ABSTRACT
Reproductive traits are important traits that directly affect a farmer's income and are difficult to improve upon using traditional genetic methods. Therefore, there is a need to consider new options for increasing the accuracy of the genetic selection of dairy cows. The objective of this study was to compare the genetic methods of the traditional BLUP and ssGBLUP techniques in terms of the estimated genetic parameters and accuracy of the estimated breeding values. The data comprised 101,331 services per conception (NSPC) records from 54,027 Thai-Holstein crossbred cows, 109,233 pedigree data, and 770 genotyped animals. A Bayesian analysis via threshold Gibbs sampling was used to analyze the estimated variance components and genetic parameters. The results showed that the means of the NSPC data were 2.21, 2.31, and 2.42 for less than 87.5% for Holstein genetics (breed group; BG1), 87.5 to 93.6% for Holstein genetics (BG2), and greater than 93.7% for Holstein genetics (BG3), respectively. The estimated heritability values were 0.038 and 0.051, and the repeatability values were 0.149 and 0.157 for the traditional BLUP and ssGBLUP methods, respectively. The accuracy of the estimated breeding values from the ssGBLUP method was higher than that from the traditional BLUP method, ranging from 6.05 to 17.69%, depending on the dataset, especially in the top 20% of the bull dataset had the highest values. In conclusion, the ssGBLUP method could improve the heritability value and accuracy of the breeding values compared with the traditional BLUP method. Therefore, switching from traditional methods to the ssGBLUP method for the Thai dairy cattle breeding program is a viable option.
ABSTRACT
The purpose of this study was to determine the combining abilities and heterosis for the growth performance and carcass characteristics in crosses between Hmong black-bone (HB), Chinese black-bone (CB), and Thai native (TN) chickens using a mating system diallel crossing. Nine crossbred chickens including HB × HB, CB × CB, TN × TN, HB × TN, TN × HB, CB × HB, HB × CB, TN × CB, and CB × TN, were tested. The total data were 699 recorded at the beginning of the experiment to 595 recorded in weeks 14 of age. Body weight (BW), average daily gain (ADG), feed conversion ratio (FCR), and survival rate (SUR) were recorded. Heterosis and combining ability regarding general combining ability (GCA), specific combining ability (SCA), and reciprocal combining ability (RCA) were estimated. The study found that CB had the greatest BW and ADG at all weeks (p < 0.05) except for hatch, while those of HB were the lowest. The highest GCA was found in CB; meanwhile, GCA was significantly negative in HB of all ages. Crossing between TN × CB had the greatest BW from 8 weeks of age, which was related to positive SCA and RCA values. However, the RCA value of TN × CB was lower than the SCA value of CB × TN. The yield percentages of the carcass in CB (87.00%) were higher than those in TN (85.05%) and HB (82.91%) (p < 0.05). The highest breast and thigh meat lightness (L*) values were obtained in TN (p < 0.05), while those of CB and HB were not different (p > 0.05). In the crossbreed, the yield percentage of the carcass was highest in TN × CB (89.65%) and CB × TN (88.55%) (p > 0.05) and was lowest in TN × HB (71.91%) (p < 0.05). The meat and skin color of the breast and thigh parts in the crossbreed had the lowest lightness in HB × CB (27.91 to 38.23) (p < 0.05), while those of TN × CB and CB × TN were insignificant (p > 0.05). In conclusion, crossing between the TN sires and CB dams has the preferable potential to develop crossbred Thai native chickens for commercial use based on their high growth performance.
ABSTRACT
Heat stress is becoming a significant problem in dairy farming, especially in tropical countries, making accurate genetic selection for heat tolerance a priority. This study investigated the effect of heat stress manifestation on genetics for milk yield, milk quality, and dairy health traits with and without genomic information using single-step genomic best linear unbiased prediction (ssGBLUP) and BLUP in Thai-Holstein crossbred cows. The dataset contained 104,150 test-day records from the first lactation of 15,380 Thai-Holstein crossbred cows. A multiple-trait random regression test-day model on a temperature-humidity index (THI) function was used to estimate the genetic parameters and genetic values. Heat stress started at a THI of 76, and the heritability estimates ranged from moderate to low. The genetic correlation between those traits and heat stress in both BLUP methods was negative. The accuracy of genomic predictions in the ssGBLUP method was higher than the BLUP method. In conclusion, heat stress negatively impacted milk production, increased the somatic cell score, and disrupted the energy balance. Therefore, in dairy cattle genetic improvement programs, heat tolerance is an important trait. The new genetic evaluation method (ssGBLUP) should replace the traditional method (BLUP) for more accurate genetic selection.
ABSTRACT
BACKGROUND AND AIM: Genomic selection improves accuracy and decreases the generation interval, increasing the selection response. This study was conducted to assess the benefits of using single-step genomic best linear unbiased prediction (ssGBLUP) for genomic evaluations of milk yield and heat tolerance in Thai-Holstein cows and to test the value of old phenotypic data to maintain the accuracy of predictions. MATERIALS AND METHODS: The dataset included 104,150 milk yield records collected from 1999 to 2018 from 15,380 cows. The pedigree contained 33,799 animals born between 1944 and 2016, of which 882 were genotyped. Analyses were performed with and without genomic information using ssGBLUP and BLUP, respectively. Statistics for bias, dispersion, the ratio of accuracies, and the accuracy of estimated breeding values were calculated using the linear regression (LR) method. A partial dataset excluded the phenotypes of the last generation, and 66 bulls were identified as validation individuals. RESULTS: Bias was considerable for BLUP (0.44) but negligible (-0.04) for ssGBLUP; dispersion was similar for both techniques (0.84 vs. 1.06 for BLUP and ssGBLUP, respectively). The ratio of accuracies was 0.33 for BLUP and 0.97 for ssGBLUP, indicating more stable predictions for ssGBLUP. The accuracy of predictions was 0.18 for BLUP and 0.36 for ssGBLUP. Excluding the first 10 years of phenotypic data (i.e., 1999-2008) decreased the accuracy to 0.09 for BLUP and 0.32 for ssGBLUP. Genomic information doubled the accuracy and increased the persistence of genomic estimated breeding values when old phenotypes were removed. CONCLUSION: The LR method is useful for estimating accuracies and bias in complex models. When the population size is small, old data are useful, and even a small amount of genomic information can substantially improve the accuracy. The effect of heat stress on first parity milk yield is small.
