Utilization of image processing to quantitate surface metmyoglobin on fresh beef

Ground beef patties were manufactured with various combinations of ascorbic acid and mechanically recovered neck bone lean (MRNL) to study the use of image processing in predicting percentage surface metmyoglobin (metMb) on fresh beef. Ascorbic acid and MRNL cause various color phenomena that resulted in a wide range of variation in surface color. Patties were also stored over six days of retail display to cause further color changes. Surface color was assessed by several different accepted methods. A prediction equation for percentage surface metMb included mean values for hue, saturation and intensity. Root mean square error, R-square and Mallow's Cp statistic were used as selection criteria for choosing the best predictive model. Image processing hue, saturation and intensity accounted for 93% of the variation in percentage surface metMb. Since hue, saturation and intensity each contribute to overall color profile it is logical that these parameters are good predictors. These data indicate that image processing is capable of objectively measuring percentage surface metMb.