromosome 19 for weaning weight (s40847.1), each explaining <1% of trait genetic variation. Differences in apparent genetic control of carcass traits may be influenced by the lambs' cross-breed, but also by management decisions affecting environmental variance and trait definitions, which should be understood in order to define protocols for incorporation of carcass traits into (cross)breeding programmes. IMPLICATIONS: Combining VIA-measured carcass traits with conventional production traits in a breeding programme could potentially improve the production and product quality of meat sheep. Phenotypes for VIA traits could be collected relatively easily if VIA machines were present at all abattoir sites. The current study and future Genome Wide Association Studies may help to identify potentially informative molecular markers, that explain large proportions of the genetic variance observed in VIA-measured carcass traits. Including this information in the estimation of breeding values could increase the accuracy of prediction, increasing the potential rate of genetic improvement for product quality. This study confirms the polygenic architecture of the investigated carcass traits, with a small number of molecular markers that each explain a small amount of genetic variation. Further studies across breed types are recommended to further test and validate molecular markers for traits related to lamb carcass quality, as measured by video image analysis.

Using Image Analysis Technique for Predicting Light Lamb Carcass Composition

Over the years, numerous techniques have been explored to assess the composition and quality of sheep carcasses. This study focuses on the utilization of video image analysis (VIA) to evaluate the composition of light lamb carcasses (4.52 ± 1.34 kg, mean cold carcass weight ± SD). Photographic images capturing the lateral and dorsal sides of fifty-five light lamb carcasses were subjected to analysis. A comprehensive set of measurements was recorded, encompassing dimensions such as lengths, widths, angles, areas, and perimeters, totaling 21 measurements for the lateral view images and 29 for the dorsal view images. K-Folds stepwise multiple regression analyses were employed to construct prediction models for carcass tissue weights (including muscle, subcutaneous fat, intermuscular fat, and bone) and their respective percentages. The most effective prediction equations were established using data from cold carcass weight (CCW) and measurements from both dorsal and lateral views. These models accounted for a substantial portion of the observed variation in the weights of all carcass tissues (with K-fold-R2 ranging from 0.83 to 0.98). In terms of carcass tissue percentages, although the degree of variation explained was slightly lower (with K-fold-R2 ranging from 0.41 to 0.78), the VIA measurements remained integral to the predictive models. These findings underscore the efficacy of VIA as an objective tool for assessing the composition of light lamb carcasses, which are carcasses weighing ≈ 4-8 kg.

Predicting fat cover in beef cattle to make on-farm management decisions: a review of assessing fat and of modeling fat deposition

Demands of domestic and foreign market specifications of carcass weight and fat cover, of beef cattle, have led to the development of cattle growth models that predict fat cover to assist on-farm managers make management decisions. The objectives of this paper are 4-fold: 1) conduct a brief review of the biological basis of adipose tissue accretion, 2) briefly review live and carcass assessments of beef cattle, and carcass grading systems used to develop quantitative compositional and quality indices, 3) review fat deposition models: Davis growth model (DGM), French National Institute for Agricultural Research growth model (IGM), Cornell Value Discovery System (CVDS), and BeefSpecs drafting tool (BeefSpecsDT), and 4) appraise the process of translating science and practical skills into research/decision support tools that assist the Beef industry improve profitability. The r2 for live and carcass animal assessments, using several techniques across a range of species and traits, ranged from 0.61 to 0.99 and from 0.52 to 0.99, respectively. Model evaluations of DGM and IGM were conducted using Salers heifers (n = 24) and Angus-Hereford steers (n = 15) from an existing publication and model evaluations of CVDS and BeefSpecsDT were conducted using Angus steers (n = 33) from a research trial where steers were grain finished for 101 d in a commercial feedlot. Evaluating the observed and predicted fat mass (FM) is the focus of this review. The FM mean bias for Salers heifers were 7.5 and 1.3 kg and the root mean square error of prediction (RMSEP) were 31.2 and 27.8 kg and for Angus-Hereford steers the mean bias were -4.0 and -10.5 kg and the RMSEP were 9.14 and 21.5 kg for DGM and IGM, respectively. The FM mean bias for Angus steers were -5.61 and -2.93 kg and the RMSEP were 12.3 and 13.4 kg for CVDS and BeefSpecsDT, respectively. The decomposition for bias, slope, and deviance were 21%, 12%, and 68% and 5%, 4%, and 91% for CVDS and BeefSpecsDT, respectively. The modeling efficiencies were 0.38 and 0.27 and the models were within a 20 kg level of tolerance 91% and 88% for CVDS and BeefSpecsDT, respectively. Fat deposition models reported in this review have the potential to assist the beef industry make on-farm management decisions on live cattle before slaughter and improve profitability. Modelers need to continually assess and improve their models but with a caveat of 1) striving to minimize inputs, and 2) choosing on-farm inputs that are readily available.

