Estimation of additive genetic, dominance, and mate sire variances for fertility traits in Thai native (Pradu Hang Dam) chickens.

The objective of this study was to compare the appropriate models used to estimate the value of genetic parameters in fertility traits: fertility (FER), hatchability of fertile eggs (HOF), and hatchability of eggs set (HOS) in Thai native (Pradu Hang Dam) chickens. Data were collected for each fertility trait from 3435 test-week records from 715 hens, 158 mate sires, and 972 pedigree animals. Three random regression models were analyzed: model 1 (M1: A + PE) was adjusted by using additive genetic and permanent environmental effects. Model 2 (M2: A + PE + D) was adjusted by using the dominance effect. Finally, model 3 (M3: A + MS + PE + D) was adjusted by using the mate sire effect. The results found the low heritability of FER (M1 to M3), HOF (M1 to M3), and HOS (M1 to M3) ranged from 0.031-0.040, 0.037-0.066, and 0.040-0.059, respectively. Adjustment for the dominance and mate sire effects in M3 reduced the upward bias in heritability and improved the accuracy of variance component estimates compared to M1 and M2. In conclusion, the genetic evaluation for FER, HOF, and HOS can include the dominance and MS effects to increase the accuracy of evaluation of breeding values and plan for mate selection in breeding programs.

Estimation of genetic parameters and trends for production traits of dairy cattle in Thailand using a multiple-trait multiple-lactation test day model.

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.

Genetic associations between milk fat-to-protein ratio, milk production and fertility in the first two lactations of Thai Holsteins dairy cattle.

The aims of this study were to estimate, simultaneously, the genetic parameters of test-day milk fat-to-protein ratio (FPR), test-day milk yield (MY), and days-open (DO) in the first two lactations of Thai Holsteins. A total of 76 194 test-day production records collected from 8874 cows with 8674 DO records between 2001 and 2011 from different lactations were treated as separated traits. The estimates of heritability for test-day FPR in the first lactation showed an increasing trend, whereas the estimates in the second lactation showed a U-shape trend. Genetic correlations for FPR-DO and MY-DO showed a decreasing trend along days in milk (DIM) in both lactations, whereas genetic correlations for FPR-MY increased along DIM in the first lactation but decreased in the second lactation. Genetic correlations of FPR between consecutive DIM were moderate to high, which showed the effectiveness of simultaneous analyses. Selection of FPR in the early stage has no adverse effect on MY and DO for the first lactation but has a negative effect on MY and positive effect on DO for the second lactation. This study showed that genetic improvement of the energy balance using FPR, MY and DO with multi-trait test day model could be applied in a Thailand dairy cattle breeding program.