Optimization using RSM design
Three process parameters (inoculum, temperature, time) were used for liquid
jaggery vinegar production and were incorporated into optimization RSM software to establish their optimum levels. The CCRD design of three factors was adapted to study the optimum levels and to explicate the effect of these independent variables on acetic acid concentration of the liquid
jaggery vinegar. Twenty experimental trials were carried out in randomized order as per the CCRD design. The results are presented in Table 1. The data generated was analyzed using Design Expert Software (12 version) and a present polynomial equation was obtained for the response. The second order equation (Eq. 1) was built to describe the response.
In the above equation, y and x are the response and factor for the above design. On the right hand side x
i, x
i2 and xixj are the regression coefficient for linear, quadratic and interaction effect, b is coefficient for each term which is being calculated by applying multiple regression analysis and a lack of fit was also calculated using RSM optimization tool. This model is accounted for by coefficient of determination (R
2) which shows the proportion of variability in data and a larger value of R
2 which suggests better fit of model data. An adequacy ratio of more than Table F value depicted that the model is adequate. A second order polynomial model was used to develop three dimensional plots and contour graphs which demonstrated the interaction between independent variables and their effect on the acetic acid content as response. The effects of different variables on acetic acid response of liquid
jaggery vinegar, prepared as per experimental design are presented in Table 2.
Effect of temperature, time and inoculum on acetic acid concentration in liquid jaggery vinegar of CoH160 sugarcane variety
The average acetic acid concentration of liquid
jaggery vinegar ranged from 0.53 to 3.99%. The lowest acetic acid concentration (0.5%) in vinegar was found in the experimental trial 17, whereas a highest acetic acid (3.99%) was achieved in the experimental trial 16 as shown in the Table 2. The maximum acetic acid (3.99%) was observed at a temperature of 28.5°C, fermentation period of 12.5 days and 7.5% inoculum concentration (CoH160), while minimum acetic acid (0.53%) was observed at 22.61°C temperature, 12.5 days fermentation period and 7.5% inoculum concentration (Table 2). The regression equation coefficients were calculated and the data were fitted to a second-order polynomial equation. Thus, to predict acetic acid per cent as affected by different factors which are represented in terms of their actual factors, a multiple regression equation was generated as shown below (Eq. 2):
Acetic acid (%) =
+3.92 + 0.44 *Temperature + 0.03 *Time + 0.51 *Inoculum-0.13 *Temperature *Time + 0.10 *Temperature* Inoculum + 0.45 *Time *Inoculum -0.94 *Temperature2- 0.49* Time2-0.63 *Inoculum2 …. (2)
The analysis of variance (ANOVA) depicted the acetic acid as a function of initial values of parameters. Table 3 shows the regression analysis of the data, in which the coefficient of determination (R2) was found to be 0.985 indicating that the statistical model was significant and can explain the variability in the response. The model F value was found to be 77.75, which is more than the tabulated F value as indicated in the ANOVA of quadratic model. A minimum desirable adequate precision value (APV) of 4.00 is required for high prediction ability, where in the study it was found to be 24.59 which are higher than the minimum value required. Therefore, the statistical analysis demonstrates that this model can be efficiently applied to explain the effect of independent variables on acetic acid content of the developed vinegar (Table 3).
