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.

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.

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.

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

The experiment evaluated the ability of portable ultra-wide band microwave coupled with a Vivaldi patch antenna to predict carcase C-site fat and GR tissue depth. For C-site, 1070 lambs, across 8 slaughter groups were scanned and for GR, 286 lambs across 2 slaughter groups. Prediction equations for reflected microwave signals were constructed with a partial least squares regression two-components model and a machine learning Ensemble Stacking technique. Models were trained and validated using cross validation methods in actual datasets and then in datasets balanced for tissue depth. The precision and accuracy indicators of microwave predicted C-site fat depth across pooled and balanced datasets were RMSEP 1.53 mm, R2 0.54, and bias of 0.03 mm. The precision and accuracy for GR tissue depth across pooled and balanced datasets were RMSEP 2.57 mm, R2 0.79 and bias of 0.33 mm. Using the AUS-MEAT fat score accreditation framework this device was able to accurately predict GR 92.7% of the time.

Using dual energy X-ray absorptiometry to estimate commercial cut weights at abattoir chain-speed.

This experiment assessed the ability of an on-line dual energy x-ray absorptiometer (DEXA) installed at a commercial abattoir to determine commercial cut weights in lamb carcases at abattoir chain-speed. 200 lamb carcases were scanned using a DEXA that was trained to predict the computed tomography determined proportions of fat, lean, and bone. Models were then trained using hot carcase weight and, DEXA fat% value or GR tissue depth to predict cut weight. Results from validation tests of DEXA models demonstrated excellent precision for predicting cut weight, in most cases describing more than 85% of the variation, and RMSE values that represented between 5 and 13% of the average weight of each cut. For most cuts these weight predictions were superior to those informed by GR tissue depth. This precision was maintained upon validation. Additional analyses utilised pixel information from the fore, saddle, and hind sections of DEXA images. This further enhanced the predictive power of cut weight models.

A prototype rapid dual energy X-ray absorptiometry (DEXA) system can predict the CT composition of beef carcases.

The development of a novel rapid dual energy X-ray absorptiometry (DEXA) system provides the opportunity to improve measurement of beef carcase composition. A prototype rapid DEXA system was built in a shipping container to scan 51 beef carcases selected for a wide range in weight and fatness. One side of each carcase was spray chilled and the other conventionally chilled overnight before being quartered for DEXA scanning and then being cut into 16 pieces for CT scanning to determine carcase composition. Spray chilling did not impact DEXA prediction of CT composition, with the DEXA system describing 89%, 95%, and 87% of the variation in beef carcase CT lean %, fat % and bone %, with a root mean square error of prediction of 2.31 lean %, 2.15 fat %, and 1.12 bone % units. These results demonstrate that the novel rapid DEXA system has excellent capacity to predict CT composition in beef carcases.

Association between visual marbling score and chemical intramuscular fat with camera marbling percentage in Australian beef carcasses.

This study assessed the precision and accuracy in the prediction of chemical intramuscular fat (IMF%), Meat Standards Australia (MSA) marbling score and AUS-MEAT eye-muscle area (EMA) using Meat Imaging Japan (MIJ) prototype camera systems. Eleven carcass datasets from the Beef Information Nucleus (BIN) project were compiled with carcass grading, IMF% and camera data. Camera prediction of IMF%, MSA marbling score and EMA was assessed using a leave-one-out cross validation method. There was an association between MIJ mirror and MIJ-30 camera traits and IMF%, MSA marbling score and EMA. However, for both prototypes precision varied for IMF% (R2 = 0.4-0.5, RMSECV = 1.5-1.6%), MSA marbling (R2 = 0.3-0.5, RMSECV = 57.5-59.3) and EMA (R2 = 0.7-0.6, RMSECV = 4.1-5.8 cm2). Accuracy also fluctuated with average bias values of 1.7-1.8%, 45.8-40.0 units and 3.8-4.1 cm2 for IMF%, MSA marbling score and EMA respectively. Key differences between carcass and camera traits and processing factors affecting the grading site are likely to have contributed to this variation.

Objective grading of eye muscle area, intramuscular fat and marbling in Australian beef and lamb.

The objective of this study was to test the performance of a prototype vision system in phenotypically diverse beef and lamb carcasses against visual grading of eye muscle area (EMA), marbling and chemical intramuscular fat (IMF%). Validation in beef demonstrated that the camera prototype in combination with analytical techniques enabled prediction of EMA (r2 = 0.83, RMSEP = 6.4 cm2), MSA marbling (r2 = 0.76, RMSEP = 66.1), AUS-MEAT marbling (r2 = 0.70, RMSEP = 0.74) and chemical IMF% (r2 = 0.78, RMSEP = 1.85%). Accuracy was also maintained on validation with all four traits displaying minimal bias of -3.6, 6.3, 0.07 and - 0.01, for EMA, MSA marbling, AUS-MEAT marbling and IMF% respectively. Preliminary analysis in lamb indicates potential of the system for the prediction of EMA (r2 = 0.41, RMSEP = 1.87) and IMF% (r2 = 0.28, RMSEP = 1.10), however further work to standardise image acquisition and environmental conditions is required.

Prediction of consumer palatability in beef using visual marbling scores and chemical intramuscular fat percentage.

With development of objective technologies that can predict chemical intramuscular fat percentage (IMF%), there is a need to understand the relationships between existing marbling traits, IMF% and eating quality. This study utilised historical carcass data (n = 9641 observations) from the Meat Standards Australia (MSA) industry research dataset and included MSA grading data, chemical IMF% data and weighted composite eating quality scores (MQ4). Several analyses were performed to assess the prediction of MQ4 by MSA marbling, M. longissimus thoracis et lumborum (striploin) IMF% and cut specific IMF%. Results demonstrated that there was similar precision between chemical IMF% (R2 = 0.32, RSE = 11.8) and MSA marbling (R2 = 0.28, RSE = 11.9) in the prediction of grilled 14 day aged striploin MQ4, with similar results across other cut by cook by days aged combinations. These results support the development of objective technologies that predict chemical IMF% in parallel with MSA marbling for carcass grading and the prediction of eating quality.