An observational retrospective study was done to provide up-to-date information on recent sow removal patterns from 9 breed-wean herds of Midwest USA. The study comprised of sow’s removal reasons and removal types of F1 Landrace x Yorkshire gilts entered in the herds between 1st Jan 2014 and 31st July 2016. Data was extr...acted from existing database on Dec 2018 and 15% of the sows were still active in the herds hence not included in the study. Descriptive statistics showed that out of the 20,009 removed sows, planned removals comprised of farrowing productivity (FP) 3,523 (17.6%) and old age (OA) 1,785 (8.9%) while unplanned removals consisted of reproductive failure (RF) 7,786 (38.9%), health problems (HP) 2,629 (13.1%), locomotion problems (LP) 1,473 (7.4%) and conformation issues (CI) 1,350 (6.8%).‘Did not conceive’ and “No heat” were observed as the main contributing factors accounting for 37.6% and 32.9% respectively for gilts & sows removed by RF.13.5% of the gilts (Parity 0) were removed from the herds before attaining their first litter of which 64.1% of their removals was due to RF. Removal type consisted of slaughter (S) 85.0%, found dead on the farm (DoF) 10.8% and euthanized (E) 4.2%. The research findings depict an upward trend of sow RF removals in the US swine herds posing a serious concern for US swine producers. Characterization and quantification of sow removals gives a revelation on the deeper intrigues about the vulnerability of the various parity in respect to common causes of RF. This helps swine producers to decisively improve on gilt replacement selection, reproductive efficiency, health and nutrition management all aimed at increasing overall swine productivity and efficiency in management. Swine farmers in the US can now focus their efforts towards curbing unnecessary RF removal within parity specifics.
Researches are being performed around the world to increase swine prolificacy by using marker-assisted selection (MAS). The present study processes researches of polymorphism examinations on 7 genes. The result of the experiments showed that the leptin gene (LEP) prolactin receptor gene (PRLP), estrogen receptor gene (ESR), properdin B (BF) epi...dermal growth factor (EGF), follicle-stimulating beta gene (FSH-ß) and Z member of the H2A histon family gene (H2A.Z) and their alleles have a positive effect on reproductive characteristics of different swine breeds. In addition to this, leptin gene (LEP) influences the build, meat production and growth of body fat. Further studies are concerned with the polymorphism of an increasing number of genes, which enables a faster genetic development of swine breeding.
In 1990ys antiatherogen, antioxidant and anticarcinogen effect of conjugated linolacids (CLA) was detected. From this reasons, our aims in this study were producing pork rich in CLA and studying the change of fatty acid composition of the produced pork cooked different kind of fats. For frying palm and sunflower oil and swine fat were used. Thi...gh was cutted for 100 g pieces. Meat pieces were fried at 160 °C for 1 and 8 minutes. Estimation of frying data it was determined that higher (0.13%) CLA content of pork was spoiled (60-70%) except in case of swine fat cooking,
because it is extremly sensitive for oxidation and heating. Swine fat has higher (0.09%) CLA content than plant oil, protecting the meat’s original CLA content. Cooking in swine fat did not have significant effect on fatty acid composition of meat. Low level of palmitic acid contect of sunflower oil (6.40%) decreased for half part of palmitic acid content of pork (24.13%) and it produced cooked meat with decreased oil acid content. Contrary of above, linoleic acid content of fried meat was increased in different folds as compared to crude pork. If it was fried in sunflower oil with high level linoleic acid increased (51.52%) the linoleic acid content in fried pork. The linoleic acid content of the high level CLA pork increased four times (48.59%) to the crude meat (16.59% and 12.32%). The high palmitic acid content of palm fat (41.54%) increased by 60% the palmitic acid content in fried pork, low stearic acid (4.44%) and linoleic acid content (10.56%) decreased the stearic and linoleic acid content of crude meat.
Cluster Analysis is one of the most favorite multivariable statistical methods, which is actually a special type of aggregating method. Observations are clustered by variables belonged to the observations. Our purpose is to create such clusters, in which the elements are the most similar, and between the clusters they are the most variant. For...example these clusters could be the qualitative classifications of farms.
There have been several methods in Cluster Analysis as well as numerous distance measures, which could be used. In this article, we study all of these methods and measures. After we show the theoretical background, we apply the method in a given casestudy to control the qualitative classifications of experts. In this study, we use both the hierarchical and the non-hierarchical method, and also compare them. We would like to attract the attention that the most important problem of the analysis is to determine the optimal of clusters.
The aim of the present study was to perform lifetime performance analysis in three pig breeds; Hungarian Large White (n=295), Duroc (n=76) and Pietrain (n=91) on a commercial farm using analysis of survival sows. We took into consideration the age of sows at the time of their inclusion into breeding, their age at the time of culling, time spent... in production, number of mating and parities, parity percentage, intervals between litters, number and mean of piglets born alive and born dead, number of raised piglet litters, number and mean of 21 days old piglets, the weight and mean of raised litter and raise percentage.
We carried out the analysis by SPSS 22.0. Single factor analysis of variants, Kaplan-Meier analysis and Cox PH model were used. The determination of the significance of risk rates differences was done by Wald chi square test.
Our results showed that the average culling age were 1056 (±33.52) days for the Hungarian Large White, 735 (±73.56) days for Duroc and 818 (±71.98) days for the Pietrain.
The log rank test of the survival analysis indicated a significant difference between the three tested genotypes (χ2=16.981, P<0.001), which means that the survival percentage of the individual breeds varied significantly from one another. In comparison with the Hungarian Large White genotype the Duroc genotype has a 1.6 times higher (P<0.001) culling risk while that of the genotype Pietrain was 1.36 times higher (P<0.001).
Our results can be used to compare the breeds kept under the same conditions and to compare the life span of one genotype under different farming conditions. Factors that increase survival and improve the profitability of pig farming can be determined by this method.
...5); font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;">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.
Heat No Service (HNS) is an increasing managerial decision made in commercial piglet producing herds. Performance of gilts has been shown to be influenced by initial decisions made on them at their introduction in the breeding herds. Lifetime Reproductive performance comprising of parity total born piglets and lifetime total born piglets of... gilts initially bred on first observed estrus (0HNS) was compared with that of gilts bred on second observed estrus (1HNS). Stored data from Porcitec database consisted of 2.072 gilts bred on first observed estrus (0HNS) and 2.453 gilts bred on second observed estrus (1HNS) totaling to 4.525 gilts. Data was statistically analyzed using the GLM procedure of IBM SPSS version 25. The results showed a significance difference (p<0.001) in lifetime total born performance of gilts bred at 0HNS (mean 93.9) and 1HNS (mean 95.7). There was also a significant difference (p<0.001) of total born piglets in parity 1, 5 and 6 in the 2 groups. There was an observed increased parity total born and lifetime total born when first time insemination of gilts was delayed to second estrus. The findings in this study favor the 1HNS breeding with an overall increased lifetime total born. Gilts inseminated at 1HNS produce 1.57 more pigs for lifetime as compared with those inseminated at 0HNS when observation is made up to P6. Producers in piglet producing herds could re examine their decisions for increased productivity by promoting many gilts into 1HNS but still maintaining the balance between breed targets and production schedules to remain competitive and profitable in the current global swine industry.