For over 30 years, CASA-Mot technology has been used for kinematic analysis of sperm motility in different mammalian species, but insufficient attention has been paid to the technical limitations of commercial computer-aided sperm analysis (CASA) systems. Counting chamber type and frame rate are two of the most important aspects to be taken into account. Counting chambers can be disposable or reusable, with different depths. In human semen analysis, reusable chambers with a depth of 10µm are the most frequently used, whereas for most farm animal species it is more common to use disposable chambers with a depth of 20µm . The frame rate was previously limited by the hardware, although changes in the number of images collected could lead to significant variations in some kinematic parameters, mainly in curvilinear velocity (VCL). A frame rate of 60 frames s-1 is widely considered to be the minimum necessary for satisfactory results. However, the frame rate is species specific and must be defined in each experimental condition. In conclusion, we show that the optimal combination of frame rate and counting chamber type and depth should be defined for each species and experimental condition in order to obtain reliable results.

Sperm quality is evaluated for the calculation of sperm dosage in artificial reproductive programs. The most common parameter used is motility, but morphology has a higher potential as a predictor of genetic quality. Morphometry calculations from CASA-Morph technology improve morphological evaluation and allow mathematical approaches to the problem. Semen from 28 Holstein bulls was collected by artificial vagina, and several ejaculates were studied. After general evaluation, samples were diluted, packaged in 0.25 ml straws, and stored in liquid nitrogen. Two straws per sample were thawed, and slides were processed and stained with Diff-Quik. Samples were analyzed by a CASA-Morph system for eight morphometric parameters. In addition to the “classical” statistical approach, based on variance analysis (revealing differences between animals, ejaculates, and straws), principal component (PC) analysis showed that the variables were grouped into PC1, related to size, and PC2 to shape. Subpopulation structure analysis showed four groups, namely, big, small, short, and narrow from their dominant characteristics, representing 31.0%, 27.3%, 24.1%, and 17.7% of the total population, respectively. The distributions varied between animals and ejaculates, but between straws, there were no differences in only four animals. This modern approach of considering an ejaculate sperm population as divided into subpopulations reflecting quantifiable parameters generated by CASA-Morph systems technology opens a new view on sperm function. This is the first study applying this approach to evaluate different ejaculates and straws from the same individual. More work must be done to improve seminal dose calculations in assisted reproductive programs.

Motility is the most widely used indicator of sperm quality. Computer-Assisted Semen Analysis (CASA) allows the objective evaluation of sperm motility parameters. CASA technology is a common tool to predict semen doses in farm animal reproduction. The kinds of video cameras used until now for image acquisition have presented limited frame rates (FR), which have a negative influence on the quality of the obtained data. The aim of the present work was to define the optimal frame rate for a correct evaluation of boar sperm motility and its subpopulation structure. Eighteen ejaculates from nine mature boars of the Pietrain breed were used. Using the ISAS v1 CASA-Mot system, with a video camera working up to 200 Hz, six FRs (25, 50, 75, 100, 150 and 200 fps) were compared. ISAS D4C20 counting chambers, warmed to 37°C, were used. FR affected all the kinematic parameters, with curvilinear velocity (VCL) and BCF the most sensitive ones. All the parameters showed differences among animals. Non-linear correlation showed the asymptotic level for VCL at 212 fps, being the highest FR for all the parameters. For future studies based just on progressive motility, almost 100 fps FR for 0.5 s must be used, while when kinematics must be considered, almost 212 fps for one-second should be analysed. Three principal components were obtained (velocity, progressivity and oscillation), being similar at 50 and 200 fps. Cells were grouped in four subpopulations but with different kinematic and cellular distribution at both FRs.