Estimation of genetic parameters and genotype effects for crossing constructions of Hungarian Pigs

Authors estimated the genetic parameters and genotype effects of average daily gain (ADG), age (AGE) and lean meat percentage (LMP) using the field test data of Pietrain (Pi), Duroc (Du), Hampshire (Ha) pigs and their crosses. Data was collected by the Agricultural Agency of Administration between 1998 and 2010 originating from 68 herds. Datasets of the different crossing combinations (Pi, Du, Pi × Du; Pi, Ha Pi × Ha) were evaluated separately using bivariate animal models. The estimated heritabilities were moderately low: 0.24–0.29, 0.22–0.26 and 0.18–0.19 for average daily gain (ADG), age (AGE) and lean meat percentage (LMP), respectively. The estimated genetic correlation coefficients were negligible: -0.07–0.01 (ADG-LMP), -0.01–0.04 (AGE-LMP). The Pi × Ha and Pi × Du crosses showed 6.76% and 4.96%; 6.74% and 4,17% and 0.08% and 0.44% heterosis for ADG, AGE and LMP, respectively. Among the environmental factors the herd effects were substantial: 41.17%, 53.67% and 14.16% for AGD, AGE and LMP, respectively. The smallest environmental influences were found for LMP

Genetic Parameters of Growth Traits from a Joint Evaluation of Purebred and Crossbred Pigs

Authors analyzed average daily gain and lean meat percentage of the Pietrain (Pi), Duroc (Du) and their cross (PixDu); Pietrain (Pi) and Hampshire (Ha) and the cross (PixHa) using the national database for the period of 1997-2010. The heritability estimates for average daily gain (0.20±0.02, 0.24±0.02, 0.25±0.03, 0.37±0.06, 0.37±0.02 for Pi, Du, PixDu, Ha, PixHa, respectively); and lean meat percentage (0.17±0.02, 0.15±0.02, 0.13±0.02, 0.22±0.06, 0.20±0.02 for Pi, Du, PixDu, Ha, PixHa, respectively) were low. Genetic correlation between the purebreds and the crossbreds ranged from moderately high to high for average daily gain (0.93±0.15, 0.85±0.12, 0.56±0.14, 0.75±0.12) and from moderate to moderately high for lean meat percentage (0.65±0.16, 0.56±0.16, -0.38±0.17, 0.48±0.20) for Pi – PixDu, Du – PixDu, Ha – PixHa, Pi – PixHa, respectively. Based on the results the selection of the purebred parents for crossbred pigs can be based on the performance of their purebred breeding values of average daily gain. On the contrary for lean meat percentage the crossbred breeding values of the purebred pigs can also be used to select the best purebred pigs for crossing

Review of diagnostic signs of postpartum uterine diseases in dairy cows by the help of catus database

Postpartum (PP) reproduction anomalies (increased calving interval and semen doses, pregnancy loss, infertility culling rate) are mostly caused by postpartum uterine diseases. The aim of this study was to find diagnostic symptoms (signs) help in identifying animals having possible subclinical endometritis. As a logical first step, analyzing a database with several thousand transrectal postpartum palpations and ultrasonic findings of the genital tract and production data of dairy cows (CATUS) seemed reasonable. Healthy (H) cows and animals with clinical endometritis (CE) both are in this database. We thought that statistical analysis of large amount of H and CE animals’ data should help in identifying signs or reasonable suspicion for recognizing cows with subclinical endometritis (SCE) in the future as well. During this work palpation and ultrasound data of healthy and CE cows were compared. Totally, data of 10683 cows were evaluated by chi-square test. These results show distinct differences in distribution of uterine size (volume) and ovarian phenomena in the two groups. As a sign of inappropriate involution large-sized uterus (32.9 % vs. 64.9 %) and uterine fluid content (6.1 % vs. 31.1 %) were significantly higher (p<0.0001) in CE group. Abnormal ovarian ovulatory phenomena (corpus luteum /CL/ with cavity: 8.0 % vs. 13.1 %; or cystic CL: 4.2 % vs. 27.4 %) also were detected in significantly higher numbers in animals with CE signs (p<0.0001). These results induce further examinations to compare them with SCE animals’ data for identifying diagnostic signs which are typical for the examiners