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Joint effect of temperature,salinity and pH on the percentage fertilization and hatching of Nile tilapia ( Oreochromis niloticus)
Authors:Wang Hui  Zhu Xiaowen  Wang Haizhen  Qiang Jun  Xu Pao  Li Ruiwei
Affiliation:1. Fisheries College, Guangdong Ocean University, , Zhanjiang, Guangdong, China;2. Freshwater Fisheries Research Center of Chinese Academy of Fishery Sciences, , Wuxi, China;3. Maonan Sangao Tilapia Breeding Base, , Maoming, Guangdong, China
Abstract:Rested upon Box‐Behnken experimental design and response surface method, the joint effect of temperature, salinity and pH on the fertilization and hatching in Nile tilapia was studied under laboratory conditions. Results showed that the linear and quadratic effects of temperature, salinity and pH on fertilization and hatching were all statistically significant (< 0.01). Interactions between temperature and salinity, and between temperature and pH on fertilization and hatching statistically differed from zero (< 0.05). Interaction between salinity and pH on hatching was significant (< 0.05), but nonsignificant on fertilization (> 0.05). Regressions of fertilization and hatching towards temperature, salinity and pH were established, with the determination coefficient being 99.17% for fertilization and 99.79% for hatching, and could be used for prediction. By utilizing statistical optimization technique, the optimal temperature/salinity/pH combinations were attained: 27.6°C/9.3 ppt/7.5 for fertilization, at which the maximum fertilization was 87.7%, with the desirability being 92.11%; and 27.1°C/9.2 ppt/7.4 for hatching, at which the maximum hatching rate reached 81.2%, with the desirability as high as 96.74%. It could be said that the fertilization and hatching concurrently culminated at the 27.3°C/9.2 ppt/7.4 combination. It can be envisioned that the application of these results derived would give an impetus to the tilapia seed production efficiency and in turn to the development of tilapia husbandry.
Keywords:genetically improved farmed tilapia  reproduction  environmental factor     Box‐Behnken design  response surface  optimization
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