Regression analyses and motile sperm subpopulation structure study as improving tools in boar semen quality analysis.

A precise estimation of the fertilizing ability of a boar ejaculate would be very useful to improve pig assisted reproduction results. For this purpose, we tested the mathematical combination of several parameters of the boar semen quality analysis, including the computer-assisted semen motility analysis (CASA), as a predictive fertility tool. The utilized mathematical relations among parameters were logistic and linear regressions. Two mathematical models obtained by logistic regression involving Osmotic Resistance Test (ORT Test), Hyperosmotic Resistance Test (HRT Test) and viability of fresh samples, showed a significant (P<0.05) correlation between semen characteristics and conception rate. However, none of the obtained models produced a significant correlation model between semen characteristics and prolificacy. The CASA analyses show that three separate subpopulations of spermatozoa with different motility characteristics coexist in boar ejaculates. There were significant (P<0.001) differences in the distribution of these subpopulations among boars, but no clear relationship between motile subpopulation structure and fertility was obtained. Our results support the belief that the predictive use of the results obtained in a standard boar semen quality analysis can reasonably be achieved by applying logistic correlation analyses among several function parameters of boar semen quality analysis and in vivo conception rates obtained after artificial insemination (AI).