Effect of temperature, time and inoculum per cent on acetic acid concentration in liquid jaggery vinegar of Co 89003 sugarcane variety
The average acetic acid concentration of liquid
jaggery vinegar ranged from 0.41 to 3.73%. The lowest acetic acid concentration (0.41%) in vinegar was found in the experimental trial 17, whereas highest acetic acid (3.73%) was achieved in experimental trial 6 as shown in Table 2. The maximum acetic acid (3.73%) was observed at a temperature of 28.5°C, fermentation period of 12.5 days and 7.5% inoculum concentration (Co 89003), while minimum acetic acid (0.41%) was observed at 22.61°C temperature, 12.5 days fermentation period and 7.5% inoculum concentration (Table 2). The regression equation coefficients were calculated and the data were fitted to a second-order polynomial equation. Thus, to predict acetic acid per cent as affected by different factors which are represented in terms of their actual factors, a multiple regression equation was generated as shown below (Eq. 3):
Acetic acid (%) =
+3.70 + 0.44 *Temperature + 0.02 *Time+ 0.50 *Inoculum -0.11 *Temperature* Time + 0.12 *Temperature* Inoculum + 0.44 *Time *Inoculum - 0.89 *Temperature2-0.44* Time2-0.56* Inoculum2 …… (3)
The analysis of variance (ANOVA) depicted the acetic acid as a function of initial values of parameters. Table 3 shows the regression analysis of the data, in which the coefficient of determination (R
2) was found to be 0.987 indicating that the statistical model was significant and can explain the variability in the response. The model F value was found to be 85.02, which is more than the tabulated F value as indicated in the ANOVA of quadratic model. A minimum desirable adequate precision value (APV) of 4.00 is required for high prediction ability, where in the study it was found to be 26.05 which are higher than the minimum value required. Therefore, the statistical analysis demonstrates that this model can be efficiently applied to explain the effect of independent variables on acetic acid content of the developed vinegar.
A similar trend was observed for the regression coefficients and ANOVA of fitted quadratic model for acetic acid percent in liquid
jaggery vinegar of both the sugarcane varieties (CoH 160 and Co 89003). The coefficient estimate of the acetic acid model (Table 3) shows that the level of temperature and inoculum at linear terms had highly significant (p<0.01) effect and an increase in temperature and inoculum percent enhanced the acetic acid production in vinegar due to the greater bioconversion of the sugars into alcohol and acetic acid. Similar results were also depicted by
Saha and Banerjee, (2013) which have found that acetic acid concentration increased with an increase in an amount of inoculum percent. At 15 and 10% inoculum concentration, acetic acid concentration of 4.67% and 4.62% was observed.
Gullo et al. (2014) found that the optimum temperature for the wine vinegar production is 30°C whereas the growth of bacteria was inhibited if a temperature was above 35°C and below 8°C. In this study, an optimum temperature was observed at 28.5°C for the vinegar production at 7.5% inoculum level. However, non-significant effect of time was observed on the acetic acid response.
The squared terms of temperature, time and inoculum had negative highly significant effect (p<0.01), thus increasing any of these independent factors, decreased the acetic acid concentration in liquid
jaggery vinegar. Any of these factors alone, keeping others constant will affect the microbial metabolism in an inverse way. The interaction between the time and inoculum variables also had statistically significant effect (p<0.01) on acetic acid, thus a higher acetic acid concentration was observed when the fermentation period (time) was increased from 10 to 15 days and inoculum percent was increased from 5 to 10 per cent. A similar trend was observed by the
(Ghosh et al., 2012).
The interaction amongst variables and their effect on acetic acid per cent of vinegar is shown in the three dimensional graph (Fig 2). The acetic acid concentration achieved in the optimum liquid
jaggery vinegar prepared from CoH 160 and Co 89003 sugarcane varieties was found to be 3.99 and 3.73 per cent which is in accordance with the acetic acid content of 3.04 per cent as found out by the
Chen et al. (2015) in the sugarcane juice vinegar prepared from different yeasts and acetic acid bacteria. Also in both sugarcane varieties maximum acetic acid content in liquid
jaggery vinegar was observed at a temperature around 28.5
oC which is in agreement with
(Arifuzzaman et al., 2014) which found that all isolated
Acetobacter strains were able to grow at 25°C and 37°C but the most favourable temperature in which a higher potency in terms of acetic acid content was observed at 30°C. Similar observation was also reported by
Sharafi et al. (2010) where the acetic acid production was found to be optimum at temperature of 31°C. Optimisation of temperature is considered essential for any biotechnological process as the microbial inactivation and enzyme denaturation can occur above the optimum temperature.
The expected response of acetic acid and its correlation between the different independent variables are shown in three dimensional plots (Fig 2 and 3), with temperature on X-axis and time on Y-axis while inoculum percentage was kept (7.5%) constant at ‘O’ central level. With an increase in temperature, acetic acid concentration increases at first and then decreases. With an increase in the number of days, acetic acid concentration increases at first and then decreases.