| A preliminary stochastic model for managing microorganisms in a recirculating aquaculture system | |
Fu, Songzhe1,3; Liu, Ying2 ; Li, Xian2; Tu, Junling1; Lan, Ruiting3; Tian, Huiqin4
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| 2015-06-01 | |
| 发表期刊 | ANNALS OF MICROBIOLOGY
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| 卷号 | 65期号:2页码:1119-1129 |
| 文章类型 | Article |
| 摘要 | Predicting the growth of key microorganisms is essential to improve the efficiency of wastewater treatment of recirculating aquaculture systems (RAS). We have developed a stochastic model to assess quantitatively the microbial populations in RAS. This stochastic model encompassed the growth model into the Monte Carlo simulation and was constructed with risk analysis software. A modified logistic model combined with the saturation growth-rate model was successfully developed to regress the growth curves of six microorganisms. Monte Carlo simulation was employed to model the effects of chemical oxygen demand (COD) on the maximum specific growth rate. Probabilistic distributions and predictions under the different COD ranges were generated for each simulated scenario. The coefficient of determination (R (2)) and bias factor (Bf) were used to assess the performance of an established model. Logistic model produced a good fit to the growth curve of Flavobacterium sp. (R (2) = 0.9511), Acinetobacter baumannii (R (2) = 0.9970), Sphingomonas paucimobilis (R (2) = 0.9086), Vibrio natriegens (R (2) = 0.9993), Lutimonas sp. (R (2) = 0.9872) and Bacillus pumilus (R (2) = 0.9816). Bacterial population structure was determined by the construction of 16S rRNA gene libraries. A regular variation trend was observed for the dominant groups during the entire process, with a decrease of Cytophaga-Flavobacterium-Bacteroidetes from 37.6 to 18.7 % and an increase in Gammaproteobacteria from 8.5 to 30.6 %. The predicted model agreed well with observed values except for Flavobacterium sp., and the results can be applied to predict key microorganisms in actual environments. The results of this study provide a method to monitor the dynamics of key microorganisms, which can also help to evaluate the impacts of microorganisms on the operations of RAS. |
| 关键词 | Recirculating Aquaculture Systems Biofilter Monte Carlo Simulation Stochastic Model |
| DOI | 10.1007/s13213-014-0958-0 |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000354724300052 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.qdio.ac.cn/handle/337002/33038 |
| 专题 | 海洋生物技术研发中心 |
| 作者单位 | 1.Nanchang Ctr Dis Control & Prevent, Nanchang 330038, Peoples R China 2.Chinese Acad Sci, Inst Oceanol, Qingdao 266701, Peoples R China 3.Univ New S Wales, Sch Biotechnol & Biomol Sci, Sydney, NSW, Australia 4.Ocean Univ China, Coll Fisheries, Qingdao 266701, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fu, Songzhe,Liu, Ying,Li, Xian,et al. A preliminary stochastic model for managing microorganisms in a recirculating aquaculture system[J]. ANNALS OF MICROBIOLOGY,2015,65(2):1119-1129. |
| APA | Fu, Songzhe,Liu, Ying,Li, Xian,Tu, Junling,Lan, Ruiting,&Tian, Huiqin.(2015).A preliminary stochastic model for managing microorganisms in a recirculating aquaculture system.ANNALS OF MICROBIOLOGY,65(2),1119-1129. |
| MLA | Fu, Songzhe,et al."A preliminary stochastic model for managing microorganisms in a recirculating aquaculture system".ANNALS OF MICROBIOLOGY 65.2(2015):1119-1129. |
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