Predicting the Production of Probiotic Biomass and Lactic Acid via Fuzzy Logic during the Anaerobic Treatment of Swine Waste (Sus domestica) with Lactobacillus acidophilus
Publication: Journal of Environmental Engineering
Volume 150, Issue 1
Abstract
The massive generation of pig manure significantly contributes to the emission of greenhouse gases; in addition, its poor disposal represents a serious risk to human and animal health. In recent years, the microbial fermentation process has become relevant because it is considered a circular bioeconomy strategy, guaranteeing the recovery of agro-industrial waste and waste management. In this work, the production of lactic acid and biomass was evaluated from an anaerobic bioconversion process of swine residues in the presence of L. acidophilus. A 5 L capacity reactor was used, and different stirring speeds were evaluated (100, 150, and 200 rpm). It was concluded that the highest production of lactic acid and biomass was 30.15 and , respectively, which were reached during the experiments carried out at 100 rpm. The biomass was analyzed to determine the content of carbohydrates, proteins, and cell count, which were , 17.16%, and , respectively. Finally, the fuzzy logic technique was applied, and response surface graphs were generated to determine the variables with the greatest impact on lactic acid and biomass generation.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
The authors are grateful for the support for the infrastructure use facilities of the Tecnológico Nacional de México Campus Orizaba. Estrada-García thanks the National Consejo Nacional de Ciencia y Tecnología (CONACyT) for the scholarship awarded for a master’s degree with CVU (scholarship holder) 1006558. Romero-Mota thanks CONACyT for the financial support to pursue a Ph.D. (engineering sciences) with CVU 608912. This research was supported by the Tecnológico Nacional de México (TecNM) through project 10199.21P.
Author contributions: Conceptualization, J.M.M.C; methodology, D.I.R.M, J.E.G, G.A.H.P., and A.A.A.L.; validation, D.I.R.M and J.E.G.; formal analysis, G.A.H.P., A.A.A.L., D.I.R.M, J.e.g., and J.M.M.C.; investigation, D.I.R.M and J.E.G.; resources, J.M.M.C; writing—original draft preparation, D.I.R.M, J.e.g., and J.M.M.C.; writing—review and editing, D.I.R.M, J.e.g., and J.M.M.C.; supervision, J.M.M.C. All authors have read and agreed to the published version of the manuscript.
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Published In
Journal of Environmental Engineering
Volume 150 • Issue 1 • January 2024
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Jul 2, 2023
Accepted: Aug 31, 2023
Published online: Oct 28, 2023
Published in print: Jan 1, 2024
Discussion open until: Mar 28, 2024
ASCE Technical Topics:
- Acids
- Agricultural wastes
- Anaerobic processes
- Artificial intelligence and machine learning
- Biological processes
- Biomass
- Chemical compounds
- Chemicals
- Chemistry
- Computer programming
- Computing in civil engineering
- Energy engineering
- Energy sources (by type)
- Environmental engineering
- Fuels
- Fuzzy logic
- Non-renewable energy
- Pollutants
- Renewable energy
- Waste management
- Waste treatment
- Wastes
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