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Several objective methods for estimating pork quality were studied: internal light scattering (FOP), electrical conductivity (EC), pH, colour, water holding capacity (WHC), soluble proteins (SP), pigment content, intramuscular fat (i.m. fat), and moisture. The measurements were made on the Semimembranosus and Longissimus thoracis at 45 min and 24 h post mortem in some cases and on the Semimembranosus in others. Most of the measurements are significantly different between normal, PSE and DFD quality categories. There is a good correlation between pH values in both muscles: pH(45)SM-pH(45)LT (r=0.74) and pH(24)SM-pH(24)LT (r=0.71). At 45 min the correlation of EC with FOP and pH was r=0.56 and r=0.48 respectively. Lower correlations were found in other parameters. The results from principal component analysis (PCA) showed that the three first components explained 60.3% of the total variation and the most important variables for the first PC were pH(45) and EC(45)., (Copyright © 1994. Published by Elsevier Ltd.)

Meat quality is one of the principal problems in Spanish dry cured ham productuon. At the experimental level, there are well developed objective instrumental measurements which can be made on the slaughterline and then, by applying the correct statistical treatment, these measurements can be used to classify hams with an acceptable degree of accuracy. These treatments, however, are not easy to apply in the industry. In this work, 312 pork carcasses were tested at three industrial abbatoirs. Ham meat quality was determined by internal light scattering (FOP), electrical conductivity (EC) and pH measurements in Semimembranosus (SM) muscle at 45 min and 24 h post mortem. The results obtained were: 21 (6.7%) DFD; 168 (53.9%) slightly DFD; 104 (33.3%) normal; 11 (3.5%) slightly PSE; and 8 (2.6%) PSE. A simplified method has been developed for classifying hams into quality categories, by deriving a theoretical quality value (Q) based on a simple statistical treatment of values for FOP, EC and pH. The multiple linear regression coefficient of Q was R(2) = 0.85 (P<0.001) with respect to the experimental variables., (Copyright © 1994. Published by Elsevier Ltd.)