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The aim of this work was to optimize the hydrolysis and fermentation of plantain peels. Kinetic study was also carried out. Proximate analysis of plantain peels was carried out and the result showed that it contains 46% cellulose. Aspergillus niger isolated and screened for cellulase activities was used as the crude enzyme for the hydrolysis and commercial available Saccharomyces cerevisae was used for the fermentation. The optimization was done using quadratic model of central composite rotatable design for both hydrolysis and fermentation. Analysis of variance ANOVA was used to test for the significance of the model and the factors. The results of the analysis showed that temperature, time, pH and the substrate concentration significantly affected the yield of simple sugar in the hydrolysis of plantain peels. The result equally showed that temperature, time and pH were significant factors of fermentation. The optimum conditions for the hydrolysis were 35°C, 5 days, and pH of 5.5, substrate concentration of 8 g/30ml and glucose yield of 49%. Also the optimum conditions of fermentation were obtained as 30°C, pH of 4.0, 9 days and ethanol yield of 19%. The Michaelis-Menten model adequately fit both the hydrolysis and fermentation kinetics.

In many parts of the world, demands for ethanol as an alternative source of energy have steadily increased due to efforts in decreasing the overall amount of greenhouse gases emitted into the atmosphere, dwindling fossil fuel resources, increased gasoline prices and the need to reduce the global unemployment rate [

Obviously there is a growing interest for economical sustainable biofuel all over the world. In Nigeria, the use of waste lignocelluloses biomass for ethanol production has been the subject of many researches. The conversion of waste lignocelluloses in Nigeria will not only reduce the over dependence on petroleum based fuel, and diversify the economy, but will reduce the growing unemployment and sanitize the environment without affecting the human food chain [

The advantages of the enzymatic route over other chemical routes include higher yield, minimal by products formations, low energy requirements, mild operating conditions and environmentally friendly processing [

Ighadaro [

Ripped plantain peels obtained from Oye Market Emene Enugu, was chopped into small pieces and dried in an oven at 65˚C for 48 hr [

The crude protein was analyzed using the Kjedal method and the fats and oils was measured using the Sohxlet method [_{2}SO_{4} for 4.5 hrs. The suspension after the treatment with the acid was filtered through a crucible and the solid residue dried at 105˚C for 24 hrs and weighed (W1). The residue was then transferred to a pre-weighed dry porcelain crucible and heated at 600˚C for 5 hrs. After cooling down, it was weighed (W2) as the ash content. The lignin was calculated by the difference (W1-W2) [

The method of Kurschner-Hanack [

Aspergillus niger was isolated and screened for cellulase activities following the method prescribed by Ezonu et al., [

1% innoculum of the multiplied A. niger from a PDA slant was prepared by aseptically transferring 10 g of the pure and screened A. niger from the slant to a 1liter volumetric flask. Distilled water autoclaved at 121˚C for 15 mins was added to make the mark of the flask. The mixture was left for 5 to 10 minutes at 150 rpm. The inoculums size was set to have a cell concentration of 1.0 × 10^{8} cells per ml [

A commercial available dried form of industrial S. cerevisiae yeast was used in this research. For inoculum, 100 ml of distilled water was heated to 40˚C in a shake flask and 0.5% (w/w) of S. cerevisiae yeast was added to the warm water to activate the yeast. The mixture was left for 5 to 10 min at 150 rpm. The inoculums size was set to have a cell concentration of 5.3 × 10^{7} cells per ml [

The enzymatic hydrolysis was carried out in 250 cm^{3} conical flask containing 50 cm^{3} of 5% inoculums of A. niger with different dosage of the plantain peels and incubated on a shaker with an agitation rate of 300 rpm at different temperatures for different time interval and at different pH. The mixture was filtered and the soluble sugar yield in the filtrate was measured using the refractometer (Model RF M960 available at PRODA, Enugu) while the reducible sugar yield was determined using the DNS method [

The fermentation was carried out in 250 cm^{3} conical flask containing 30-cm^{3} of medium obtained from either enzymatic hydrolysis [