Using fat thickness and longissimus thoracis traits real-time ultrasound measurements in Black Belly ewe lambs to predict carcass tissue composition through multiresponse multivariate adaptive regression splines algorithm

The main idea of the current study was to estimate carcass tissue composition using fat thickness and longissimus thoracis (LT) traits real-time ultrasound measurements (USM) in Black Belly ewe lambs through multiresponse multivariate adaptive regression splines (MARS) algorithms. Twenty-four hours before slaughter, subcutaneous (SFT) and kidney-fat thickness (KFT), LT depth (LTD), width (LTA, cm) and area (LTMA) were measured in 60 lambs (BW of 26.40 ± 7.01 kg). Information on carcass and non-carcass components was recorded after slaughter. The total carcass muscle (TCM), total carcass bone (TCB), and total carcass fat (TCF) had a low to high correlation (P < 0.01) with BW, cold carcass weight (CCW), and LTD, SFT, KFT, and LDMA. The CCW (%65.58) and SFT (%16.70) were the most effective variables, whilst LTD (%9.57) and LTMA (%8.15) were the lowest variables for determining TCB, TCM, and TCF. The multiresponse MARS algorithm provides an accurate and efficient means of estimating TCF, TCB, and TCM.

Prediction of primal and retail cut weights, tissue composition and yields of youthful cattle carcasses using computer vision systems; whole carcass camera and/or ribeye camera

The application of two computer vision systems (CVS) was evaluated to predict primal and retail cut composition in youthful beef carcasses. Left carcass sides from a total of 634 animals were broken down into primal cuts, scanned using dual-energy x-ray absorptiometry for the prediction of tissue composition and fabricated into retail cuts. Cold carcass camera (CCC) images led to higher R² values than hot carcass camera (HCC) images. The CVS coefficients of prediction for the primal cut weights ranged from 0.61 to 0.97. For the primal cut tissue composition predictions, R² values ranged from 0.09 for Brisket HCC bone prediction to 0.82 for Chuck CCC fat prediction. Retail cut weight estimations had similar R² values, ranging from 0.10 for IMPS 112 (Ribeye roll-denuded ribeye) to 0.99 for IMPS 113C (semi-boneless chuck) both using CCC. The results suggest the feasibility of CVS technologies to predict beef primal and retail cuts weights together with tissue composition, and yield percentages.

Assessing the Feasibility of Using Kinect 3D Images to Predict Light Lamb Carcasses Composition from Leg Volume

This study aimed to evaluate the accuracy of the leg volume obtained by the Microsoft Kinect sensor to predict the composition of light lamb carcasses. The trial was performed on carcasses of twenty-two male lambs (17.6 ± 1.8 kg, body weight). The carcasses were split into eight cuts, divided into three groups according to their commercial value: high-value, medium value, and low-value group. Linear, area, and volume of leg measurements were obtained to predict carcass and cuts composition. The leg volume was acquired by two different methodologies: 3D image reconstruction using a Microsoft Kinect sensor and Archimedes principle. The correlation between these two leg measurements was significant (r = 0.815, p < 0.01). The models to predict cuts and carcass traits that include leg Kinect 3D sensor volume are very good in predicting the weight of the medium value and leg cuts (R² of 0.763 and 0.829, respectively). Furthermore, the model, which includes the Kinect leg volume, explained 85% of its variation for the carcass muscle. The results of this study confirm the good ability to estimate cuts and carcass traits of light lamb carcasses with leg volume obtained with the Kinect 3D sensor.

