Search

The EUROP classification system is based on visual assessment of carcass conformation and fatness. The first objective was to test the EUROP classification repeatability and accuracy of the national senior assessors of the system in Norway. The second objective was to test the accuracy of the trained and certified abattoir EUROP classifiers in Norway relative to EU Commission's supervising assessors. The third and final objective was to test the accuracy of the EUROP classification system, as assessed by the National senior assessors, for prediction of lean meat, fat and bone percentage and lean meat in relation to bone ratio. The results showed that the repeatability and accuracy of the national senior assessors was good, achieving high correlations both for conformation and fatness. For the abattoir assessors, there were some systematic differences compared to EU Commission's assessors, but these differences were within limits accepted by EU Commission. The relationship between abattoir and national senior assessors was good, with only small systematic differences. This may suggest that there also is a systematic difference between the national senior assessors of the system and EU Commission's assessors. The EUROP system predicted lean meat percentage poorly (R(2)=0.407), with a prediction error for 3.027% lean. For fat and bone percentage, the results showed a fairly good prediction of fat percentage, but poorer for bone percentage, R(2)=0.796 and R(2)=0.450, respectively. The prediction error for fat and bone percentage was 2.300% and 2.125%, respectively. Lean: bone ratio was predicted poorly (R(2)=0.212), with a prediction error of 0.363 lean: bone ratio.

Gas sensor array technology combined with multivariate data processing methods as artificial neural network has been demonstrated to have a promising potential for rapid nondestructive analysis of odour and flavour in foods. It may be applicable in quality control of raw material, food processing or products. This technique cannot completely replace reference methods like the use of sensory panels as the technique requires a frequent calibration against some valid reference method. As with all new techniques there remain some basic problems to be solved concerning sample handling and instrumental performance. The emerging research activity in the development of chemical sensors including hardware and software combined with applied research makes it realistic to expect applications with this technique implemented on-line in the food industry in near future. In particular, promising applications on meat seem to be within the field of spoilage, off-flavour, sensory analysis and fermentation processes.