This was carried out using a simple distillation set up. The fermented liquid was transferred into round bottom flask and placed on a heating mantle fixed to a distillation column enclosed in running tap water. Another flask was fixed to the other end of distillation column to collect the distillate at 78˚C [

The distillate collected was measured using a measuring cylinder and expressed as quantity of ethanol produced

Factor | Symbol | −1 | 0 | +1 | −2.0 | +2.0 | |
---|---|---|---|---|---|---|---|

Temperature (˚C) | X1 | 28 | 35 | 42 | 21 | 49 | |

Time (days) | X2 | 3 | 5 | 7 | 1 | 9 | |

pH | X3 | 3.5 | 5.5 | 7.5 | 1.5 | 9.5 | |

DOSAGE (g/50ml) | X4 | 5 | 8 | 11 | 2 | 14 | |

No of core points n_{j} | 16 | ||||||

No of starlike points n_{α} | 8 | ||||||

No of null points n_{o} | 6 | ||||||

Total no of points n | 30 | ||||||

in g/l by multiplying the volume of the distillate by the density of ethanol [

Ethanol concentration was determined by comparing the density of the ethanol produced with the standard ethanol density curve [

Based on the result of the screening of factors, an optimization experiment was carried out to determine the optimum parameters for the enzymatic hydrolysis of plantain peels. The Central Composite Rotatable Design (CCRD) was applied for the optimization experiment.

An optimization experiment was carried out to obtain the optimum parameters for the fermentation of the hydrolyzed plantain peels. The Central Composite Rotatable Design (CCRD) was also used for this study.

The kinetics model is based on the following theorems:

The rate of the reaction is given by the Equation (1)

where C_{A} is the concentration of the limiting reactant, in this case the limiting reactant is the cellulose and hemicelluloses content of the plantain peels.

The differential,

The numerical differential formula is used when the data points in the independent variable are equally spaced, such as:

The three-point differential formulae are presented in Equations (2)-(5):

Initial point:

Interior points:

Factor | Symbol | −1 | 0 | +1 | −1.68 | +1.68 |
---|---|---|---|---|---|---|

Temperature (˚C) | X1 | 30 | 40 | 50 | 23 | 56.8 |

Time (days) | X2 | 3 | 6 | 9 | 1 | 11 |

pH | X3 | 4 | 6 | 8 | 2.6 | 9.3 |

No of core points n_{j} | 8 | |||||

No of starlike points n_{α} | 6 | |||||

No of null points n_{o} | 6 | |||||

Total no of points n | 20 |

Time (hrs) | t_{0 } | t_{1} | t_{2} | t_{3} | t_{4} | t_{5} |
---|---|---|---|---|---|---|

C_{A} (g/dm^{3}) | C_{A0} | C_{A1} | C_{A2} | C_{A3} | C_{A4} | C_{A5} |

Last point:

Equations (2)-(5) were used to calculate the change in the reactant concentration with time

The method of Kurschner-Hanack [

This method is a gravimetric method where the weight of cellulose and hemicellulose is measured when nitric acid and Acetic acid dissolved every other component of the plantain peels; cellulose and hemicellulose are insoluble in water, acetic acid and nitric acid.

1 gram of the plantain peel sample is measured in a round bottom flask. 15 ml of 80% acetic acid and 1.5 ml of raw nitric acid are added into the flask. The flask is connected to a reflux condenser and heated with a heating mantle for 2 hours. The solution after heating is filtered and the residue is washed and dried in an oven at 105˚C. The dried residue is weighed as the cellulose and hemiccellulose content of the sample.

The form of the Michaelis-Menten kinetic equation is given as in Equation (6) [

where r_{A} = the rate of the enzymatic reaction;

V_{max} = the maximum rate of the reaction for a given total enzyme concentration;

K_{m} = the Michaelis-Menten constant;

S = the substrate concentration.

The linear form of the model is given in Equation (7)

The plot of _{max} and K_{m} can be calculated from the intercept and the slope respectively.

