Carcase grading reflects the variation in beef yield - a multivariate method for exploring the relationship between beef yield and carcase traits.

Beef carcases in Europe are classified as a proxy for the quantity and ratio of tissues, commonly referred to as yield. It is important that proxies accurately measure yield as they contribute to financial transactions between abattoirs and producers. The main purpose of the study was therefore to examine the ability of EUROP carcase classification to explain the variation in yield. Furthermore, the effect of breed, as a confounder, was also examined. A multivariate definition of yield separating the carcase into six product categories was utilised as a response in a linear regression analysis. The conclusion was that EUROP and carcase features explain the majority of yield variation. Breed has an effect on yield beyond what is explained by carcase features including classification. The magnitude of the breed effects varies with breed and product category.

Computed tomography for quantitative determination of sodium chloride in ground pork and dry-cured hams.

Seventy-five ground meat and fat samples of pork with varying composition of sodium chloride (0% to 16%), fat (1% to 82%), protein (1% to 46%), and water (13% to 76%) were scanned by X-ray computed tomography (CT) at 110 kV. The dependency of CT value on chemical composition and the linear relationships between sodium chloride (NaCl) and CT value were modeled. When all ground samples were used for modeling and no information of chemical composition was included in the model, the prediction error for NaCl was 2.8%. Adding information on fat or protein content to the model reduced the error to 1.6%. A minimal prediction error of 0.2% for NaCl was found when the variation in chemical composition was strongly reduced. In addition, 22 samples of dry-cured ham lean and fat tissues at different processing stages were CT scanned; their chemical compositions were 0% to 14% NaCl, 1% to 85% fat, 5% to 33% protein, and 7% to 76% water. The NaCl content in dry-cured ham samples was modeled with prediction errors of 0.6% to 2.1%, depending on which chemical component was included in the models. In general, predictions were improved if either the range of concentrations was reduced or information of chemical composition was included in the models. Important sources of error in the models were the reproduction error for ground samples, and for ham samples the analytical errors in determining the chemical composition.