Statistical Optimisation of Fermentation Media for Novel <i>Clostridium novyi</i> -NT Using Response Surface Methodology.

Krishnamoorthy, Kannan; Landge, Anil Vijay

doi:10.1590/1678-4324-2018180026

Kannan Krishnamoorthy ^**Author for correspondence: egkkannan@yahoo.co.in

Annamalai University Department of Pharmacy - Pharmacy, Tamilnadu, India

Anil Vijay Landge

Annamalai University Department of Pharmacy - Pharmacy, Tamilnadu, India

*Author for correspondence: egkkannan@yahoo.co.in

Figures (8)
Tables (8)

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Figure 1
Response surface curve (a) and contour plot (b) for absorbance, illustrates interactions between trypticase soya broth and peptone concentrations after 22 h of fermentation.

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Figure 2
Response surface curve (a) and contour plot (b) for absorbance, illustrates interactions between pH and trypticase soya broth concentrations after 22 h of fermentation.

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Figure 3
Response surface curve (a) and contour plot (b) for absorbance, illustrates interactions between pH and peptone concentrations after 22 h of fermentation.

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Figure 4
Response surface curve (a) and contour plot (b) for enzyme activity, illustrates interactions between trypticase soya broth and peptone concentrations after 22 h of fermentation.

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Figure 5
Response surface curve (a) and contour plot (b) for enzyme activity, illustrating interactions between pH and peptone concentrations after 22 h of fermentation.

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Figure 6
Response surface curve (a) and contour plot (b) for enzyme activity, showing interactions between pH and trypticase soya broth concentrations after 22 h of fermentation.

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Figure 7
Perturbation curves indicating interaction of various factors involved in absorbance (a) and enzyme activity (b).

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Figure 8
Parity plot indicating the distribution of experimental vs predicted values of biomass concentration and enzyme activity.

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Table 1
Real and coded variables used to optimize fermentation media for C. novyi -NT in central composite design (CCD).

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Table 2
Experimental design and result of full model CCD for two responses

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Table 3
Analysis of variance for response surface quadratic model on the optimization of Absorbance

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Table 4
Summary of results for optimization of Absorbance in ANOVA.

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Table 5
Analysis of variance for response surface quadratic model on the optimization of collagenase activity

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Table 6
Summary of results for optimization of Collagenase activity in ANOVA.

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Table 7
Optimization criteria used in this study with help of CCD quadratic model.

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Table 8
Most desirable solution obtained while optimized combination of fermentation parameters for biomass density and enzyme activity.

Independent variables	Names of Independent variables	Levels*
Independent variables	Names of Independent variables	Lower (-1)	Central (0)	Higher (+1)	Axial (-α)	Axial (+α)
x₁ - (g 100 ml^-1)	Concentration of trypticase soya broth (A) in g	1.0	1.5	2.0	5	2.5
x₂ - (g 100 ml^-1)	Proteose peptone (B) in g	4.5	5	5.5	4.0	6.0
x₃	pH of medium (C)	6.5	7.0	7.5	6.0	8.0
* x₁= (X₁ - 1.5) /0.5; x₂= (X₂ - 5) /0.5; x₃= (X₃ - 7) /0.5

Std order	Coded A	Coded B	Coded C	Absorbance		Enzyme activity (Units/mg)
Std order	Coded A	Coded B	Coded C	Actual	Predicted	Actual	Predicted
1	-1	-1	-1	0.75	0.7204	120.66	120.40
2	1	-1	-1	0.919	0.8793	215.56	215.34
3	-1	1	-1	0.824	0.781	295.5	275.71
4	1	1	-1	0.941	0.8987	200.08	194.01
5	-1	-1	1	0.529	0.5007	116.22	120.09
6	1	-1	1	0.563	0.5455	240.27	221.79
7	-1	1	1	0.812	0.8222	235.56	227.23
8	1	1	1	0.856	0.8561	142.22	133.93
9	-α	0	0	0.672	0.6991	235.11	233.02
10	α	0	0	0.847	0.861	220.52	234.41
11	0	-α	0	0.452	0.5123	112.81	122.97
12	0	α	0	0.869	0.8502	202.67	204.61
13	0	0	-α	0.903	0.9314	210.33	202.66
14	0	0	α	0.647	0.6597	122.65	142.39
15	0	0	0	0.611	0.6376	150.33	227.23
16	0	0	0	0.623	0.6376	164.08	227.23
17	0	0	0	0.672	0.6376	182.22	227.23
18	0	0	0	0.614	0.6376	158.67	227.23
19	0	0	0	0.681	0.6376	178.17	227.23
20	0	0	0	0.632	0.6376	168.33	227.23

Source	Sum of Squares	df	Mean Square	F Value	p-value Prob > F
Model	0.37	9	0.041	27.18	< 0.0001*
A	0.03	1	0.032	21.07	0.0010*
B	0.14	1	0.138	91.67	< 0.0001*
C	0.09	1	0.089	59.30	< 0.0001*
AB	0.00	1	0.000	0.15	0.7100
AC	0.01	1	0.005	3.59	0.0874
BC	0.03	1	0.029	19.12	0.0014*
A²	0.04	1	0.037	24.36	0.0006*
B²	0.00	1	0.003	2.29	0.1615
C²	0.05	1	0.045	29.94	0.0003*
Residual	0.02	10	0.002

Source	Sum of Squares	df	Mean Square	F Value	p-value Prob > F
Model	44049.83	9	4894.425	23.48	< 0.0001*
A	2.34	1	2.340	0.01	0.9177
B	8060.07	1	8060.074	38.66	< 0.0001*
C	4394.86	1	4394.856	21.08	0.0010*
AB	20778.43	1	20778.431	99.68	< 0.0001*
AC	121.91	1	121.914	0.58	0.4621
BC	2382.92	1	2382.916	11.43	0.0070*
A²	8144.70	1	8144.701	39.07	< 0.0001*
B²	14.47	1	14.473	0.07	0.7975
C²	63.04	1	63.038	0.30	0.5945

Source	Mean square	F value	p-value (Prob>F)
Model	4894.425	23.48	< 0.0001	Significant
Lack of Fit	274.123	1.92	0.2457	non significant*

Parameter	Limit		Criterion
Parameter	lower	Upper
pH	6.5	-	Target
T. Soya broth in g	1	-	Target
Peptone in g	-	5.5	Target
Absorbance	0.452	0.941	Maximize
Enzyme Activity in units/mg	112.81	295.5	Maximize

Solution no.	T. Soya Broth in g	Peptone in g	pH	Predicted Absorbance	Actual Absorbance	Predicted Enzyme Activity in Units/mg	Actual Enzyme Activity in Units/mg	Desirability
1	1.0	5.5	6.5	0.81198	0.8309 ± 0.0012	305.428	298.88±1.36	0.94058
2	1.0	5.5	6.5	0.78863	-	282.868	-	0.91484
3	1.0	5.5	6.5	0.78809	-	282.047	-	0.91058
4	1.0	5.5	6.5	0.78763	-	282.217	-	0.91044
5	1.0	5.5	6.5	0.78739	-	280.982	-	0.90489

[1] *Author for correspondence: egkkannan@yahoo.co.in

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Statistical Optimisation of Fermentation Media for Novel Clostridium novyi -NT Using Response Surface Methodology.

ABSTRACT