chapter 3 - RiuNet
chapter 3 - RiuNet
chapter 3 - RiuNet
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GENERAL INTRODUCTION<br />
in fish (Kime et al., 2001; Fauvel et al., 2010; Boryspholets et al., 2013).<br />
However, the most used technique to assess sperm motion has been<br />
subjective evaluation, and some problems have emerged from this method.<br />
In this respect, the subjective assessment depends on an experienced<br />
observer, and several aspects such as sperm density, sperm velocity, drift,<br />
etc. can cause over- or underestimation readings. Therefore, the low<br />
reproducibility of this motility analysis through subjective evaluation, which<br />
can result in variations of 30 to 60% from the same sample, often makes it<br />
difficult to interpret and compare the results between labs (Verstegen et<br />
al., 2002; Rosenthal et al., 2010). In this sense, the gradual appearance of<br />
computerized techniques has provided us with an objective and rapid<br />
method for obtaining a correct and accurate evaluation of sperm motion<br />
features (Rurangwa et al., 2004, Cabrita et al., 2011).<br />
3.2 New tools to determine sperm quality<br />
The appearance of Computer Assisted Sperm Analysis (CASA) systems has<br />
made it possible to estimate a higher number of sperm motion parameters<br />
using an objective, sensitive and accurate technique. These systems are the<br />
evolution of multiple photomicrography exposure and video-micrography<br />
techniques for spermatozoa track, using a computer equipped with imaging<br />
software (Rurangwa et al., 2004). This technique was first introduced in the<br />
80´s in mammalian sperm and only in the last few years have modern CASA<br />
systems been adapted for fish spermatozoa studies (Van Look et al., 2000;<br />
Wilson-Leedy and Ingermann, 2007). The differences in the biology of fish<br />
and mammalian spermatozoa may explain the delay in the release of<br />
adequate tools for the measurement of sperm motility in fish. To date,<br />
these systems have been used and validated in a wide range of animal<br />
groups such as marine invertebrates (Gallego et al., 2013), birds (Kleven et<br />
al., 2009), marine mammals (Montano et al., 2012), reptiles (Tourmente et<br />
al., 2011) or even insects (Al-lawati et al., 2009).<br />
A long time ago and by subjective assessment, the experimented observer<br />
was only able to estimate two sperm motion traits: the percentage of<br />
motile sperm cells and the total duration of spermatozoa movement. Then,<br />
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