The results of the proximate analysis shown in

The optimization of the hydrolysis of plantain peels using quadratic model of Response Surface or Central Composite Design of experiment gave a significant model; the results of the second order response surface model in the form of analysis of variance (ANOVA) are given in ^{2}). In this case, the value of the determination coefficient (R^{2} = 0.9330) indicates that only 6.7% of the total variations are not explained by the model. A high value of the correlation coefficient, (R^{2} = 0.9330) justifies an excellent correlation between the independent variables. The value of the adjusted determination coefficient (Adj. R^{2} = 0.87004) is also high to advocate for a high significance of the model [

where A = temperature (˚C), B = time (days), C = pH and D = substrate concentration (g/30ml).

Deleting the non significant terms, the model equation reduces to:

According to Tengborg et al., [

Component | % Composition |
---|---|

Lignin | 25.7 |

Crude protein | 6.8 |

Cellulose/hemicelluloses | 46.5 |

Ash | 5.9 |

Moisture | 7.8 |

Fats and oil | 7.3 |

Source | Sum of squares | df | Mean square | F value | p-value Prob > F | Remarks |
---|---|---|---|---|---|---|

Model | 436.13 | 14 | 31.15 | 14.91 | <0.0001 | significant |

A-Temperature | 170.67 | 1 | 170.67 | 81.70 | <0.0001 | |

B-Time | 28.17 | 1 | 28.17 | 13.48 | 0.0023 | |

C-pH | 73.50 | 1 | 73.50 | 35.19 | <0.0001 | |

D-Substrate Conc | 32.67 | 1 | 32.67 | 15.64 | 0.0013 | |

AB | 4.00 | 1 | 4.00 | 1.91 | 0.1867 | |

AC | 6.25 | 1 | 6.25 | 2.99 | 0.1042 | |

AD | 12.25 | 1 | 12.25 | 5.86 | 0.0286 | |

BC | 5.684E−014 | 1 | 5.684E−014 | 2.721E−014 | 1.0000 | |

BD | 4.00 | 1 | 4.00 | 1.91 | 0.1867 | |

CD | 0.25 | 1 | 0.25 | 0.12 | 0.7342 | |

A^{2} | 29.76 | 1 | 29.76 | 14.25 | 0.0018 | |

B^{2} | 5.76 | 1 | 5.76 | 2.76 | 0.1175 | |

C^{2} | 0.19 | 1 | 0.19 | 0.091 | 0.7668 | |

D^{2} | 65.19 | 1 | 65.19 | 31.21 | <0.0001 | |

Residual | 31.33 | 15 | 2.09 | |||

Lack of Fit | 24.50 | 10 | 2.45 | 1.79 | 0.2696 | Not significant |

Pure Error | 6.83 | 5 | 1.37 | |||

Cor Total | 467.47 | 29 |

Std. Dev = 1.45, Mean = 20.47, C.V % = 7.06, PRESS = 150.96, R-Square = 0.9330, Adj R-Squared = 0.8704, Pred. R-Squared = 0.6771, Adeq Precision = 16.145.

Factors | Temp (˚C) | Time (days) | pH | Subs. conc (g/30ml) | Glucose yield % (predicted) | Yield (%) experimental |
---|---|---|---|---|---|---|

Optimum | 35.000 | 5.000 | 5.500 | 8.000 | 52.3 | 49.1 |

The graph of the predicted against the actual values shown in

The contour and 3D graphs of Figures 2-7 show the factors and the interactive effects on the yield of simple sugar (Glucose).

