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Taguchi approach significantly increases bioremediation process efficiency: a case study with Hg (II) removal by Pseudomonas aeruginosa
Author(s) -
Tupe S.G.,
Rajwade J.M.,
Paknikar K.M.
Publication year - 2007
Publication title -
letters in applied microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.698
H-Index - 110
eISSN - 1472-765X
pISSN - 0266-8254
DOI - 10.1111/j.1472-765x.2007.02152.x
Subject(s) - taguchi methods , orthogonal array , bioremediation , response surface methodology , volume (thermodynamics) , pseudomonas aeruginosa , process optimization , design of experiments , surface area to volume ratio , process variable , chemistry , chromatography , process (computing) , environmental science , chemical engineering , environmental engineering , mathematics , computer science , biology , bacteria , engineering , statistics , physics , quantum mechanics , genetics , operating system
Aim: Optimization of process parameters for mercury removal by an Hg (II)‐reducing Pseudomonas aeruginosa strain. Methods and Results: A strain of Ps. aeruginosa was found to reduce 10 mg l −1 Hg (II) to Hg 0 with 70% efficiency in 24 h. To optimize process performance, a statistical tool – Taguchi design of experiments (DOE) – was used to carry out 18 well‐defined experiments (L18 Orthogonal array) with eight variable parameters (viz. agitation, temperature, pH, carbon source, medium volume: flask volume ratio and concentrations of Hg (II), ammonium sulfate and yeast extract). When data obtained were analyzed using specialized software for Taguchi design, Qualitek‐4 (Nutek Inc., MI, USA), Hg (II) reduction efficiency was predicted to be 95% in 24 h under the optimized process parameters (also suggested by the software). In the validation experiment, Hg (II) removal of 99·29% in 24 h was indeed obtained. Conclusions: Using Taguchi DOE, Hg (II) reduction (and hence its removal) using Ps. aeruginosa could be improved by 29·3%. Significance and Impact of the Study: Taguchi approach could be employed as an efficient and time‐saving strategy for parameter optimization in bioremediation processes.