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

Abstract

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 (RSE_V) = 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 (RSE_V = 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.