1) The effect of temperature

The relationship between temperature and glucose yield was seen to be inverse. The yield of glucose decreases with the temperature and the optimum was seen at around 35˚C. At a temperature level from the ambient to 35˚C, the glucose yield increased considerably and decreased at a higher temperature. The effect of temperature on the yield of glucose was however significant as confirmed in

Temperature has effective interaction with other factors however only the interaction with the substrate concentration was significant (

Zapkaa et al. [

2) The effect of pH

The contour and 3D plots of

The interactive effects of the pH with other factors were not significant. This was shown in

Akponah and Akpomie [

3) The effect of substrate concentration

The substrate concentration is the amount of plantain peels (g) that was soaked into 30 ml of the inoculums of A. niger prepared as shown in Section 2.3.

concentration was higher than the rate at a substrate concentration close to the optimum value. The rate of the glucose decrease above the optimum value of concentration was low.

Zapkaa et al. [

Substrate concentration had a significant interaction with temperature (

4) The effect of time

From the selected optimum solution, the optimum time of the hydrolysis reaction was 5 days. This can also be seen from the result of the kinetics study shown in

Zakpaa et al. [

over the incubation period. Akponah and Akpomie [^{th} day of incubation and suggested that hydrolysis is dependent on the growth kinetics of the fungus.

The optimization of the fermentation experiment was carried out using the Central Composite Rotatable Design or the Box-Wilson design. The model of the experiment used was quadratic model. The Model F-value of 57.25 implies the model is significant. There is only a 0.01% chance that an F-value this large could occur due to noise. Values of “Prob > F” less than 0.0500 indicate model terms are significant. In this case A, B, C, AB, AC, A^{2}, B^{2}, C^{2} are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. The goodness of fit of the model was checked by the determination coefficient (R^{2}) (^{2} = 0.9810) indicates that only 1.4% of the total variations are not explained by the model. A higher value of the correlation coefficient, (R^{2} = 0.9810) justifies an excellent correlation between the independent variables. The value of the adjusted determination coefficient (Adj. R^{2} = 0.9638) is also

high to advocate for a high significance of the model [

Removing the non significant term, the model equation reduces to:

where A = temperature (˚C), B = pH and C = time (days).

Source | Sum of squares | df | Mean square | F value | p-value Prob > F | |
---|---|---|---|---|---|---|

Model | 14.60 | 9 | 1.62 | 57.25 | <0.0001 | Significant |

A-temperature | 1.20 | 1 | 1.20 | 42.48 | <0.0001 | |

B-pH | 0.77 | 1 | 0.77 | 27.22 | 0.0004 | |

C-Time | 1.56 | 1 | 1.56 | 55.00 | <0.0001 | |

AB | 4.35 | 1 | 4.35 | 153.54 | <0.0001 | |

AC | 1.53 | 1 | 1.53 | 54.03 | <0.0001 | |

BC | 0.011 | 1 | 0.011 | 0.40 | 0.5428 | |

A^{2} | 4.05 | 1 | 4.05 | 142.93 | <0.0001 | |

B^{2} | 1.46 | 1 | 1.46 | 51.43 | <0.0001 | |

C^{2} | 0.36 | 1 | 0.36 | 12.84 | 0.0050 | |

Residual | 0.28 | 10 | 0.028 | |||

Lack of fit | 0.21 | 5 | 0.042 | 2.78 | 0.1432 | Not significant |

Pure error | 0.075 | 5 | 0.015 | |||

Cor total | 14.89 | 19 |

Std. Dev = 0.17, Mean = 8.23, C.V. % = 2.04, PRESS = 1.69, R-Squared = 0.9810, Adj. R-Squared = 0.9638, Pred R-Squared = 0.8863, Adeq Precision = 29.411.

The interactive effects of the factors for fermentation are shown by the contour and 3D plots of Figures 9-11.

