Microbial production of acetoin is eco-friendly and inexpensive when compared with its synthetic methods of production. In the present findings, bioproduction of acetoin in a typical bioreactor was discussed with a view to ascertain the seemingly comparative advantage of bioreactor system over shake flask, and more importantly, to confirm that corn steep liquor can indeed adequately be used as a replacement for other organic nitrogen sources. Taguchi design was statistically used to optimized the fermentation process which resulted in a 3-fold increase in molar yield (83%) corresponding to a six-fold increase in acetoin concentration (63.43 g/L), as compared to a similar study conducted in a shake flask. Although agitation rate was observed to be the most controlling, the bioreactor may underperform at agitation rate greater than 300 rpm. The optimum parameters for acetoin production in this study were 300 rpm agitation, 1.5 slpm aeration, 2 days fermentation time, and pH 6.5. The results show that the commercial production of acetoin can be envisioned using a biological approach that may be of economic advantage.

This study designed, techno-economically analyzed and compared the heat-assisted extraction (HAE)- and ultrasound-assisted extraction (UAE)-technology-based processes (HAE-tBP and UAE-tBP) for the production of crude anthocyanins powder (CAnysP) from Hibiscus sabdariffa calyx (HSC) with the assistance of SuperPro Designer software. Both the base cases and industrial setups of 600 L extractor capacities for HAE- and UAE-tBPs were analyzed and compared. When building the process flowsheets, peculiarities of the technicalities of both HAE and UAE extractors were taken into consideration. Materials and energy demands, production costs and unit production cost (UPC) of CAnysP were the parameters used for process analysis. Uncertainty and sensitivity analyses were conducted for the process with least CAnysP UPC using Monte Carlo simulations in Oracle Crystal Ball software. The HAE-tBP recorded the highest number of batches of 5278 per annum. HSC of 15.551 kg was required to produce 7.433 and 10.022 kg/batch CAnysP by 600 L extractor setup of HAE- and UAE-tBPs, respectively. The UAE-tBP achieved lower CAnysP UPC (164.28 US$/kg) compared with HAE-tBP (176.31 US$/kg) with 80.08% certainty. Out of the variables considered for sensitivity analysis of UAE-tBP UPC, ultrasound treatment time contributed the highest (+62%), while anthocyanins recovery contributed the least (+0.2%) to the variance in UPC.

Bioethanol production has seen an increasing trend in research recently, with a focus on increasing its economic viability. The aim of this study is to develop a low-cost fermentation medium with a minimum of redundant nutritional supplements, thereby minimizing the costs associated with nutritional supplements and seed production. Corn steep liquor (CSL) in glucose fermentation by Saccharomyces Type 1 (ST1) strain and Anchor Instant Yeast (AIY), which are low-cost media, is used as a replacement for yeast extract (YE). The fermentation process parameters were optimized using artificial neural networks (ANN) and the response surface method (RSM). The study shows that for CSL, maximum average ethanol concentrations of 41.92 and 45.16 g/L, representing 82% and 88% of the theoretical yield, were obtained after 36 h of fermentation in a shake flask for ST1 and AIY, respectively. For YE, ethanol concentrations equivalent to 86% and 88% of theoretical yield were obtained with ST1 and AIY, respectively after 48 h. Although ANN better predicted the responses compared to RSM, optimum conditions were better predicted by RSM. This study shows that corn steep liquor is an inexpensive potential nutrient that may have significant cost implications for commercial ethanol production.

The drive for renewable energy as an alternative to fossil fuel is on the increase globally. Modeling a renewable energy process is crucial for increasing process monitoring and control of plant efficiency for the ultimate objective of optimal biorefinery operations. This study aims to develop and compare models that best predict the fermentation process parameters of bioethanol production using corn‐steep liquor (CSL) as a media supplement. The response surface method (RSM), artificial neural networks (ANNs) and adaptive neuro‐fuzzy inference system (ANFIS) were tested in the modeling of bioethanol fermentation processes. Box–Behnken design was used to investigate fermentation process parameters considering the effect of CSL (0.5–5.5 w/v), pH (4, 5), time (12–36 h), temperature (25–35°C) and inoculum size (0.5–5.5 v/v). The results from the kinetics study show media formulation with corn steep liquor results in a comparable yield with that substituted with yeast extract. The study shows that, for CSL, a maximum ethanol concentration of 17.40 g L⁻¹ was obtained after 48 h of fermentation while 21.53 g L⁻¹ was attained after 6 h for the media formulation with yeast extract. Based on the model evaluation using statistical error indices, ANN predictability was better at R² = 0.90; R = 0.95; SEP = 1.73. The ANN models described the process better than ANFIS and RSM. This study shows the intelligent predictive ability of ANN that could be useful for the scale‐up process of ethanol production in industry. © 2023 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.