Catfishes of the family Claridae comprise the most commonly cultivated fishes in Nigeria, since the culture of Clarias gariepinus through hypophysation was initiated in Western Nigeria in 1973, the procedure has been widely practiced throughout Nigeria thus leading to increase of farm-raised catfishes from the 1980 ’s to date (Adewumi and Olaleye 2011).
The availability of semen with desirable quality is one of the critical factors necessary to increase the efficiency of artificial fertilization of fish species. Increased fingerling production must be coupled with increased survival through production that involves the use of male broodstock with highly viable sperm and high milt volume. In fish reproduction under controlled conditions attempts are made to obtain sperm of highest quality and hence to produce the highest possible numbers of good quality seeds, fish sperm quality however is highly variable and depends on various external factors such as feeding regime, the quality of feed, and the rearing temperature of the male, (Canyurt and Akhan, 2008). Common practices in hatcheries such as transportation, handling, cleaning, use of chemicals, and problems with water quality are stressors that may negatively influence reproduction (Billard et al., 1995). These factors affect fertilization success in artificial reproduction commonly used for aquaculture.
The most common parameters used to evaluate sperm quality are motility rate, motile duration and fertilization ability. The percentage of motile sperm is significantly related to fertilization capacity in catfish, Clarias gariepinus (Rurangwa et al., 2001). Viable sperm is an essential component of any successful animal production operation and the success of reproduction process is dependent on a supply of high quality gametes (Cruz-Casallas et al., 2005). Spermatozoa motility is the most commonly used criterion to evaluate sperm quality. Most hatchery operations are not successful due to many factors which include immotile sperm (Bozkurt et al., 2006), therefore the research seeks to determine the sperm quality of broodstocks expressed in term of sperm count and sperm motility.
Materials and Methods
Fifteen male broodstock of Clarias gariepinus weighing between 400 g-700 g were obtained from a fish farm in Makurdi, Nigeria. They were transported to the fish hatchery of the University of Agriculture Makurdi and maintained in concrete tanks for a period of two weeks during which they were acclimatized. During this period of acclimatization, they were fed to satiation using 4 mm commercial feed.
Collection of Milt
Each male broodstock of C. gariepinus were weighed and sacrificed by spinal transection, and the testes removed. Blood and other tissue were rinsed away using saline solution. The testes were weighed and expressed as percentage body weight of the fish. Incision was made into the lobes of the testes, and the milt was squeezed into a petri dish, and its volume was measured with plastic syringe.
Determination of sperm count
Concentration of sperm was determined by counting the number of spermatozoa in simple diluents with KCl in a ratio of 1:50 under 400 x magnifications using Neubauer improved counting chamber (Rainis et al., 2003).
Determination of Percentage Motility
Percentage Motility for each sample was estimated using a light microscope at 400 x magnification immediately after addition of a drop of semen with 50 drops of KCl in a non-activating medium. Immotile sperm cells (ISC) were counted and the motile sperm cells were also quickly counted until there was no more sign of motility. Whole sperm cell (WSC) was counted using method described by Canyurt and Akhan (2008). The motile sperm cells (MC) were calculated thus
Determination of Level of Correlation of parameters and Regression
The pearson’s correlation matrix between the different parameters was done using Graphpad Prism 5 while regression analysis was done using Minitab 14 and Microsoft Excel 2007.
Table 1 shows the sperm quality parameters of the broodstocks of Clarias gariepinus. The milt volume of the experimental fish ranged from 0.2 ml to 1.3 ml. The highest milt volume (1.3 ml) was obtained from the broodstock with 639.8 g body weight and testes weight of 3.88 g, and the least milt volume (0.2 ml) was obtained from the broodstock fish with 496.6 g body weight and 0.97 g testes weight.
The highest Gonado-somatic index GSI (0.606%) was obtained from broodstock with body weight of 639.8 g and 3.88 testes weight while the least GSI (0.193%) was from 465.5 g body weight and 0.9 g testes weight.
Percentage motility of the experimental semen varied between 57.1% and 93.7%. The sperm count in the experimental fish varied between 38 x 109 spm/ml to 97 x 109 spm/ml.
Table 2, shows the correlation matrix for % motility, sperm count, volume of semen, weight of male, and weight of testes. Correlation between % motility and sperm count was significant (P = 0.00007 and r = 0.845) which indicates a strong positive correlation between the two parameters. Correlation between weight of testes and volume of semen was also very significant (P = 0.0000 and r = 0.978. Correlation between body weight and weight of testes was significant (P = 0.0049 and r = 0.684) and strongly positive. Another significant correlation was the correlation between volume of semen and the weight of broodstock which was also a strong positive correlation (P = 0.0053 and r = 0.679).
Equations 1 and 2 shows the multiple regressions to predict volume of semen from weight of male and weight of testes and to predict % motility of sperm from Volume of semen, sperm count and weight of testes respectively. Regression equation 1 is significant (P = 0.000) and the co-efficient of determination (95.7% adjusted as 94.9%) shows that 94.9% of variance in volume of semen is as a result of variance in the predictors which include weight of male and weight of testes. On the other hand, regression equation 2 is significant (0.000) with the co-efficient of determination (79.2% adjusted as 73.5%) showing that 73.5% of variance in % sperm motility being accounted for by variance in the predictor variables of the equation.
