Meat tenderness in Australian lamb: Data editing, environmental variation and their effects in genetic parameter estimation.

Breeding for meat quality increases the value of lambs and requires reliable genetic parameters to achieve balanced genetic progress. Meat tenderness, accomplished by selecting for lower shear force, is an important eating quality trait because of its relationship with consumer satisfaction. Factors influencing shear force, include the pH and temperature decline post-mortem which can contribute towards higher shear force values and increased variation across contemporary groups. This study explored if genetic parameters for shear force change when post slaughter covariates and heterogeneous variance are corrected for, using data from 32,223 animals from different sheep breeds. Results showed that removing extreme individuals and contemporary groups with high mean shear force values reduced residual variance, followed by a smaller reduction in additive genetic variance and little effect on heritability. Results show that edited data performed better at predicting progeny performance and reduced potential bias introduced in the genetic evaluation due to data quality. The effect of including post-slaughter covariates in the genetic analysis was tested by estimating different model predictability through regression of estimated breeding values against offspring performance, showing that the model including hot carcass weight performed better followed by the one including both carcass weight and C-site fat depth. Our results highlight that historic and current in-plant recording practices do not provide the capacity to account for non-genetic factors associated with abattoir environment that might be impacting the ability to accurately calculate shear force breeding values. In that sense, genetic evaluation can be improved by applying more rigorous data editing.

Ageing of Australian lamb beyond 14 days does not further improve eating quality.

Limited studies are available assessing the impact of extended ageing on lamb eating quality of a wide range of cuts. From lamb (n = 153) and young mutton (n = 40) carcasses, seven cuts (eye of rack, eye of shoulder, knuckle, loin, outside, rump and topside) were collected and aged based on three ageing times (5, 14 or 21 days). Additionally, residual glycogen was determined from the loin at the corresponding ageing time. Untrained consumers assessed samples for tenderness, juiciness, flavour liking and overall liking. Increasing ageing time from 5 to 14 or 21 days significantly improved cut eating quality; however, ageing beyond 14 days showed no additional benefit. The ageing effect reduced when corrected for pH and temperature measurements, confirming ageing can improve eating quality when pH and temperature variation exists. Loin residual glycogen had no impact on eating quality at each ageing time. Our results confirm the importance of establishing optimum ageing times for cuts to ensure the highest consumer acceptability.

Ultra-wideband microwave precisely and accurately predicts sheepmeat hot carcase GR tissue depth.

A portable ultra-wideband microwave system (MiS) coupled with an antipodal slot Vivaldi patch antenna (VPA) was used as an objective measurement technology to predict sheep meat carcase GR tissue depth, tested against AUS-MEAT national accreditation standards. Experiment one developed the MiS GR tissue depth prediction equation using lamb carcasses (n = 832) from two slaughter groups. To create the prediction equations, a two layered machine learning stacking ensemble technique was used. The performance of this equation was tested within the dataset using a k-fold cross validation (k = 5), which demonstrated excellent precision and accuracy with an average R2 of 0.91, RMSEP 2.11, bias 0.39 and slope 0.03. Experiment two tested the prediction equation against the AUS-MEAT GR tissue depth accreditation framework which stipulates predictions from a device must assign the correct fat score, with a tolerance of ±2 mm of the score boundary, and 90% accuracy. For a device to be accredited three measurements captured within the same device, as well as measurements across three different devices, must meet the AUS-MEAT error thresholds. Three MiS devices scanned lamb carcases (n = 312) across three slaughter days. All three MiS devices met the AUS-MEAT accreditation thresholds, accurately predicting GR tissue depth 96.1-98.4% of the time. Between the different devices, the measurement accuracy was 99.4-100%, and within the same device, the measurement accuracy was 99.7-100%. Based on these results MiS achieved AUS-MEAT device accreditation as an objective technology to predict GR tissue depth.

Changing Australia's trading language has enhanced the implementation of objective carcase measurement technologies.

