On-station growth performance of rainbow trout fingerlings with different stocking densities

Abstract

A study was conducted to evaluate the performance of Rainbow trout (Oncorhynchus mykiss) fingerlings with different stocking densities under station conditions at Trout breeding centre, Haa. The trout fingerlings with initial average weight of 9.78  0.67 g were grown in different stocking densities of SD₁₀, SD₁₅ and SD₂₀ with 10 kg/m³, 15 kg/m³ and 20 kg/m³ fingerlings respectively. The fingerlings were reared in the tanks of capacity 0.7452 m³ for the duration of 107 days. The parameters like mean weight gain, mean length gain, Specific Growth Rate (SGR), Feed Conversion Ratio (FCR) and survival of the fingerlings stocked at different densities were assessed during the study period. The result indicated that there was a significant difference (P < 0.05) in the mean final weight of the fingerlings raised in different tanks. The mean final weight was recorded highest at SD₁₀ with 59.16 ± 1.98 g followed by SD₁₅ with 50.86 ± 8.61 g and SD₂₀ with 42.26 ± 6.62 g respectively. Moreover, the highest mean weight gain was obtained from the fingerlings with SD₁₀ followed by SD₁₅ and SD₂₀ with 49.38 g, 41.08 g and 32.44 g respectively. The higher growth rate was observed in the fingerlings with lower densities. Though not significant, the mean final length of the fingerlings was also recorded highest at SD₁₀ (15.69 ± 1.74 cm) followed by SD₁₅ and SD₂₀ with 14.58 ± 1.32 cm and 13.96 ± 1.23 cm respectively. The survival of fingerlings was recorded higher with lower stocking density and FCR was also in favour of the lower density. Besides, the finding was also indicative that SGR was better in fingerlings with lower stocking density. It is suggestive that stocking density had significant effect on mean final weight, mean final length, SGR and FCR of the fingerlings. Thus, the study concludes that for optimal growth of trout fingerlings, the stocking density of (10kg/m³) is recommended in trout hatcheries under Bhutanese rearing conditions to optimize production for higher returns.