Testing MRI and image analysis techniques for fat quantification in meat science

The world of meat faces a permanent need for new methods of meat quality evaluation. Recent advances in the area of computer and video processing have created new ways to monitor quality in the food industry. Here, the authors describe an image processing technique to determine fat content in beef meat. To achieve this NMR (Nuclear Magnetic Resonance) images of beef meat have been used. The inherent advantages of NMR images are many. Chief among these are unprecedented contrasts between the various structures present in meat, as muscle, fat, and connective tissue. Moreover, the three-dimensional nature of the NMR method allows the analysis of isolated cross-sectional slices of the meat and the measure of volumetric content of fat, no only the superficially visible one. The authors propose a segmentation algorithm for the detection of fat and a filtering technique to remove intensity inhomogeneities in NMR images, cause by non-uniformities of magnetic field during acquisition. Measurements have been successfully correlated with chemical analysis and digital photography. The authors also propose a method to quantify the distribution of fat. Their results show that NMR technique is a promising non-invasive method to determine fat content in meat.