Evaluation of the functionality of EUROP carcass classification system in thin-tailed and fat-tailed lambs

Aim of study was to investigate the relationship of EUROP carcass fatness and conformation classes with carcass and meat quality characteristics in thin-tailed (Kivircik) and a fat-tailed (Kangal Akkaraman) lambs. A total of 96 lamb carcasses (48 Kivircik and 48 Kangal Akkaraman breed) were examined. Distribution of carcasses in conformation and fatness classes were more limited in Kangal Akkaraman carcasses. More accurate predictions were obtained in Kivircik lambs compared to Kangal Akkaraman lambs in terms of backfat thickness, kidney knob and channel fat percentage, longissimus thoracis muscle area, weights of high-value carcass joints, weights of tissues in the hind limb and muscle/bone ratio. EUROP classification system was not appropriate for predicting meat quality in thin-tailed and fat-tailed lambs. The combination of EUROP fatness and conformation classes with cold carcass weight can be used to predict weights of high-value carcass joints and weights of hind limb tissues.

Carcass and Primal Composition Predictions Using Camera Vision Systems (CVS) and Dual-Energy X-ray Absorptiometry (DXA) Technologies on Mature Cows

This study determined the potential of computer vision systems, namely the whole-side carcass camera (HCC) compared to the rib-eye camera (CCC) and dual energy X-ray absorptiometry (DXA) technology to predict primal and carcass composition of cull cows. The predictability (R²) of the HCC was similar to the CCC for total fat, but higher for lean (24.0%) and bone (61.6%). Subcutaneous fat (SQ), body cavity fat, and retail cut yield (RCY) estimations showed a difference of 6.2% between both CVS. The total lean meat yield (LMY) estimate was 22.4% better for CCC than for HCC. The combination of HCC and CCC resulted in a similar prediction of total fat, SQ, and intermuscular fat, and improved predictions of total lean and bone compared to HCC/CCC. Furthermore, a 25.3% improvement was observed for LMY and RCY estimations. DXA predictions showed improvements in R² values of 26.0% and 25.6% compared to the HCC alone or the HCC + CCC combined, respectively. These results suggest the feasibility of using HCC for predicting primal and carcass composition. This is an important finding for slaughter systems, such as those used for mature cattle in North America that do not routinely knife rib carcasses, which prevents the use of CCC.

Evaluation of an Image Analysis Approach to Predicting Primal Cuts and Lean in Light Lamb Carcasses

Simple Summary

The traditional way of estimating the carcass composition by complete dissection of muscle, fat and bone is an expensive, time-consuming and inconsistent process. The purpose of this study was to evaluate the accuracy of a simple video image analysis (VIA) system to predict the composition and primal cuts using light lamb carcasses. The six cuts of the carcasses were grouped according to their commercial value: high-value cuts (HVC), medium-value (MVC), low-value (LVC) and all of the cuts (AllC). Results showed the ability of the VIA system to estimate the weight and yield of the groups of carcass joints.

Abstract

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 < 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 < 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.

Using a lamb's early-life liveweight as a predictor of carcass quality

The commercial value of lamb carcasses is primarily determined by their weight and quality, with the latter commonly quantified according to muscle coverage and fat depth. The ability to predict these quality scores early in the season could be of substantial value to sheep producers, as this would enable tailored flock management strategies for different groups of animals. Existing methods of carcass quality prediction, however, require either expensive equipment or information immediately before slaughter, leaving them unsuitable as a decision support tool for small to medium-scale enterprises. Using seven-year high-resolution data from the North Wyke Farm Platform, a system-scale grazing trial in Devon, UK, this paper investigates the feasibility of using a lamb's early-life liveweight to predict the carcass quality realised when the animal reaches the target weight. The results of multinomial regression models showed that lambs which were heavier at weaning, at 13 weeks of age, were significantly more likely to have leaner and more muscular carcasses. An economic analysis confirmed that these animals produced significantly more valuable carcasses at slaughter, even after accounting for seasonal variation in lamb price that often favours early finishers. As the majority of heavier-weaned lambs leave the flock before lighter-weaned lambs, an increase in the average weaning weight could also lead to greater pasture availability for ewes in the latter stage of the current season, and thus an enhanced ewe condition and fertility for the next season. All information combined, therefore, a stronger focus on ewes' nutrition before and during lactation was identified as a key to increase system-wide profitability.

