A. Högberg

Fatty acid composition and tocopherol concentrations in muscle of entire male, castrated male and female pigs, reared in an indoor or outdoor housing system

The objective of this study was to investigate the effect of outdoor rearing on the fatty acid (FA) composition and contents of tocopherols of M. longissimus dorsi polar (PL) and neutral lipids (NL) in entire males, castrated males and female pigs. Fat content did not differ between genders or rearing conditions. In PL of the indoor pig muscle the level of n-6 highly unsaturated fatty acids (HUFA) was higher in females and entire males compared with castrated males. The outdoor environment resulted in a slightly higher level of n-3 polyunsaturated FA (PUFA) in muscle PL and NL of entire males compared with females and castrated males. We also found an increased level of 18:2 n-6 in the muscle PL of outdoor reared females compared with the indoor females. The higher levels of PUFA in the entire male muscle, in both PL and NL, were not accompanied by a higher level of vitamin E.

A segmentation technique to determine fat content in NMR images of beef meat

There is a constant 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. In this paper, we describe an image-processing technique to determine fat content in beef meat. To achieve this, nuclear magnetic resonance (NMR) 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, such 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 the volumetric content of fat, and it is not limited to measurements of the superficially visible fat. We propose a segmentation algorithm for the detection of fat and a filtering technique to remove intensity inhomogeneities in NMR images, caused by nonuniformities of magnetic field during acquisition. Measurements have been successfully correlated with chemical analysis and digital photography. We also propose a method to quantify the distribution of fat. Our results show that the NMR technique is a promising noninvasive method to determine fat content in meat.

Color image analysis technique for measuring of fat in meat: an application for the meat industry

Intramuscular fat content in meat influences some important meat quality characteristics. The aim of the present study was to develop and apply image processing techniques to quantify intramuscular fat content in beefs together with the visual appearance of fat in meat (marbling). Color images of M. longissimus dorsi meat samples with a variability of intramuscular fat content and marbling were captured. Image analysis software was specially developed for the interpretation of these images. In particular, a segmentation algorithm (i.e. classification of different substances: fat, muscle and connective tissue) was optimized in order to obtain a proper classification and perform subsequent analysis. Segmentation of muscle from fat was achieved based on their characteristics in the 3D color space, and on the intrinsic fuzzy nature of these structures. The method is fully automatic and it combines a fuzzy clustering algorithm, the Fuzzy c-Means Algorithm, with a Genetic Algorithm. The percentages of various colors (i.e. substances) within the sample are then determined; the number, size distribution, and spatial distributions of the extracted fat flecks are measured. Measurements are correlated with chemical and sensory properties. Results so far show that advanced image analysis is useful for quantify the visual appearance of meat.

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.