In 2016 an Australian project, the Advanced Livestock Measurement Technologies project (ALMTech), was initiated to accelerate the development and implementation of technologies that measure lean meat yield and eating quality. This led to the commercial testing, and implementation of a range of new technologies in the lamb, beef, and pork industries. For measuring lean meat yield %, these technologies included dual energy X-ray absorptiometry, hand-held microwave systems, and 3-D imaging systems. For measuring beef rib-eye traits and intramuscular fat %, both pre- and post-chilling technologies were developed. Post-chilling, a range of camera systems and near infrared spectrophotometers were developed. While pre-chilling, technologies included insertable needle probes, nuclear magnetic resonance, and X-ray systems. Initially these technologies were trained to predict the pre-existing traits already traded upon within industry. However, this approach was limiting because the technologies could measure attributes that were either non-existent in the trading language, were superior as calibrating standards, or more accurately reflected value than the pre-existing trait. Therefore, we introduced IMF% into the trading language for both beef and sheep meat, and carcase lean%, fat%, and bone% for sheep meat. These new technologies and the traits that they predict have delivered multiple benefits. Technology provider-companies are instilled with the confidence to commercialise due to the provision of achievable accreditation standards. Processors have the confidence to invest in these technologies and establish payment grids based upon their measurements. And lastly, it has enhanced data flow into genetic databases, industry data systems (MSA), and as feedback to producers.

Using chemical intramuscular fat percentage to predict visual marbling scores in Australian beef carcasses.

Meat Standards Australia (MSA) marbling score and AUS-MEAT marbling represent key determinants of carcass value in the Australian beef industry and are well recognised traits in national and international markets. However, with the emergence of objective measurement technologies there are opportunities to grade beef carcasses using objective traits such as chemical intramuscular fat (IMF%) but abrupt changes to MSA and AUS-MEAT grading practices would cause significant disruption to the industry. Therefore, the objective of the study was to develop and validate models that transform chemical IMF% into equivalent MSA marbling scores and AUS-MEAT marbling. The second objective was to compare IMF%-derived and grader-derived MSA marbling scores when used as input values in the MSA model to generate predicted eating quality scores (MQ4). Carcasses (n = 5513) from industry experiments across 7 years (2017-2023) were graded for MSA marbling and AUS-MEAT marbling and sampled for chemical IMF%. Data were utilised to develop IMF%-derived models for MSA marbling score (IMF-MSAMB) and AUS-MEAT marbling (IMF-AUMB). Calibration performance was maintained when cross-validated and independently validated. The IMF-MSAMB model described 91% of the variation in MSA marbling score (Residual Standard Error (RSEV) = 57.9), with a slope of 0.90 and very small bias of -0.54. Similarly, IMF-AUMB described 88% of the variation in grader AUS-MEAT marbling (RSEV = 0.68) with a slope very close to 1 (0.94) and negligible bias (0.06). In addition, predicted MQ4 scores were almost equivalent irrespective of which marbling input value was used, across a suite of cut and cook combinations. Therefore, there is an opportunity for models to assist transition to the use of chemical IMF% in place of visual marbling scores. This would enable grading technologies to be calibrated and validated against chemical IMF%, whilst minimising industry disruption.

The association of P2 and lean % estimates from commercial measurement systems with computed tomography determined composition within Australian pork abattoirs.

Pork carcasses were obtained from three abattoirs in Australia (n = 345) where technologies enabled collection of post slaughter measures of P2 fat depth (mm) (Hennessy Grading Probe (HGP), AutoFom III, PorkScan Lite) and estimates of carcass lean % (HGP, AutoFom III, PorkScan Plus). Computed tomography (CT) was used to scan carcasses and determine lean and fat %, with the strength of associations with abattoir measurement devices determined. The AutoFom III lean % demonstrated the strongest associations with whole carcass CT lean % (R2 0.63, RMSE 1.73) and fat % (R2 0.68, RMSE 1.80) and with section (fore, loin, belly and hind) CT composition. The association of P2 from AutoFom III was lower in comparison, however remained superior to other commercial devices (PorkScan Lite and HGP). Porkscan Plus lean % demonstrated moderate associations with whole carcass and section CT lean and fat %, with R2 values generally less than half those of the AutoFom III. The HGP demonstrated weakest associations with CT lean and fat % using either lean % or P2 outputs, which is likely related to data being collected from only the P2 measurement site. This is the first experiment to compare the strength of associations between multiple pork abattoir measurement devices and CT lean and fat % in Australia. P2 is the current industry standard for the assessment of lean yield in pork, however demonstrates weaker associations with carcass CT composition than devices capable of capturing multiple measures across the carcass like AutoFom III and PorkScan Plus.