Review of Livestock Welfare Indicators Relevant for the Australian Live Export Industry

Animal welfare is an important issue for the live export industry (LEI), in terms of economic returns, community attitudes and international socio-political relations. Mortality has traditionally been the main welfare measure recorded within the LEI; however, high mortality incidents are usually acted upon after adverse events occur, reducing the scope for proactive welfare enhancement. We reviewed 71 potential animal welfare measures, identifying those measures that would be appropriate for use throughout the LEI for feeder and slaughter livestock species, and categorised these as animal-, environment- and resource-based. We divided the live export supply chain into three sectors: (1) Australian facilities, (2) vessel and (3) destination country facilities. After reviewing the relevant regulations for each sector of the industry, we identified 38 (sector 1), 35 (sector 2) and 26 (sector 3) measures already being collected under current practice. These could be used to form a 'welfare information dashboard': a LEI-specific online interface for collecting data that could contribute towards standardised industry reporting. We identified another 20, 25 and 28 measures that are relevant to each LEI sector (sectors 1, 2, 3, respectively), and that could be developed and integrated into a benchmarking system in the future.

Advances in Sheep and Goat Meat Products Research

The main goal of this chapter was to review the state of the art in the recent advances in sheep and goat meat products research. Research and innovation have been playing an important role in sheep and goat meat production and meat processing as well as food safety. Special emphasis will be placed on the imaging and spectroscopic methods for predicting body composition, carcass and meat quality. The physicochemical and sensory quality as well as food safety will be referenced to the new sheep and goat meat products. Finally, the future trends in sheep and goat meat products research will be pointed out.

The value of objective online measurement technology: Australian red meat processor perspective

In the past, the adoption of online measurement technologies for measuring carcass and meat quality traits objectively has been low among Australian red meat processors. The aim of the present work was to obtain a greater understanding of Australian processor views on the value of objective online measurement technologies. This was achieved through consultation with 65 Australian processors, to understand which carcass and meat quality traits they considered important to objectively measure and what they thought of current and future technologies. It was shown that beef processors ranked meat colour and tenderness as the most important traits (P < 0.001) to objectively measure online. Sheep processors ranked tenderness, pH, age, meat colour, total tissue depth at the 12th rib 110 mm from the midline (GR) and saleable meat yield percentage as the most important traits (P < 0.001) to objectively measure online. The overall processor responses indicated that there is support for online measurement technologies, with 80% of processors stating that online objective grading systems have a role in the Australian meat processing sector now and 88% considered these to have a role in the future. Much can be learned from the implementation of previous online objective measurement technologies by processors in terms of commercialisation and adoption strategies. The development and adoption of objective online measurement technologies is challenging and complex. However, increased adoption of online measurement technologies has the potential to achieve benefits to the whole of industry and needs continued support, coupled with new approaches to enhance adoption.

Prediction of foal carcass composition and wholesale cut yields by using video image analysis

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-R 2) 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-R 2 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-R 2 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.

Post-mortem prediction of primal and selected retail cut weights of New Zealand lamb from carcass and animal characteristics

Post-mortem measurements (cold weight, grade and external carcass linear dimensions) as well as live animal data (age, breed, sex) were used to predict ovine primal and retail cut weights for 792 lamb carcases. Significant levels of variance could be explained using these predictors. The predictive power of those measurements on primal and retail cut weights was studied by using the results from principal component analysis and the absolute value of the t-statistics of the linear regression model. High prediction accuracy for primal cut weight was achieved (adjusted R(2) up to 0.95), as well as moderate accuracy for key retail cut weight: tenderloins (adj-R(2)=0.60), loin (adj-R(2)=0.62), French rack (adj-R(2)=0.76) and rump (adj-R(2)=0.75). The carcass cold weight had the best predictive power, with the accuracy increasing by around 10% after including the next three most significant variables.

