1. Predicting Boar Sperm Survival during Liquid Storage Using Vibrational Spectroscopic Techniques.
- Author
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Kameni, Serge L., Semon, Bryan, Chen, Li-Dunn, Dlamini, Notsile H., Ariunbold, Gombojav O., Vance-Kouba, Carrie K., and Feugang, Jean M.
- Subjects
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SEMEN analysis , *OXIDANT status , *CERVIX uteri , *NEAR infrared spectroscopy , *REACTIVE oxygen species , *SEMEN - Abstract
Simple Summary: Artificial insemination (AI) is a reproductive technique routinely used in livestock to deliver sperm directly to the cervix or uterus to achieve pregnancy. In swine, AI is performed with chill-stored sperm displaying minimum criteria evaluated using traditional procedures; however, variegated fertility appeals for additional tools for sperm evaluation. To enhance sperm evaluation, we assess the potential of near-infrared (NIR) and Raman spectroscopy in addition to traditional techniques to monitor boar sperm quality during 10-day chill-storage. Sperm samples showed differential responses to storage, with sperm quality nearly maintained in some samples, whereas it sharply deteriorated in others. Better than NIR, Raman spectral profiles obtained from freshly extended samples efficiently predict sperm survival to storage, making the technique a promising tool for in-depth assessment of sperm samples. Artificial insemination (AI) plays a critical role in livestock reproduction, with semen quality being essential. In swine, AI primarily uses cool-stored semen adhering to industry standards assessed through routine analysis, yet fertility inconsistencies highlight the need for enhanced semen evaluation. Over 10-day storage at 17 °C, boar semen samples were analyzed for motility, morphology, sperm membrane integrity, apoptosis, and oxidative stress indicators. Additionally, machine learning tools were employed to explore the potential of Raman and near-infrared (NIR) spectroscopy in enhancing semen sample evaluation. Sperm motility and morphology gradually decreased during storage, with distinct groups categorized as "Good" or "Poor" survival semen according to motility on Day 7 of storage. Initially similar on Day 0 of semen collection, "Poor" samples revealed significantly lower total motility (21.69 ± 4.64% vs. 80.19 ± 1.42%), progressive motility (4.74 ± 1.71% vs. 39.73 ± 2.57%), and normal morphology (66.43 ± 2.60% vs. 87.91 ± 1.92%) than their "Good" counterparts by Day 7, using a computer-assisted sperm analyzer. Furthermore, "Poor" samples had higher levels of apoptotic cells, membrane damage, and intracellular reactive oxygen species on Day 0. Conversely, "Good" samples maintained higher total antioxidant capacity. Raman spectroscopy outperformed NIR, providing distinctive spectral profiles aligned with semen biochemical changes and enabling the prediction of semen survival during storage. Overall, the spectral profiles coupled with machine learning tools might assist in enhancing semen evaluation and prognosis. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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