Heat stress is a major environmental threat to poultry production systems, especially in tropical areas. The effects of heat stress have been discovered in several areas, including reduced growth rate, reduced egg production, low feed efficiency, impaired immunological responses, changes in intestinal microflora, metabolic changes, and deterioration of meat quality. Although several methods have been used to address the heat stress problem, it persists. The answer to this problem can be remedied sustainably if genetic improvement approaches are available. Therefore, the purpose of this review article was to present the application of different approaches to genetic improvement in poultry in the hope that users will find suitable solutions for their poultry population and be able to plan future poultry breeding programs.

Temperature and relative humidity indices (THIs) are widely used to study the effects of heat stress on reduced poultry production traits. However, a suitable THI for reproductive traits has not yet been established. This study aimed to develop a novel THI to predict semen traits in native roosters using regression analysis. A total of 242 Thai native grandparent roosters (Pradu Hang Dum) aged 30 weeks were used. Semen was collected weekly for 1 year to assess parameters, including semen volume, mass motility, and sperm concentration. To simplify the evaluation of semen traits, a composite measure termed the "semen index" was developed. This index was calculated by summing the Z-scores of the volume, mass, and concentration of each sample. Simple regression analysis was performed using several statistical criteria to identify the optimal THI function for the dataset and determine the THI threshold that influences changes in semen characteristics. The results indicated that the newly developed THI function (THI_F) offered a better fit for predicting the onset of heat stress than the original THI1, particularly at a THI threshold of 76. The improved fit of THI_F, as demonstrated by the lower values of the sum of squared errors, Akaike information criterion, and Bayesian information criterion, suggests that it provides a more reliable indication of thermal stress affecting reproductive performance. Therefore, the newly developed THI function is a more precise tool for evaluating the effects of thermal stress. This improved index has important applications in genetic selection and breeding strategies aimed at enhancing heat tolerance and reproductive performance in livestock, particularly for improving the resilience of poultry to heat stress, which is crucial for sustaining productivity under challenging environmental conditions.

The aim of this study was to analyze suitable genetic models and selection indices to estimate the genetic parameters and breeding values of native Thai roosters. A total of 3475 records of seven semen traits (mass movement, semen pH, semen color, volume, sperm viability, sperm abnormalities, and sperm concentration) from 242 Thai native grandparent roosters were analyzed. Multiple-trait random regression test-day models with five covariance functions were used to analyze the variance components, genetic parameters, and breeding values. The selection index (SI) was calculated to determine the optimal genetic value for different selection percentages. The results showed that a multiple-trait random regression test-day model with a second-order Legendre polynomial function was the most appropriate genetic model for this population. The estimated heritability values were low to moderate, ranging from 0.110 to 0.112 (mass movement), 0.040 to 0.051 (semen pH), 0.092 to 0.097 (semen color), 0.220 to 0.225 (semen volume), 0.067 to 0.083 (sperm viability), 0.086 to 0.099 (sperm abnormalities), and 0.134 to 0.138 (sperm concentration). The repeatability values exceeded the heritability values and were within the range of 0.133 to 0.688. The genetic correlations among semen traits ranged from −0.332 to 0.677, and phenotypic correlations ranged from −0.260 to 0.460. When considering heritability and genetic correlation values, semen volume, sperm concentration, and mass movement were the top three priority semen traits calculated as selection indices. Finally, the top 10% of the selection index was recommended for creating the next generation. Our findings provide useful information on genetic parameters and an appropriate selection index of semen traits for selecting the genetics of individual Thai native grandparent roosters. The heritability estimates for semen traits reported here suggest an adequate response to selection through a genetic evaluation approach. Our results indicate that it is possible to select grandparent roosters with better reproductive performance.

