Prediction of influence of stepwise increment of initial acetic acid concentration in charging medium on acetification rate of semi-continuous process by artificial neural network

Based on industrial vinegar production, ethanol concentration in charging medium is normally considered as a strong variable influencing the acetification for a given initial acetic acid concentration. Moreover, high initial acetic acid concentration is considered when higher than 100 g L⁻¹ of acetic acid as finished product is obtained. This study assessed the effect of a stepwise increment of initial acetic acid concentration in fermentation medium of 45, 55, and 65 g L⁻¹ after charging at constant ethanol concentration of 35 g L⁻¹ on acetification rate (ETA) by high acid-tolerant strain of Acetobacter aceti WK. Average ETA was 8.144 + 0.09 g L⁻¹ d⁻¹ at 45 g L⁻¹ and 8.655 + 0.09 g L⁻¹ d⁻¹ at 55 g L⁻¹, and significant decreased to 6.819 + 0.23 g L⁻¹ d⁻¹ at 65 g L⁻¹. An artificial neural network (ANN) model was applied to predict the ETA in semi-continuous acetification under the conditions of the study. The optimized ANN structure was revealed to contain two hidden layers and seven neurons per layer. The experimental acetification correlated to the predicted data with R² of training and testing data set of 0.858 and validation data set of 0.831, respectively. Results indicated that the inputs as acetic acid and ethanol concentrations successfully predicted the ETA of semi-continuous acetification process.     

Lipase from Penicillium camembertii KCCM 11268: Optimization of solid state fermentation and application to biodiesel production

Lipase was produced by Penicillium camembertii KCCM 11268 under solid state fermentation (SSF), and the production process was optimized by using statistical experimental designs. The initial moisture content, cultivation time, inoculum size and concentration of basal medium were considered as the factors of optimum conditions for SSF. P. Camembertii KCCM 11268 was cultivated in SSF using wheat bran as the substrate for lipase production. Under the optimized condition, lipase activity was reached around 7.8 U/ml after eight days fermentation. To partially purify the lipase, ammonium sulfate (80% saturation) was added to the crude lipase solution and concentrated using a diafiltration (VIVAFLOW 50). The concentrated lipase solution from P. Camembertii KCCM 11268 (PCL) was immobilized on silica gel by cross-linking method. Also, PCL was mixed with a commercial lipase solution from Candida rugosa (CRL), and this mixture was co-immobilized on silica gel. The immobilized and co-immobilized lipase activities were 1150.1 and 7924.8 U/g matrix, respectively. Palm oil and methanol were used as substrates and 1mmol of methanol was added every 1.5 h and 2 times during biodiesel production. The reaction was carried out at temperatures of 30, 40, 50, 60 and 70 °C. The maximum biodiesel conversion by co-immobilized lipase was 99% after 5 h at 50 °C.     

Butanol and ethanol production from tapioca starch wastewater by Clostridium spp

Total (TWW) and tapioca starch wash wastewater (TSWW) from a cassava processing plant in Thailand were analyzed for their composition with a view to evaluate their potential as substrates for solvent production by ABE fermentation with Clostridium spp. Starch was detected at a 1.63-fold higher level in the TWW than that in the TSWW (24.4% and 15.0% (w/w), respectively). The chemical oxygen demand (COD) was broadly similar (20,093 and 20,433 mg/L), but the biological oxygen demand (BOD) was 1.84-fold higher (18,000 and 9,750 mg/L) in the TWW than that in the TSWW. Thus, the TSWW was selected as a substrate to evaluate its potential for butanol and ethanol production by two Clostridium spp. The combined ethanol plus butanol production in the TSWW at pH 6.5 was higher than that at pH 4.5, being around 27.8- and 3.4-fold higher in C. butyricum TISTR 1032 and C. acetobutylicum ATCC 824, respectively. In both strains, the butanol (and combined butanol plus ethanol) production level was improved at pH 5.5. The addition of yeast extract increased the bacterial cell production, but did not significantly improve solvent productivity in C. acetobutylicum, and even decreased butanol production by C. butyricum.