1) The effect pH on fermentation

pH of the solution is a significant factor of fermentation (p value < 0.0001,

Abah et al. [

2) The effect time on fermentation

The optimum duration for the fermentation of the plantain peals was 9 days. The duration of the fermentation had a significant effect on fermentation as can be seen in

Time had an interactive effect with temperature as can be seen from the curves of the contour plot of

Temperature (˚C) | pH | Time (days) | Ethanol yield (%) (predicted) | Yield (%) experimental |
---|---|---|---|---|

30.000 | 4.000 | 9.000 | 21.194 | 19.8 |

of time with pH is obvious from the contour plot of

Akponah and Akpomie [

3) The effect of temperature on fermentation

The optimum temperature for the fermentation of the hydrolyzed plantain peels was 30˚C. Temperature was a significant factor of fermentation as can been seen from the ANOVA table of

This optimum fermentation temperature of 30˚C had been widely reported by other researchers [

Following the linear form of model equation (Equation (7))

The kinetics parameters and the fitness were determined using the linear plot shown in

The value of the correlation coefficient R^{2}, being close to 1 shows that Michaelis-Menten model described the kinetics of the enzymatic hydrolysis. It can be seen that the rate of the reaction decreased with time and remained almost constant after the fifth day

Using the Michaelis-Menten parameters calculated, the kinetics equation for the hydrolysis was obtained as shown in Equation (13) by substituting the parameters into Equation (6).

Time (days) | Cellulose conc. (g/L) C_{A} | Rate of reaction | ^{ } | ^{ } |
---|---|---|---|---|

0 | 49 | 19 | 0.02 | 0.053 |

1 | 32 | 15 | 0.03 | 0.067 |

2 | 19 | 10.5 | 0.05 | 0.095 |

3 | 11 | 7 | 0.09 | 0.143 |

4 | 5 | 5 | 0.2 | 0.2 |

K_{m} (g∙dm^{−3}) | V_{max} (g∙dm^{−3}∙day^{−1}) | R^{2 } |
---|---|---|

16.2 | 20.4 | 0.946 |

The kinetics of the fermentation was modeled using the Michaelis-Menten equation. The concentration of the glucose in the fermentation is measured with time using the DNS method. The numerical method is used to calculate the differential change in glucose concentration with time.

The closeness of R^{2} to 1 also confirmed that the kinetics of the fermentation was described by the Michaelis- Menten equation.

Based on the values of the Michaelis-Menten parameters in

The quadratic model of central composite rotatable design CCRD was an adequate model for the enzymatic hydrolysis of plantain peels using Aspergillus niger. Temperature, time, pH and substrate concentration were significant factors that affected the yield of simple sugar in enzymatic hydrolysis. The optimum parameters in enzymatic hydrolysis were 35˚C, 5 days, 5.5 and 8 g/30ml for temperature, time, pH and substrate concentration

Time (days) | Glucose conc: C_{A} (g/dm^{3}) | 1/C_{A} | Rate: _{ } (g/dm^{3}/day) | −1/r_{A} |
---|---|---|---|---|

0 | 83 | 0.012 | 39.5 | 0.025 |

1 | 50 | 0.020 | 26.5 | 0.038 |

2 | 30 | 0.033 | 13.0 | 0.077 |

3 | 24 | 0.042 | 8.0 | 0.125 |

4 | 14 | 0.071 | 7.5 | 0.133 |

5 | 9 | 0.111 | 4.5 | 0.222 |

6 | 5 | 0.200 | 3.5 | 0.286 |

K_{m} (g∙dm^{−3}) | V_{max} (g∙dm^{−3}∙day^{−1}) | R^{2 } |
---|---|---|

39 | 28.6 | 0.921 |

respectively. The quadratic model of central composite rotatable design was also an adequate model for fermentation of the hydrolyzed peels. The fermentation optimum parameters were 30˚C, 9 days and 4.0 for temperature, time and pH respectively. It can be concluded that Aspergillus niger can yield 50% simple sugar from plantain peels and the feremtation using Saccharomyces cerevisae can yield 20% ethanol when the optimum conditions are observed. The kinetics of the hydrolysis and the fermentation follows the Michaelis-Menten model as can be seen by the correlation coefficient of the model.

Philomena Kanwulia Igbokwe,Christian Nnabuike Idogwu,Joseph Tagbo Nwabanne, (2016) Enzymatic Hydrolysis and Fermentation of Plantain Peels: Optimization and Kinetic Studies. Advances in Chemical Engineering and Science,06,216-235. doi: 10.4236/aces.2016.62023