Per Horn

Prediction of technological quality (cooking loss and Napole Yield) of pork based on fresh meat characteristics

In order to investigate if cooking loss and Napole Yield can be predicted from various fresh meat characteristics, pH (1, 15, 30, 60, 120 min and 24 h post mortem), temperature (1, 15, 30, 60, 120 min and 24 h post mortem), water-holding capacity (Honikels drip loss method and centrifugation loss), and NMR T2 relaxation 24 h post mortem were measured in fresh porcine M. longissimus dorsi from 102 Hampshire crossbreeds of known RN(-) genotype. Subsequently, cooking loss and Napole Yield were determined on cooked and cured, cooked samples, respectively, and partial least squares regression (PLS) was carried out to investigate possible intercorrelations between the physico-chemical measurements performed on the fresh meat and cooking loss/Napole Yield. Significant correlations were found between NMR T2 relaxation measured in fresh pork 24 h post mortem and the cooking loss (R=0.64) and Napole Yield (R=0.58), whereas no correlations were found between traditionally applied methods such as pH measurements, Honikels method and centrifugation, and the cooking loss/Napole Yield. Consequently, it is concluded that NMR T2 relaxation characteristics of fresh pork in contrast to traditional fresh meat characteristics contain information about factors of importance for cooking loss/Napole Yield from cooked uncured/cured pork. The result implies that low-field (LF) NMR data from fresh meat reflects information about water compartmentalisation and mobility that is partly decisive for subsequent heat-induced changes of importance for the distribution of water within the cooked meat. In addition, the obtained results show that LF NMR data measured on fresh meat also seems to contain information about the inherent water of importance for the technological characteristics of the meat even when the meat is cured before cooking.

Functional genomics in farm animals – Microarray analysis

The rapid progression of farm animal genomics has introduced novel technologies capable of presenting global descriptions of biological systems at the level of gene and protein expression and protein interaction. To fully benefit from these developments, experimental designs have to be adapted to these new technologies, and important considerations must be made in the choice of technologies and methods of analysis to be used. This paper addresses practical issues in the use of microarray based methods for gene-expression analysis in farm animals, and provides an overview of different array-platforms as well as a presentation of methods and software for the analysis of array data. Experimental design and the selection of animals and samples for microarray studies in farm animals present novel challenges, which are often overlooked. In particular, the frequent use of half sibs and full sibs in animal studies increases the risk of falsely identifying genes as being differentially expressed, due to genetic linkage of the gene to a QTL or a major gene affecting the trait in question.