title: Response surface optimization of the critical medium components for the production of alkaline protease by a newly isolated Bacillus sp.
abstract: OBJECTIVE
  Optimization of the fermentation medium for maximum alkaline protease production was carried out using a new strain, Bacillus Sp. PE-11.
  
  
  METHODS
  The carbon source (glucose), the nitrogen source (peptone) and salt solution were selected to optimize. A 2(3 )full factorial composite experimental design and response surface methodology were used in the design of experiments and in the analysis of results. This procedure limited the number of actual experiments performed while allowing for possible interactions between the three components.
  
  
  CONCLUSIONS
  The optimum values for the tested variables for the maximum alkaline protease production were; glucose 7.798 (g/L), peptone 9.548 (g/L) and salt solution 8.757%. The maximum alkaline protease production was 4,98,123 PU/L. This method was efficient; only 20 experiments were necessary to assess these conditions, and model adequacy was very satisfactory, as the coefficient of determination was 0.941.
  
  
  CONCLUSIONS
  In the work, we have demonstrated the use of a central composite factorial design by determining the conditions leading to the high yield of enzyme production. Thus, smaller and less time consuming experimental designs could generally suffice for the optimization of many fermentation processes.
authors.affiliation: Pharmaceutical Biotechnology Division, Department of Pharmaceutical Sciences, Andhra University, Visakhapatnam, India.
authors.forename: K
authors.initials: K
authors.lastname: Adinarayana
authors.forename: P
authors.initials: P
authors.lastname: Ellaiah
mesh_terms: D000704:Analysis of Variance; D001407:Bacillus / Q000201:enzymology* / Q000254:growth & development* / Q000378:metabolism; D003470:Culture Media / Q000737:chemistry / Q000378:metabolism; D005285:Fermentation; D005947:Glucose / Q000378:metabolism*; D007700:Kinetics; D015233:Models, Statistical; D009010:Monte Carlo Method; D010447:Peptide Hydrolases / Q000378:metabolism; D010461:Peptones / Q000378:metabolism*; D012107:Research Design / Q000706:statistics & numerical data; D012697:Serine Endopeptidases / Q000096:biosynthesis* / Q000378:metabolism; D013045:Species Specificity; D014443:Tyrosine / Q000378:metabolism
chemical_list: D003470:Culture Media; D010461:Peptones; D014443:Tyrosine; D010447:Peptide Hydrolases; D012697:Serine Endopeptidases; C032923:microbial serine proteinases; D005947:Glucose