Improved cut weight predictions from DEXA scans of lamb carcasses enables more accurate allocation of cuts to processing plans.

The value of precise dual energy X-ray absorptiometry (DEXA) cut weight predictions to lamb allocation to cut plans is unknown. Lambs (n = 191) varying in carcase weight (HSCW) and GR (tissue depth over the 12th rib) were DEXA scanned and boned out to weigh retail cuts. Cut weights were predicted using HSCW; HSCW + GR; HSCW + DEXA and HSCW + DEXA image components in GLM models. DEXA improved cut weight predictions in most cuts (P < 0.05). A dataset of 10,000 carcases was then simulated using the associations between HSCW, GR and cut weights, before being truncated to 4500 lambs representing onel day's HSCW distribution. A lamb Carcase Optimisation Tool scenario was developed with 2-3 cut options per carcase section and cut weight thresholds applied to several cuts. Processing costs, market values and actual cut weights were input into the Optimiser to determine carcase allocation to cut options for optimised profits. This scenario was repeated using the predicted cut weights to determine the cut misallocations caused. DEXA-predicted cut weights produced 16.7% and 8.0% less misallocations than HSCW and GR. DEXA produced 20.8% and 14.3% less misallocations than HSCW and GR in shortloins, and 25.5% and 12.9% less in hindquarters. While cut misallocations have little direct impact on total profits, as product is over and under-valued when misallocated, reducing cut misallocations will improve processor compliance when sorting carcases into cut plans- reducing their need to retrim, downgrade and repackage product or the erosion of customer confidence caused by supplying product not meeting market specifications.

Dynamic correction of dual-energy x-ray absorptiometry images improves chain speed prediction of lamb composition in abattoirs.

A prototype, on-line Dual Energy X-ray Absorptiometer (DXA) has shown high precision of the prediction of carcass composition for the purpose of improved sheep meat grading in the Australian lamb supply chain, albeit with small inaccuracies over time. These inaccuracies were present across hours, and more significantly across days, which were unacceptable for any accreditation of this device as an objective carcass measurement tool in Australia. This inaccuracy demanded the creation of a novel image-processing algorithm for the prototype DXA. This DXA was tested for repeatability of predictions of lamb carcass composition over minutes, hours, and days, using two developed image processing algorithms. There was high immediate repeatability for both algorithms when predicting lean muscle % in 40 lamb carcasses, with a maximum CV of 0.65% over five repeated scans. There was a decrease in the CV of the prediction of lean muscle % of 30 lambs scanned three times over a 48-h period from 5.93 to 1.19% when the superior algorithm was used. The inaccuracies of lean muscle % predictions were associated with increases in the unattenuated space pixel values in DXA images. Improvements of the current algorithm are required to demonstrate repeatability over time for the purpose of accreditation within the Australian sheep meat industry, and for possible expansion of this technology into international supply chains.

Validation of a handheld near-infrared spectrophotometer for measurement of chemical intramuscular fat in Australian lamb.

The objective of the study was to independently validate a calibrated commercial handheld near infrared (NIR) spectroscopic device and test its repeatability over time using phenotypically diverse populations of Australian lamb. Validation testing in eight separate data sub-groups (n = 1591 carcasses overall) demonstrated that the NIR device had moderate precision (R2 = 0.4-0.64, RMSEP = 0.70-1.22%) but fluctuated in accuracy between experimental site demonstrated by variable slopes (0.50-0.94) and biases (-0.86-0.02). The repeatability experiment (n = 10 carcasses) showed that time to scan post quartering affected NIR measurement from 0 to 24 h (P < 0.001). On average, NIR IMF% was 0.97% lower (P < 0.001) at 24 h (4.01% ± 0.166), compared to 0 h. There was no difference (P > 0.05) between Time 0 and 1 h or Time 0 and 4 h or between replicate scans within each time point. This study demonstrated the SOMA NIR device could predict lamb chemical IMF% with moderate precision and accuracy, however additional work is required to understand how loin preparation, blooming and surface hydration affect NIR measurement.

