This paper highlights the statistical methodology used in a dissection experiment carried out in Romania to calibrate
and standardize two classification devices, OptiGrade PRO (OGP) and Fat-o-Meat'er (FOM). One hundred
forty-five carcasses were measured using the two probes and dissected according to the European reference
method. To derive prediction formulas for each device, multiple linear regression analysis was performed on
the relationship between the reference lean meat percentage and the back fat and muscle thicknesses, using
the ordinary least squares technique. The root mean squared error of prediction calculated using the leaveone-
out cross validation met European Commission (EC) requirements. The application of the new prediction
equations reduced the gap between the lean meat percentage measured with the OGP and FOM from 2.43%
(average for the period Q3/2006–Q2/2008) to 0.10% (average for the period Q3/2008–Q4/2014), providing the
basis for a fair payment system for the pig producers.