Comparative studies of semen quality traits and sperm kinematic parameters in relation to fertility rate between 2 genetic groups of breed lines

Semen quality is important for roosters' fertility. The correlations between semen quality traits and fertility has less been analyzed, impeding the selection of effective parameters for roosters selection. This research aimed to investigate the variation in semen quality traits in relation to fertilization capacity between 2 chicken breeds. A total of 156 Rhode Island Red (n = 78) and White Leghorn (n = 78) roosters of 53 wk were selected for semen quality estimation including semen volume, pH, sperm concentration, motility, viability, abnormal sperm percentage, and sperm kinematic parameters. Individual fertility was measured by artificial insemination using each 30 birds from 2 breeds. Significant variations were observed between breeds in semen volume, pH, sperm motility (MOT), viability, and abnormal sperm percentage (P < 0.05). The volume, MOT, and viability in Rhode Island Red were higher than those of White Leghorn roosters (P < 0.001). In addition, sperm kinematic parameters such as curvilinear velocity (VCL), straight line velocity (VSL), amplitude lateral head displacement (ALH), and average path velocity (VAP) in Rhode Island Red were higher than those of White Leghorn (P < 0.001). Fertility rate was positively correlated with MOT (r = 0.57), concentration (r = 0.43), viability (r = 0.39), VSL (r = 0.36), ALH (r = 0.43), and ALH (r = 0.38) for Rhode Island Red roosters (P < 0.05). Fertility rate of White Leghorn roosters was positively correlated with MOT (r = 0.71), concentration (r = 0.39), VCL (r = 0.52), ALH (r = 0.50), and VAP (r = 0.39) (P < 0.05). Principal component analysis of sperm kinematic descriptors revealed 2 principal components explaining more than 65% of total variance. In addition, for both genetic lines, the whole population was divided into 3 independent clusters. These results indicated that selection of roosters based on semen quality traits for may improve the fertility, and multivariate analysis may help to precise selection by comprehensive usage of different measures of sperm quality.