Predicting lamb carcase composition from tissue depth measured at a single point with an ultrawide-band microwave scanner.

This study evaluated the ability of portable ultra-wide band microwave system (MiS) to predict lamb carcase computed tomography (CT) determined composition % of fat, lean muscle and bone. Lamb carcases (n = 343) from 6 slaughter groups were MiS scanned at the C-site (45 mm from spine midline at the 12th /13th rib) prior to CT scanning to determine the proportion of fat, muscle and bone. A machine learning ensemble stacking technique was used to construct the MiS prediction equations. Predictions were pooled and divided in 5 groups stratified for each CT composition trait (fat, lean or bone%) and a k-fold cross validation (k = 5) technique was used to test the predictions. MiS predicted CT fat% with an average RMSEP of 2.385, R2 0.78, bias 0.156 and slope 0.095. The prediction of CT lean% had an average RMSEP of 2.146, R2 0.64, bias 0.172 and slope 0.117. CT bone% prediction had an average RMSEP of 0.990, R2 0.75, bias 0.051 and slope 0.090. Predictions for CT bone% met AUS-MEAT device accreditation error tolerances on the whole range of the dataset. Predictions for CT lean% and fat% met AUS-MEAT error tolerances on a constrained dataset.

Adding value to beef portion steaks through measuring individual marbling.

The current Meat Standards Australia (MSA) and AUS-MEAT grading system assumes that marbling through the M. longissmus thoracis et lumborum (loin) is represented by the score of the grading site. However, studies have indicated marbling varies within the beef loin, but commercially individual portion steaks are not graded for marbling. Cube rolls from a wide phenotypic marbling range (n = 102) were collected and sliced into 15 mm portion steaks, which were imaged with a Marel vision scanner to obtain objective marbling scores. Additionally, three locations (grading site, middle, cranial) across each cube roll were tested for intramuscular fat percentage (IMF%). The effect of steak location demonstrated marked variation across the length of the cube roll for both vision scanner marbling scores and IMF%. This variation in vision scanner marbling scores, expressed in units of MSA marbling score, equated to 316 MSA units. This work suggests an opportunity for individual portion marbling measurements and segregation of individual portion cut steaks based upon their marbling levels.

Prediction of chemical intramuscular fat and visual marbling scores with a conveyor vision scanner system on beef portion steaks.

This study describes the performance of a Marel conveyer vision scanner, across beef carcases (n = 102) from a wide visual marbling score range, in its ability to predict chemical intramuscular fat (IMF%), Meat Standards Australia (MSA) and AUS-MEAT marbling scores of portion steaks. Vision scanner marbling scores were acquired on fresh-cut steaks, with its predictions tested using a leave-one-out cross validation method, which demonstrated precise and accurate predictions of IMF% (R2 = 0.87; RMSEP = 1.16; slope = 0.09; bias = 0.22), MSA (R2 = 0.82; RMSEP = 70.11; slope = 0.09; bias = 17.08) and AUS-MEAT marbling (R2 = 0.79; RMSEP = 0.75; slope = 0.16; bias = 0.08). Care must be taken when calibrating devices on non-fresh-cut steak, as fresh-cut steaks produced different vision scanner marbling values suggesting different prediction equations are warranted. The Marel vision scanner prediction of visual grader scores was relatively less precise and accurate than its prediction of IMF%, however in this case it may have been due to error in the grader scores.

Prediction of lamb carcase C-site fat depth and GR tissue depth using a non-invasive portable microwave system versus body condition scoring.

This study compared portable ultra-wide band microwave system (MiS) versus body condition score to predict C-site fat depth, GR tissue depth and eye muscle depth (EMD) in lambs. Experiment 1 assessed MiS and condition score to predict ultrasound measured C-site and EMD (n = 1549). Precision and accuracy was greatest for the MiS measurement with liveweight included in the model, with a C-site predicted RMSEP of 0.58 mm, R2 0.60 and bias of 0.021 mm and an EMD predicted RMSEP of 2.27 mm, R2 0.72 and bias of 0.088 mm. Experiment 2 (n = 900) assessed pre-slaughter MiS scanning and condition scoring to predict carcase GR tissue depth, C-site fat depth and EMD. MiS performed better than condition score for all three carcase trait predictions, regardless of the inclusion of liveweight, with the highest precision and accuracy for GR tissue depth determination with a RMSEP of 3.68 mm, R2 0.63 and bias 0.072 mm.