Figure 1 shows the linear regression graph for prediction of % sperm motility from sperm count. This shows that 71.4% of variance in sperm motility is accounted for by variance in sperm count. This regression is the only simple linear regression that was significant (P = 0.000).
Figure 2 shows the testicular description statistics for the samples investigated. Most of the samples had full testes while very few had semi-flat testes.
Milt quality evaluation is critical to determination of milt quality. The milt volume of the experimental fishes ranged from 0.2 ml to 1.3 ml. Eunice et al., (2010) reported a milt volume between 1.1 ml and 2.0 ml for Clarias gariepinus fed different levels of Kigelia africana (Medicinal plant), the difference in these results is attributable to different experimental diets used. Canyurt and Akhan, (2008) support this claim as they stated that fish sperm quality is highly variable and depends on various external factors such as feeding regime, the quality of feed etc. K. africana fruit extracts had been used successfully as fertility enhancing agent in rats (Abioye et al., 2003) and possess promising pro-fertility quality (Eunice et al., 2010) hence could be said to have influenced the milt volume. However the wide variance in milt volume noticed between experimental feed can be linked to genetic variability among the broodstock (Munkittrick and Moccia 1987 and McAndrew et al., 1993).
A sperm count varying from 3.8 x 1010 spm/ml to 9.7 x 1010 spm/ml was observed in the experimental fish. Leung and Jamieson (1991) stated that spermatozoa concentrations in fish may range from 2 x 106 to 5.3 x 1010.
Sperm count varying between 2.6 x 1010 spm/ml to 3.5 x 1010 spm/ml were observed in six species of carps by Verma et al., (2009), variation of this from those gotten in the experiment could be attributed to difference in genera and species involved. McAndrew et al., (1993) stated that studies on the composition of milt suggest large intra-specific and inter specific variations in spermatozoa concentration and fitness and seminal plasma composition. These variations have been attributed to genetic variability, intratesticular aging of spermatozoa, seasonality (Munkittrick and Moccia 1987), breeding state and strategy (McAndrew et al., 1993.)
The sperm count observed in the present study where higher than those in treated groups with K africana (6.5 x 109 spm/ml) as reported by Eunice et al., (2010). The fairly high proportion of sperm count observed in this experiment could be attributed to the fact that this experiment was carried out at the peak of the breeding season. This is in line with the report of Terner (1986) that motility of the spermatozoa is observed at the peak of the breeding season. Buyukhatipoglu and Holtz (1984) and Munkittrick and Moccia (1987), reported that sperm density decline as the season advanced, whereas Rideout et al., (2004) and Piironen and Hyvarinen (1983), noted that the spermatocrit and sperm concentration increased over the stripping season.
Verma et al., (2009) reported a progressive motility of sperm of more than 60% in spermatozoa of Indian major carps as well as in silver and grass carps. Studies on brown trout (Salmo truuta) and Atlantic salmon (Salmon solar) (Hajirezaee et al., 2010 and Vladic, 2011) have shown that duration of motility and proportion of active spermatozoa exhibit seasonal variation.
In rainbow trout, the proportion of spermatozoa that are activated decreases as the spawning season progressed (Buyukhatipoglu and Holtz 1984 Munkittrick and Moccia 1987), this variation was attributed to decrease as the spawning season progress in the concentration and ratio of ions such as potassium and sodium which are implicated in the initiation of sperm motility (Munkittrick and Moccia 1987). Consequently increase in the observed motility of studied fishes could be attributed to possible increase in potassium and sodium ion as the season peaks. More so, Eunice (2010) showed a strong relationship between motility and fertility as an increased motility resulted into increased fertility. Rurangwa et al., (2001) also observed a high correlation between sperm fertility and spermatozoa motility and stated that higher percentage of motile sperm is significantly correlated to fertilization capacity in catfish, Clarias gariepinus, hence it is concluded that higher motility observed in this study means broodstock will exhibit high fertility.
This study however observed that body weight and testes weight do not affect or influence the motility or viability of the sperm as the regression analysis for these parameters were not significant (P = 0.625 and P = 0.498 respectively). This can be attributed to weight gain being a function of food intake while sexual maturity is a function of time of existence and quality of food intake. it was also observed during the present study that sperm obtained from two broodstock of 600 g and 556.6 g body weight having 2.9 g and 2.8 g testes weight respectively were immotile when viewed under the microscope, this according to McAndrew et al., (1993), could be as a result of intratesticular aging of spermatozoa which is a strong cause of variation in sperm quality study.
The study has established the relevant equations to predict sperm volume and motility given the body weight of the fish, testes weight and sperm count. The value of motility for predicting fertility has been proven questionable because of the subjectivity of the technician performing the analysis and the short duration of motility following activation, fertilization capacity however, is the most conclusive test of sperm quality (McNiven et al., 1993), hence the need for more research.
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