Department of Environmental Engineering, Peking University, The Key Laboratory of Water and Sediment Sciences, Ministry of Education, Beijing, China.
PLoS One. 2013;8(4):e60322. doi: 10.1371/journal.pone.0060322. Epub 2013 Apr 2.
Statistical methodology was applied to the optimization of the ammonium oxidation by Nitrosomonas europaea for biomass concentration (C(B)), nitrite yield (Y(N)) and ammonium removal (R(A)). Initial screening by Plackett-Burman design was performed to select major variables out of nineteen factors, among which NH4Cl concentration (C(N)), trace element solution (TES), agitation speed (AS), and fermentation time (T) were found to have significant effects. Path of steepest ascent and response surface methodology was applied to optimize the levels of the selected factors. Finally, multi-objective optimization was used to obtain optimal condition by compromise of the three desirable objectives through a combination of weighted coefficient method coupled with entropy measurement methodology. These models enabled us to identify the optimum operation conditions (C(N)= 84.1 mM; TES = 0.74 ml; AS= 100 rpm and T = 78 h), under which C(B)= 3.386×10(8) cells/ml; Y(N)= 1.98 mg/mg and R(A) = 97.76% were simultaneously obtained. The optimized conditions were shown to be feasible through verification tests.
采用统计方法对欧洲亚硝化单胞菌的生物量浓度 (C(B))、亚硝态氮产率 (Y(N)) 和氨氮去除率 (R(A)) 的铵氧化进行了优化。通过 Plackett-Burman 设计进行了初始筛选，从 19 个因素中选择了主要变量，其中发现氯化铵浓度 (C(N))、微量元素溶液 (TES)、搅拌速度 (AS) 和发酵时间 (T) 有显著影响。采用最陡上升路径和响应面法对选定因素的水平进行了优化。最后，通过加权系数法与熵测度法相结合的组合，对三个理想目标进行折衷，进行多目标优化以获得最佳条件。这些模型使我们能够确定最佳操作条件（C(N)=84.1 mM；TES=0.74 ml；AS=100 rpm 和 T=78 h），在此条件下，同时获得 C(B)=3.386×10(8) 个细胞/ml；Y(N)=1.98 mg/mg 和 R(A)=97.76%。通过验证试验表明优化条件是可行的。