Bone mineral concentration predicted by dual energy X-ray absorptiometry and its relationship with lamb eating quality.

Lumbar bone mineral concentration, as predicted by dual energy x-ray absorptiometry (DEXA), may reflect changes in lamb maturity and eating quality. New season (n = 60) and old season (n = 60) lambs were slaughtered and DEXA scanned at a commercial abattoir across 2 kill groups. The second lumbar vertebra was isolated from the spine for determination of calcium, phosphorus, and magnesium concentration (mg/g). The loin and rack cuts were collected for consumer sensory grilling and roasting analyses. Mineral concentration was significantly higher in old season lambs within kill group 1 (P < 0.05). DEXA was a positive predictor of phosphorus and calcium concentration, but only when DEXA lean % (P < 0.05) was included in the model. Calcium and phosphorus were significant positive predictors of overall liking scores (P < 0.05), but only for the rack roast. These effects became insignificant when DEXA lean % was included. These results suggest that DEXA values likely reflect changes in both DEXA lean % and bone minerals, and that DEXA lean % was the driver of eating quality, rather than maturity.

Short term magnesium supplementation to reduce dark cutting in pasture finished beef cattle.

This study assessed the capacity of magnesium supplementation to reduce muscle glycogen loss, ultimate pH and increase plasma magnesium in pasture fed slaughter cattle. Beef cattle (n = 1075) from 14 farms were supplemented with or without magnesium pellets for 7-14 days prior to slaughter. Magnesium was allocated at 9.83 g of elemental magnesium per head per day, while the control diet was balanced to be isoenergetic and isonitrogenous, but contained no added magnesium. Groups of cattle (n = 44) were slaughtered at the same processing plant over two consecutive seasons, from August - September 2016 to May - July 2017. Magnesium supplementation increased muscle glycogen (P < 0.01) in cattle supplied from 2 of 14 farms, and increased plasma magnesium in 4 of 14 farms (P < 0.01). Magnesium supplementation had no effect on overall incidence of ultimate pH between the magnesium and control supplementation groups. The benefits of short term magnesium supplementation prior to slaughter was inconsistent for protecting muscle glycogen.

Objective measurement technologies for transforming the Australian & New Zealand livestock industries.

This paper introduces the special edition of Meat Science focused upon the development, calibration and validation of technologies that measure traits influencing meat eating quality, or carcass fat and lean composition. These papers reflect the combined research efforts of groups in Australia, through the Advanced Livestock Measurement Technologies project, and New Zealand through AgResearch. We describe the various technologies being developed, how these devices are being trained upon common gold-standard measurements, and how their outputs are being simultaneously integrated into existing industry systems. We outline how this enhances the industry uptake and adoption of these technologies, and how this is further accelerated by education programs and strategic industry investment into their commercialisation.

Capturing lean distribution in lamb carcases is of more value to the processor than the breeder.

With an increased implementation of chain speed measures of lean weight in lamb processing plants there is the potential for increased feedback of measures for carcase composition to the breeder. The following studies used computed tomography scans of 3167 Merino and Merino cross lamb carcases to determine the importance of capturing variation in carcase, fore, saddle and hind section lean to the processor and the breeder. Sectional measures of lean weight will provide processors with improved precision around the decision making associated with carcase processing and endpoint usage. Genetic correlations between lean (adjusted for carcase weight) within carcase sections ranged from 0.47 to 0.63. Whilst the correlations are moderate, current differences in the value of lean across the carcase does not make it viable for sheep breeders to target disproportional gains in lean across carcase sections. Instead, sheep breeders should continue to target overall carcase lean as part of their breeding objective.

Meat eating and nutritional quality of lambs sired by high and low muscle density rams.