A systematic review of animal based indicators of sheep welfare on farm, at market and during transport, and qualitative appraisal of their validity and feasibility for use in UK abattoirs

In the UK, it has been suggested that abattoirs are ideal locations to assess the welfare of sheep as most are slaughtered at abattoirs either as finished lambs or cull ewes. Data from abattoirs could provide benchmarks for welfare indicators at a national level, as well as demonstrating how these change over time. Additionally, feedback could be provided to farmers and regulatory authorities to help improve welfare and identify high or low standards for quality assurance or risk-based inspections. A systematic review of the scientific literature was conducted, which identified 48 animal-based indicators of sheep welfare that were categorised by the Five Freedoms. Their validity as measures of welfare and feasibility for use in abattoirs were evaluated as potential measures of prior sheep welfare on the farm of origin, at market, or during transportation to the abattoir. A total of 19 indicators were considered valid, of which nine were considered theoretically feasible for assessing sheep welfare at abattoirs; these were body cleanliness, carcass bruising, diarrhoea, skin lesions, skin irritation, castration, ear notching, tail docking and animals recorded as 'obviously sick'. Further investigation of these indicators is required to test their reliability and repeatability in abattoirs. Novel welfare indicators are needed to assess short-term hunger and thirst, prior normal behaviour and long-term fear and distress.

A Potential Use of 3-D Scanning to Evaluate the Chemical Composition of Pork Meat

The aim of this study was to determine the possibility of 3-D scanning method in chemical composition evaluation of pork meat. The sampling material comprised neck muscles (1000 g each) obtained from 20 pork carcasses. The volumetric estimation process of the elements was conducted on the basis of point cloud collected using 3-D scanner. Knowing the weight of neck muscles, their density was calculated which was subsequently correlated with the content of basic chemical components of the pork meat (water, protein and fat content, determined by standard methods). The significant correlations (P ≤ 0.05) between meat density and water (r = 0.5213), protein (r = 0.5887), and fat (r = -0.6601) content were obtained. Based on the obtained results it seems likely to employ the 3-D scanning method to compute the meat chemical composition.

PRACTICAL APPLICATION

The use of the 3-D scanning method in industrial practice will allow to evaluate the chemical composition of meat in online mode on a dressing and fabrication line and in a rapid, noninvasive manner. The control of the raw material using the 3-D scanning will allow to make visual assessment more objective and will enable optimal standardization of meat batches prior to processing stage. It will ensure not only the repeatability of product quality characteristics, but also optimal use of raw material-lean and fat meat. The knowledge of chemical composition of meat is essential due to legal requirements associated with mandatory nutrition facts labels on food products.

Recent developments in cattle, pig, sheep and horse breeding - a review

The aim of this review was to summarize new genetic approaches and techniques in the breeding of cattle, pigs, sheep and horses. Often production and reproductive traits are treated separately in genetic evaluations, but advantages may accrue to their joint evaluation. A good example is the system in pig breeding. Simplified breeding objectives are generally no longer appropriate and consequently becoming increasingly complex. The goal of selection for improved animal performance is to increase the profit of the production system; therefore, economic selection indices are now used in most livestock breeding programmes. Recent developments in dairy cattle breeding have focused on the incorporation of molecular information into genetic evaluations and on increasing the importance of longevity and health in breeding objectives to maximize the change in profit. For a genetic evaluation of meat yield (beef, pig, sheep), several types of information can be used, including data from performance test stations, records from progeny tests and measurements taken at slaughter. The standard genetic evaluation method of evaluation of growth or milk production has been the multi-trait animal model, but a test-day model with random regression is becoming the new standard, in sheep as well. Reviews of molecular genetics and pedigree analyses for performance traits in horses are described. Genome – wide selection is becoming a world standard for dairy cattle, and for other farm animals it is under development.

The ability of video image analysis to predict lean meat yield and EUROP score of lamb carcasses

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.

Effects of a quantitative trait locus for increased muscularity on carcass traits measured by subjective conformation and fat class scores and video image analysis in crossbred lambs

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.