Optimization of process parameters for bioethanol production from oil palm frond juice by Saccharomyces cerevisiae using response surface methodology as a tool

Abstract

The aim of this research was to investigate the effect of temperature, medium initial pH and rotation rate on the production of bioethanol from OPF juice without nutrient and nitrogen source supplementation using Saccharomyces cerevisiae Kyokai No. 7 (ATCC 26622). A five-level-three-factor central composite design (CCD) was employed in this study and the central point of each process variable was chosen based on the best condition obtained from the one-factor-at-time (OFAT) method. The parameters ranges were set as follows; medium initial pH (5-9), temperature (27.5-37.5°C) and rotation rate (80-120 rpm). Bioethanol and residual sugars concentration were determine using High Performance Liquid Chromatography (HPLC). The optimum conditions for bioethanol production from OPF juice were achieved at medium initial pH (6.62), rotation rate (96.51 rpm) and temperature (33.03°C). Based on the validation experiment, the optimum bioethanol yield was 0.50 ±0.02 g/g sugars and this value was in close agreement with the model prediction where the difference was only 4.17%. Under the optimal conditions, the bioethanol yield obtained was 47.06% higher compared with non-optimized condition. The promising yield obtained in this study suggests that OPF juice can be used as a renewable and complete fermentation feedstock for bioethanol production.

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“…Maximum bioethanol concentrations have been obtained under similar conditions (Betiku and Taiwo, 2015;Zani et al, 2019). However, the concentrations obtained were higher than those of Sivamani and Baskar (2018) and Dasgupta et al (2013), with 25.59 g/L and 17.44 g/L, respectively, after similar optimization experiments.…”

Fundamental Concepts and Recent Applications of Factorial Statistical Designs

“…According to reports, a Central Composite design was successfully used to optimize the parameters of a process that was used for the production of bioethanol by a yeast strain (ZANI et al, 2019). Other studies indicated that CCR designs were also effectively applied in the evaluation of performance and optimization of the parameters of an anaerobic codigestion of leachate and glycerol for renewable energy generation, and in the maximization of the phytoremediation process of an arsenic-contaminated water (DE SOUZA et al, 2019;TAKEDA et al, 2020).…”

Predictive Modeling of Bioenergy Production from Fountain Grass Using Gaussian Process Regression: Effect of Kernel Functions

“…In recent years, bioenergy production from various biomass sources has received a lot of attention, and perennial grasses have emerged as a potential source of biomass for biofuel production [1][2][3]. There is less competition for food crops when perennial plants are cultivated on land that is no longer suitable for agricultural use [4,5].…”