• Journal of Animal Science and Technology
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• v.54 no.5
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• pp.337-340
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• 2012

The genetic connectedness between herds is an essential requirement to make robust across-herd estimation of the breeding values of the animals. In this study, genetic connectedness between herds was evaluated by a connectedness rating method. A total of 24,971 records of days to 90 kg (D90KG) of the pigs on performance testing programs collected from six herds (labeled from 'A' to 'F') of Duroc breed along with pedigree information comprising 456,697 families were used. Results showed that a total of eight boars were used for semen exchange programs among participant farms. Herds 'A' through 'E' were found strongly connected among them. But 'F' herd was genetically connected strongly only with 'A' herd. The highest average connectedness rating was 91.7% between 'A' herd and 'C' herd. The lowest average connectedness rating was 65.1% between 'D' and 'F'. The concept of a single genetic group comprising six Duroc herds studied is meaningful due to high connectedness rates among them. Therefore, with this high genetic ties between participant Duroc farms, the more accurate genetic evaluation would be possible.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.2
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• pp.153-158
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• 2004

Data containing 14,188 lactation and reproductive records of Korean Holstein cows at first parity distributed across 3,734 herd-year-season groups were analyzed to get genetic (co)variance estimates for milk yield, fat yield, calving ease, and days open. Milk and Fat yields were adjusted to 305 d. Heritabilities and genetic correlations were estimated in two different animal models on which were included direct genetic effects (Model 1) and direct+maternal genetic effects (Model 2) using REML algorithms. Milk and fat yields were affected by age at first calving as linear and quadratic. Heritability estimates of direct effects were 0.25 for milk yield, 0.17 for fat yield, 0.03 for calving ease and 0.03 for days open in Model 2. These estimates for maternal effects were 0.05, 0.08, 0.04 and less than 0.01 for each corresponding trait. Milk productions at first lactation were to show genetically favorable correlation with calving ease and days open for direct genetic effects (-0.24 - -0.11). Moreover, calving ease was correlated with days open of 0.30 for direct genetic effects. Correlations between direct and maternal effects for each trait were negatively correlated (-0.63 - -0.32). This study suggested that maternal additive genetic variance would be not ignorable for genetic evaluation of milk production as well as reproductive traits such as calving ease and days open at first parity. Furthermore, difficult calving would genetically influence the next conception.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.9
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• pp.1387-1399
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• 2020

Objective: The objective of this study was to estimate the genetic parameters and trends for milk, fat, and protein yields in the first three lactations of Thai dairy cattle using a 3-trait,-3-lactation random regression test-day model. Methods: Data included 168,996, 63,388, and 27,145 test-day records from the first, second, and third lactations, respectively. Records were from 19,068 cows calving from 1993 to 2013 in 124 herds. (Co) variance components were estimated by Bayesian methods. Gibbs sampling was used to obtain posterior distributions. The model included herd-year-month of testing, breed group-season of calving-month in tested milk group, linear and quadratic age at calving as fixed effects, and random regression coefficients for additive genetic and permanent environmental effects, which were defined as modified constant, linear, quadratic, cubic and quartic Legendre coefficients. Results: Average daily heritabilities ranged from 0.36 to 0.48 for milk, 0.33 to 0.44 for fat and 0.37 to 0.48 for protein yields; they were higher in the third lactation for all traits. Heritabilities of test-day milk and protein yields for selected days in milk were higher in the middle than at the beginning or end of lactation, whereas those for test-day fat yields were high at the beginning and end of lactation. Genetics correlations (305-d yield) among production yields within lactations (0.44 to 0.69) were higher than those across lactations (0.36 to 0.68). The largest genetic correlation was observed between the first and second lactation. The genetic trends of 305-d milk, fat and protein yields were 230 to 250, 25 to 29, and 30 to 35 kg per year, respectively. Conclusion: A random regression model seems to be a flexible and reliable procedure for the genetic evaluation of production yields. It can be used to perform breeding value estimation for national genetic evaluation in the Thai dairy cattle population.

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.366-373
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• 2024

This study aims to estimate the connectedness rating (CR) of Korean swine breeding herds. Using 104,380 performance and 83,200 reproduction records from three swine breeds (Yorkshire, Landrace and Duroc), the CR was estimated for two traits: average daily gain (ADG) and number born alive (NBA) in eight breeding herds in the Republic of Korea (hereafter, Korea). The average CR for ADG in the Yorkshire breed ranges from 1.32% to 28.5% depending on the farm. The average CR for NBA in the Yorkshire herd ranges from 0% to 12.79%. A total of 60% of Yorkshire and Duroc herds satisfied the preconditions suggested for genetic evaluation among the herds. The precondition for the genetic evaluation of CR for ADG, as a productive trait, was higher than 3% and that of NBA, as a reproductive trait, was higher than 1.5%. The ADG in the Yorkshire herds showed the highest average CR. However, the average CR of ADG in the Landrace herds was lower than the criterion of the precondition. The prediction error variance of the difference (PEVD) was employed to assess the validation of the CR, as PEVDs exhibit fluctuations that are coupled with the CR across the herds. A certain degree of connectedness is essential to estimate breeding value comparisons between pig herds. This study suggests that it is possible to evaluate the genetic performance together for ADG and NBA in the Yorkshire herds since the preconditions were satisfied for these four herds. It is also possible to perform a joint genetic analysis of the ADG records of all Duroc herds since the preconditions were also satisfied. This study provides new insight into understanding the genetic connectedness of Korean pig breeding herds. CR could be utilized to accelerate the genetic progress of Korean pig breeding herds.