Abstract
BACKGROUND AND AIM: Artificial insemination (AI) is a key biotechnology for improving dairy cattle populations, offering genetic enhancement and increased milk production. The advent of sexed semen allows for the preferential selection of female offspring which is beneficial for dairy operations. This study aimed to evaluate and optimize a spermatozoa sexing method using Percoll density gradient centrifugation (PDGC) and analyze kinetic parameters of the separated spermatozoa using computer-assisted sperm analysis. MATERIALS AND METHODS: The study was conducted on two Holstein-Friesian bulls at the Singosari Artificial Insemination Center and Universitas Brawijaya, Indonesia. Semen samples underwent PDGC sexing at two density gradients, (T1) 20%-65% and (T2) 20%-60%. Kinetic parameters, including motility, velocity, and movement patterns, were assessed pre- and post-sexing. Statistical analyses were performed using a one-way analysis of variance and Duncan's test to determine significant differences. RESULTS: Fresh semen (control) exhibited significantly higher motility (88.45%) compared to T1 (70.94%) and T2 (72.22%), with p < 0.01. Velocity parameters, including curvilinear velocity, were also significantly reduced post-sexing. However, motility levels in sexed samples still exceeded the 40% AI threshold. The 20%-65% gradient demonstrated better performance in maintaining sperm quality compared to the 20%-60% gradient. CONCLUSION: Although sexing reduced motility and kinetic parameters, both gradients yielded semen suitable for AI applications. The 20%-65% gradient showed superior results, indicating its potential for optimizing the sexing process. Further research is recommended to refine the technique and improve the viability of sexed sperm.