Semen quality is a major determinant of reproductive efficiency in poultry production systems. In Thai native chickens, the relatively low male-to-female mating ratio increases the reproductive importance of individual sires, making semen quality traits critical for maintaining flock fertility. Thai native chickens represent an important genetic resource characterized by high adaptability to tropical environments and unique genetic diversity, yet remain relatively under-studied compared with commercial lines. Therefore, accurate estimation of genetic parameters and a clear understanding of the genetic architecture underlying semen traits are required to support effective breeding programs. However, despite their importance, semen quality traits in Thai native chickens remain poorly characterized at the genomic level, and the effectiveness of genomic evaluation approaches for improving these traits has not been fully explored. This study estimated genetic parameters, characterized the genetic architecture of semen traits, and evaluated the impact of genomic information on prediction accuracy in Thai native chickens. We evaluated the predictive performance of sperm quality traits using three genetic evaluation models: pedigree-based best linear unbiased prediction (PBLUP), single-step genomic BLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Estimates of heritability for mass movement, semen volume, and sperm concentration were low (0.149, 0.165, and 0.060, respectively), indicating limited additive genetic variation for these traits. Incorporation of genomic information improved prediction accuracy, with ssGBLUP and WssGBLUP increasing accuracy by 5.88% and 7.49%, respectively, compared with PBLUP. A strong positive genetic correlation (0.977) was observed between mass movement and sperm concentration, suggesting that selection for improved mass movement is likely to result in a favorable correlated genetic response in sperm concentration. In addition, WssGWAS identified genomic regions on chromosomes 6, 11, 19, 21, and 22 that harbored 14 candidate genes associated with sperm structure and metabolic processes. These findings suggest that the identified genomic regions may influence semen quality through biological pathways related to sperm membrane integrity, energy metabolism, and cellular regulation, which are essential for maintaining sperm motility and function. Our results demonstrate the utility of genomic information, particularly the WssGBLUP approach, for improving semen quality traits in Thai native chickens. These findings provide biologically relevant insights to support the development of sustainable genetic improvement programs.

Native chickens are important both economically and for the preservation of genetic diversity, especially for optimizing the reproductive performance of male chickens, which plays an important role in genetic propagation. However, hot and humid weather affects the quality of semen and the breeding ability of male chickens. One method used to solve this problem is genetic selection using genomic technology, which improves accuracy and shortens the breed selection time. Therefore, we collected and analyzed data from relevant research to review the genetic improvement approach for male chickens using genomic technology. We compared popular genomic selection models, such as GBLUP, ssGBLUP, Bayesian approaches, RR-GBLUP, WGBLUP, and MTGBLUP, as well as genome-wide association studies (GWASs), to identify genes associated with semen quality and heat tolerance. The results of this analysis suggested that the use of genomic data can enhance genetic selection and enable breeding to occur more quickly and accurately. We addressed the trends and scientific developments in male chicken genetic selection, together with the benefits and constraints of each method. This will help breeders and researchers to create the most successful genetic selection plans for the next generation of chickens.

Improving reproductive traits, particularly semen quality and quantity, is crucial for optimizing poultry production and addressing the current limitations in native chicken reproduction. The aim of this study was to develop a genetic model to estimate genetic parameters guiding the selection of individual Thai native roosters. Using data collected from 3475 records of 242 Thai native grandparent roosters aged 1–4 years, we evaluated semen traits (mass movement, semen volume, and sperm concentration) over 54 weeks. A random regression test–day model incorporating five covariance functions, including a linear spline function with four, five, six, and eight knots (SP4, SP5, SP6, and SP8) and second-order Legendre polynomial function (LG2), was used to estimate genetic parameters. The results showed that the SP8 model consistently outperformed the other models across all traits, with the lowest mean square error, highest coefficient of determination, and superior predictive ability. Heritability estimates for mass movement, semen volume, and sperm concentration ranged from 0.10 to 0.25, 0.22 to 0.25, and 0.11 to 0.24, respectively, indicating moderate genetic influence on these traits. Genetic correlations between semen volume and sperm concentration were highest in the SP8 model, highlighting a strong genetic association between these traits. The SP8 model also revealed a high genetic correlation between mass movement and semen volume, supporting the potential for selecting mass movement as a predictor of semen volume. In conclusion, this study highlights the effectiveness of random regression models with linear spline functions to evaluate the genetic parameters of semen traits in native Thai roosters. The SP8 model is a robust tool for breeders to enhance the reproductive performance of native Thai chickens, contributing to sustainable poultry production systems.