Economic Feasibility of Soybean Oil Production by Enzyme-Assisted Aqueous Extraction Processing View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03

AUTHORS

Ming-Hsun Cheng, Kurt A. Rosentrater, Jasreen Sekhon, Tong Wang, Stephanie Jung, Lawrence A. Johnson

ABSTRACT

Aqueous oil extraction is an approach that could replace organic solvent extraction with water. Compared to typical solvent extraction and mechanical pressing processes, aqueous extraction has higher oil recovery (over 80%) than the mechanical pressing process, and resolve issues resulted from chemical loading and remaining in the hexane extraction. Proteases are used to assist free oil release from oil bodies by hydrolyzing cotyledon cell walls in aqueous extraction process. The resulting enzyme-assisted aqueous extraction process (EAEP) includes dehulling, flaking, extruding, enzymatic extraction, and enzymatic demulsification processes. SuperPro Designer was used to conduct a techno-economic analysis (TEA) of the extraction process. The total capital investment, operation cost, and profits were evaluated. During EAEP, insolubility of water and oil allows the simultaneous extraction of protein and oil. This decreases operation costs, especially the oil purification process, and therefore increases profits made from the main product (soybean oil). This simultaneous extraction also increases the profit towards the coproduct, i.e., protein in skim. Additionally, the absence of chemical and enzyme recycling contribute to the better economic value of EAEP. Despite the increase in facility costs due to extraction and demulsification units, the value-added coproduct extraction and high free oil yield contribute to the economic feasibility of EAEP in industrial- and commercial-scale productions when skim and insoluble fiber are used as water and carbohydrate supplies for integrated soy/corn ethanol biorefinery processing. More... »

PAGES

539-550

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11947-018-2228-9

DOI

http://dx.doi.org/10.1007/s11947-018-2228-9

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https://app.dimensions.ai/details/publication/pub.1111403722


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