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.

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.

The objectives of this study were to investigate changes in genetic parameters for milk yield (MY) and heat tolerance of the crossbred Thai Holstein Friesian population under different heat stress levels over time, and to investigate the threshold point of heat stress manifestation on milk production. Genetic parameters were estimated using single-step genomic REML (ssGREML) and traditional REML models. Data included 58,965 test-day MY records from 1999 to 2008 (old data) and 105,485 test-day MY records from 2009 to 2018 (recent data) from the first parity of 24,520 cows. The pedigree included 55,168 animals, of which 882 animals had genotypes. Variance components were estimated with the REMLF90 program using a repeatability model with random regressions on a function of temperature-humidity index (THI) for additive genetic and permanent environmental effects. Fixed effects included farm-calving season combination, breed group months in milk combination, and age at first calving. Random effects included additive genetic (intercept and slope) effects, permanent environmental (intercept and slope) effects, and herd-month-year of test. The phenotypic mean for MY was 13.33 +/- 4.39 kg/d in the old data, and 14.48 +/- 4.40 kg/d in the recent data. Estimates over different THI levels for the intercept additive genetic variance using old data ranged from 2.61 to 2.77 and from 5.02 to 5.38 using recent data with the REML method. In ssGREML analyses (performed with recent data only) the estimates for the intercept additive genetic variance ranged from 4.71 to 5.05. Estimates for the slope additive genetic variance were close to zero in all cases, with the largest values (0.024-0.030) at the most extreme THI value (80). Using REML, the covariance between the intercept and the slope additive genetic effects (THI from 72 to 80) ranged from -0.001 to 0.019 with old data and from 0.027 to 0.060 with recent data. The same covariance ranged from 0.026 to 0.057 in ssGREML analyses. The covariance between the intercept and the slope permanent environmental effects ranged from -0.42 to -0.67 for all data and THI levels. Across THI levels, the genetic correlation between MY and heat tolerance varied from -0.06 to 0.13 with old data, from 0.16 to 0.30 with recent data in REML analyses, and from 0.15 to 0.30 in ssGREML analyses, suggesting that in the current population the top animals for MY are more resistant to heat stress. This was expected, because of the introduction of Bos indicus genes in the last years. Heritability estimates for MY ranged from 0.19 to 0.21 (old data) and from 0.33 to 0.40 (recent data) for REML analyses. Heritability estimates for MY using ssGREML ranged from 0.31 to 0.38. A decline in MY was found when the animals' breed composition had more than 97.3% of Holstein genetics, and it was greatest at THI 80. The heritability and genetic correlations observed in this study show that selection for MY is possible without a negative correlated response for heat tolerance. Although the inclusion of genomic information is expected to increase the accuracy of selection, more genotypes must be collected for successful application. Future research should address other production and fitness traits within the Thai Holstein population.

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.

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.

Improving egg production under heat stress remains a major challenge in tropical poultry breeding. This study demonstrates that clutch length and hen-day egg production are robust indicators of genetic variation in heat tolerance and directly applicable to climate-resilient breeding programs in Thai native chickens. Records from 2400 Pradu Hang Dum hens across five generations were analyzed using a reaction-norm repeatability model with the temperature–humidity index (THI) as an environmental covariate. A THI threshold of 74 was identified, beyond which heat stress altered the genetic expression of both traits. Heritability estimates declined with an increasing THI, from 0.49 to 0.32 for clutch length and from 0.37 to 0.26 for hen-day egg production, indicating reduced additive genetic control under heat stress. Genetic correlations between baseline performance and heat-stress sensitivity were moderately to strongly negative (−0.46 to −0.54), revealing antagonism between productivity under thermoneutral conditions and heat tolerance. Reaction-norm breeding values showed substantial genotype-by-environment interactions, highlighting heterogeneity in heat-stress responses among genotypes. Despite thermal challenges, positive genetic trends were observed, with an average genetic trend of 1.34 eggs per generation for clutch length and 8.8 percent per generation for hen-day egg production. These results demonstrate that genetic improvement can be sustained under heat stress and support the integration of THI-based reaction-norm evaluations to identify genotypes combining reproductive efficiency with enhanced heat tolerance for climate-resilient breeding programs.