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Microalgae to Bioenergy: Optimization of Aurantiochytrium sp. Saccharification.

Joana OliveiraSara PardilhóJoana M DiasJosé C M Pires
Published in: Biology (2023)
Microalgae are a promising feedstock for bioethanol production, essentially due to their high growth rates and absence of lignin. Hydrolysis-where the monosaccharides are released for further fermentation-is considered a critical step, and its optimization is advised for each raw material. The present study focuses on the thermal acid hydrolysis (with sulfuric acid) of Aurantiochytrium sp. through a response surface methodology (RSM), studying the effect of acid concentration, hydrolysis time and biomass/acid ratio on both sugar concentration of the hydrolysate and biomass conversion yield. Preliminary studies allowed to establish the range of the variables to be optimized. The obtained models predicted a maximum sugar concentration (18.05 g/L; R 2 = 0.990) after 90 min of hydrolysis, using 15% ( w / v ) biomass/acid ratio and sulfuric acid at 3.5% ( v / v ), whereas the maximum conversion yield (12.86 g/100 g; R 2 = 0.876) was obtained using 9.3% ( w / v ) biomass/acid ratio, maintaining the other parameters. Model outputs indicate that the biomass/acid ratio and time are the most influential parameters on the sugar concentration and yield models, respectively. The study allowed to obtain a predictive model that is very well adjusted to the experimental data to find the best saccharification conditions for the Aurantiochytrium sp. microalgae.
Keyphrases
  • anaerobic digestion
  • wastewater treatment
  • machine learning
  • big data
  • ionic liquid
  • deep learning
  • lactic acid