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.

Application of Ultrasound Images Texture Analysis for the Estimation of Intramuscular Fat Content in the Longissimus Thoracis Muscle of Beef Cattle after Slaughter: A Methodological Study

Simple Summary

Fat content in the muscle mass (IMF) is one of the most important characteristics influencing the aroma, tenderness, and juiciness of the meat and therefore has high importance for both commercialization purposes and consumers. However, IMF determination currently relies on visual inspection, which is a subjective and inconsistent technique. The aim of the present study is the elaboration of a procedure capable of predicting IMF% in beef carcasses using ultrasound imaging texture analysis. Ultrasound images taken on meat samples were compared to meat composition measured by chemical extraction. Determination coefficient between the two techniques was R² = 0.76, while Receiver Operating Characteristic analysis showed a sensitivity of 88% and a specificity of 90%. The results therefore suggest that the described procedure is expected to determine IMF% in muscle with good accuracy. Ultrasound imaging could be applied in routine beef grading practices. This may help to solve the issues related to subjectivity and leave to the operator only imaging acquisition. Better consistency in beef products could enhance consumers’ satisfaction and commercial standardization programs.

Abstract

Intramuscular fat (IMF) is a major trait in the evaluation of beef meat, but its determination is subjective and inconsistent and still relies on visual inspection. This research objective was a method to predict IMF% from beef meat using ultrasound (US) imaging texture analysis. US images were performed on the longissimus thoracis muscle of 27 Charolaise heifers. Cuts from the 12th to 13th ribs were scanned. The lipid content of the muscle samples was determined with the petrol ether (Randall) extraction method. A stepwise linear discriminant analysis was used to screen US texture parameters. IMF% measured by chemical extraction (IMFqa) was the dependent variable and the results of the texture analysis were the explanatory variables. The model highlighted seven parameters, as a predictive and a multiple regression equation was created. Prediction of IMF content (IMFpred) was then validated using IMFqa as ground truth. Determination coefficient between IMFqa and IMFpred was R² = 0.76, while the ROC analysis showing a sensitivity of 88% and a specificity of 90%. Bland-Altman plot upper and lower limit were +1.34 and −1.42, respectively (±1.96 SD), with a mean of −0.04. The results from the present study therefore suggest that prediction of IMF content in muscle mass by US texture analysis is possible.

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.