Post-slaughter carcass evaluation in whiteheaded mutton sheep according to the EUROP classification

Analyses were conducted on 120 lambs of the whiteheaded mutton sheep (60 tup lambs and 60 ewe lambs). Lambs were weaned at the age of 60 ± 3 days. Lambs were fattened using pelleted balanced feed. 1 kg of feed contained 860 g dry matter, 147 g crude protein and 6.9 MJ (net energy). On the day of slaughter (100 ± 3 days), tup lambs weighed an average of 33.1 kg and ewe lambs weighed 31.0 kg. After slaughter, a point score conformation and fatness evaluation was performed according to the EUROP classification (E is excellent, U is very good, R is Good, O is fair and P is poor), carcass measurements were taken, and the tissue composition of the half-carcass was determined on the basis of complete dissection. In terms of conformation, the carcasses of tested lambs of both sexes were classified to three grades, that is, E: 14.2%, U: 60.8% and R: 25.0%, respectively. A total of 76.7% carcasses of tup lambs and 73.3% ewe carcasses were classified to two highest grades, that is E and U. In terms of fatness, carcasses were classified to 4 grades, denoting small and medium fatness, that is, 2: 15.0%, 3L: 56.7%, 3H: 20.0% and 4L: 8.3%. A higher number of carcasses with the most desirable degree of fatness (grades 2 and 3L), came from tup lambs (78.3%) than ewe lambs (65.0%). A comparison of the subjective EUROP classification with the results of evaluation based on measurements and complete dissection shows that when evaluating conformation, it was not possible to determine precisely the tissue composition of the carcass. In turn, fatness evaluation may be informative on tissue contents in the carcass.Keywords: Lamb, carcass composition, EUROP classificatio

Use of entropy in the analysis of nominal traits in sheep

In the analysis of dependencies between nominal traits entropy and its function, mutual information seems to be a proper descriptive statistic. This is shown by characterizing the relationships between the prolificacy of dams and selected genetic attributes: the genotype of transferrin, the genotype of hemoglobin, and the type of birth, as well as the environmental attribute, i.e., year of birth. The entropy method may improve the exactitude of investigations concerning the influence of different factors on production trait. The index of relative uniformity, introduced in this study, proved to be an adequate tool for the determination of similarity in the examined flocks. The application of mutual information in the determination of values of the dependence measures in the analyzed experiment was justified

Interaction between the level of immunoglobulins and number of somatic cells as a factor shaping the immunomodulating properties of colostrum

The aim of this study was to investigate the association between immunoglobulins and SCC as a factor in shaping the content of the immunostimulatory components of colostrum. Seventy-eight multiparous Polish Holstein–Friesian cows were selected for the experiment. Colostrum samples were collected immediately after calving (up to a max. of 2 h). The cows were divided into groups according to the following levels: Immunoglobulins (IG class)—(IG1) over 50 g/L, (IG2) up to 50 g/L; SCC class—(SCC1) up to 400 000/ml, (SCC2) 400–800 000/ml, (SCC3) over 800 000/ml. Colostrum assigned to the IG1 SCC1 group had a statistically significant higher (p ≤ 0.01) concentration of both whey proteins and fatty acids compared to the IG1 SCC2 and SCC3 groups. The concentration of IgG, IgM, and IgA was shown to be higher in IG1 SCC1 than IG2 SCC3 by 226%, 149%, and 115%, respectively. The concentration of lactoferrin was shown to be higher in IG1 SCC1 than IG2 SCC3 by 149%. The determination of colostrum quality based on the concentration of immunoglobulins in the colostrum may not be sufficient because serum IgG concentrations at birth show a linear increase relative to colostrum SCC. A breakdown of colostrum into quality classes, taking into account the level of SCC, should therefore be introduced

Welfare Health and Productivity in Commercial Pig Herds

In recent years, there have been very dynamic changes in both pork production and pig breeding technology around the world. The general trend of increasing the efficiency of pig production, with reduced employment, requires optimisation and a comprehensive approach to herd management. One of the most important elements on the way to achieving this goal is to maintain animal welfare and health. The health of the pigs on the farm is also a key aspect in production economics. The need to maintain a high health status of pig herds by eliminating the frequency of different disease units and reducing the need for antimicrobial substances is part of a broadly understood high potential herd management strategy. Thanks to the use of sensors (cameras, microphones, accelerometers, or radio-frequency identification transponders), the images, sounds, movements, and vital signs of animals are combined through algorithms and analysed for non-invasive monitoring of animals, which allows for early detection of diseases, improves their welfare, and increases the productivity of breeding. Automated, innovative early warning systems based on continuous monitoring of specific physiological (e.g., body temperature) and behavioural parameters can provide an alternative to direct diagnosis and visual assessment by the veterinarian or the herd keeper