Intramuscular fat (IMF) content affects eating and nutritional quality of lamb meat. Muscle density measured by computer tomography is an in vivo proxy measure of IMF content that affects eating and nutritional quality of lamb meat. Lambs sired by high muscle density (HMD) or low muscle density (LMD) rams, selected for slaughter on commercial criteria were measured for meat quality and nutritional traits. A restricted maximum likelihood model was used to compare lamb traits. Additionally, regression analysis of sire estimated breeding value (EBV) for muscle density was performed for each meat quality trait. Muscle density EBV had a negative regression with IMF content (P < 0.001). For each unit increase in muscle density EBV, there was a significant decrease in loin (-1.69 mg/100 g fresh weight) and topside IMF (-0.03 mg/100 g fresh weight). Muscle density EBV had a negative regression with grouped saturated and monounsaturated fatty acids concentration (and monounsaturated proportion P < 0.001). Muscle density EBV had a negative regression with loin sensory traits tenderness, juiciness and overall liking and many novel tenderness sensory traits measured (P < 0.05). Selecting for LMD EBV increased IMF content and favourable meat eating quality traits. In contrast, sire muscle density EBV had a positive regression with loin polyunsaturated:saturated fat ratio and grouped polyunsaturated proportion traits (including total polyunsaturated proportion, total omega-6 (n-6) and total omega-3 (n-3) fatty acids (P < 0.001). This is explained by the fact that as sire muscle density EBV increases, polyunsaturated fatty acid proportion increases and the proportion of saturated and monounsaturated fatty acid content decreases. Muscle density EBV had a positive regression with shear force and the novel toughness sensory traits (P < 0.05). Selection for HMD EBV's increased shear force and toughness traits, which is unfavourable for the consumer. Low muscle density sired meat had higher meat colour traits chroma/saturation (+0.64, SD 2.30, P = 0.012), redness (+0.52, SD 1.91, P = 0.012) and yellowness (+0.31, SD 1.49, P = 0.08) compared to HMD sired meat. Selection for LMD could be used within a breeding programme to increase IMF content and enhance both meat colour and improve eating quality parameters.

The potential for dual energy X-ray absorptiometry to predict lamb eating quality.

Data were obtained from 120 lambs which were slaughtered, scanned using dual energy X-ray absorptiometry (DEXA) and underwent eating quality assessment. DEXA images were used to determine R values, reflecting atomic mass, to predict carcass lean %. Additionally, bone regions (humerus, lumbar, femur and "all carcass bone") were isolated from images to determine bone specific R values (DEXA R Mean and SDev). Prediction of overall liking of cuts across the carcass (scored between 0 and 100) using lean % and bone DEXA was variable. Loin grill overall liking demonstrated significant associations with lumbar DEXA R Mean and SDev, decreasing by 8.6 and 7.6 units across the increasing range of these bone DEXA measures. This association is somewhat independent of carcass lean % and intramuscular fat % of the loin. Given the association of DEXA with eating quality, there are potential benefits for the lamb industry with respect to carcass sorting and marketing during routine processing and DEXA scanning.

Ultrawide band microwave system as a non-invasive technology to predict beef carcase fat depth.

A portable ultra-wide band microwave system (MiS) coupled with an open-ended coaxial probe (OCP) or Antipodal Vivaldi Antenna (VPA) was tested as a non-invasive objective measurement to predict beef carcase single site fat depth at commercial abattoirs. Experiment one tested the effectiveness of MiS coupled with a VPA. The VPA was used to predict hot carcase P8 (fat depth on the rump) across 4 slaughter groups (n = 241). The VPA was also used to predict cold carcase rib fat (at the quartering site, 75% along the rib eye muscle) across 5 slaughter groups (n = 598). Experiment two tested the ability of MiS coupled with OCP to measure hot carcase P8 across two slaughter groups (n = 435). A machine learning stacking ensemble method was used to create the prediction equations. Datasets were grouped by prediction trait (P8 or ribfat) and probe/antenna then randomly divided into 5 groups based on tissue depth. Precision was greatest using OCP to predict P8 fat depth with a RMSEP of 2.47 mm and R2 of 0.70. The VPA precision was similar for the two tissue depths assessed, hot carcase P8 had an average RMSEP of 2.86 mm and R2 of 0.58 compared to cold carcase rib fat RMSEP of 2.60 mm and R2 of 0.55.