Statistical Optimization of Biohydrogen Production from Palm Oil Mill Effluent by Natural Microflora

Abstract

Abstract:In this study, palm oil mill effluent (POME) was used as the substrate for biohydrogen production. Heat-treated POME sludge acclimated with POME incubated at 37°C for 24 hours was used as seed culture. Preliminary screening on the effects of inocula sizes, heat treatment, substrate concentration and pH of incubation by using a factorial design (FD) were conducted under mesophilic condition (37°C) using a serum vial (160 mL). The experimental results from two-level FD showed that pH and Chemical Oxygen Demand (COD) of POME significantly affected biohydrogen production. Optimizations of the specific hydrogen production (P s ) and the hydrogen production rate (R m ) were achieved by using a central composite design (CCD). The maximum P s of 272 mL H 2 /g carbohydrate was obtained under optimum conditions of pH 5.75 and substrate concentration of 80 g/L. The maximum R m of 98 mL H 2 /h was calculated under the optimum conditions of pH 5.98 and substrate concentration of 80 g/L. The optimized conditions obtained were subjected to a confirmation run and it showed reproducible data with a P s of 226 mL H 2 /g carbohydrate and R m of 72 mL H 2 /h.

Optimization of high‐pressure processing in extraction of astaxanthin from Penaeus monodon carapace using response surface methodology

“…The significance of coefficients has been reported to be directly proportional to t value and inverse to p value (Akhnazorova & Katarao, ). Nonsignificant lack of fit indicates excellent due to implying the model fits the data (Rasdi et al, ). The model terms are significant if the Prob.…”

Evaluation of Factors Affecting Polyhydroxyalkanoates Production by Comamonas sp. EB172 Using Central Composite Design

“…The two-level factorial design is a tool for this initial screening since it is possible to determine the influence of the multivariable factors and lessen the number of experiments (Rasdi et al 2009). The variables tested were temperature, initial medium pH, inoculum size, concentration of (NH4)2SO4 and concentration of mixed organic acids.…”

“…EB172 was affected by all the factors except for (NH4)2SO4 concentration since the P-value for the (NH4)2SO4 concentration was 0.1630 which was greater than 0.05. In two level factorial design, an independent variable with pvalue >0.05 can be taken as being not significant (Rasdi et al 2009) and hence, it can be eliminated. However, PHA production was influence by (NH4)2SO4 concentration as shown by analysis of variance with Pvalue of 0.02.…”

“…Preliminary screening was done by two-level factorial method. Two-level factorial design was used since it is possible to determine the influence of the multivariable factors and lessen the number of experiments by this method (Rasdi et al 2009). Subsequently, the significant factors were optimized by using CCD whereby the experimental results were fitted with a second order polynomial equation in order to correlate the response variables to the independent variables.…”