摘要
The biomass of petroleum-degrading bacteria, such as Halomonas spp., is crucial to the alleviation of severe oil spills through bioremediation. In this paper, the bacterium(HDMP1) was isolated and identified. Growth factors were analysed and optimised through the single-factor experiments, the factor analysis(FA), the principal component analysis(PCA), and the response surface methodology(RSM). Results indicated that HDMP1 was identified as genus Halomonas. In the single-factor experiments, the range of suitable growth conditions for HDMP1 covered: a salt concentration of 2%-4%, a medium pH value of approximately 9, an inoculum concentration of 1.0%, a substrate concentration of 1.0%-1.4%, and a rotation rate of 140 r/min. The evaluation by FA and PCA indicated that three significant growth factors were the salt concentration, the pH value, and the rotation rate. A maximum biomass of HDMP1 was obtained under the conditions covering a salt concentration of 3.5%, a medium pH of 8, and a rotation rate of 151 r/min by optimization.
The biomass of petroleum-degrading bacteria, such as Halomonas spp., is crucial to the alleviation of severe oil spills through bioremediation. In this paper, the bacterium(HDMP1) was isolated and identified. Growth factors were analysed and optimised through the single-factor experiments, the factor analysis(FA), the principal component analysis(PCA), and the response surface methodology(RSM). Results indicated that HDMP1 was identified as genus Halomonas. In the single-factor experiments, the range of suitable growth conditions for HDMP1 covered: a salt concentration of 2%—4%, a medium pH value of approximately 9, an inoculum concentration of 1.0%, a substrate concentration of 1.0%—1.4%, and a rotation rate of 140 r/min. The evaluation by FA and PCA indicated that three significant growth factors were the salt concentration, the pH value, and the rotation rate. A maximum biomass of HDMP1 was obtained under the conditions covering a salt concentration of 3.5%, a medium pH of 8, and a rotation rate of 151 r/min by optimization.
基金
funded by the National Natural Science Foundation of China(Grant No.51408347)
the Open Research Fund Program of Shandong Key Laboratory of Eco-Environmental Science for Yellow River Delta(Binzhou University)(2019KFJJ02)
the Major Science and Technology Innovation Projects in Shandong Province(2019JZZY020808)
the SDUST Graduate Technology Innovation Project(SDKDYC190321)
