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...
Saved in:
Published in | Meat science Vol. 199; p. 109141 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier Ltd
01.05.2023
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | 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.
•The conveyor vision scanner predicts chemical IMF% with good precision and accuracy.•The conveyor vision scanner predicts visual marbling scores with good precision and accuracy.•Inclusion of high marbling scores reduced the predictability of the validation tests.•The grading steak produced different prediction outcomes than freshly cut steaks. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0309-1740 1873-4138 |
DOI: | 10.1016/j.meatsci.2023.109141 |