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A review on upcycling waste cooking oil into polyhydroxyalkanoates (bioplastic): A pathway for sustainable materialopen access

Authors
Bhatia, Shashi KantPatel, Anil KumarSaratale, Ganesh DattatrayaKumar, VinodYang, Yung-Hun
Issue Date
Sep-2025
Publisher
Elsevier B.V.
Keywords
Artificial intelligence; Biodegradable; Circular economy; Polyhydroxyalkanoates; Upcycling; Waste cooking oil
Citation
International Journal of Biological Macromolecules, v.322, pp 1 - 16
Pages
16
Indexed
SCIE
SCOPUS
Journal Title
International Journal of Biological Macromolecules
Volume
322
Start Page
1
End Page
16
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/59000
DOI
10.1016/j.ijbiomac.2025.146592
ISSN
0141-8130
1879-0003
Abstract
Waste cooking oil (WCO) improper disposal leads to water pollution, ecosystem disruption, and human health hazards. Various upcycling strategies have been explored, including conversion to biodiesel, surfactants, and biodegradable polymers. Converting WCO into polyhydroxyalkanoates (PHAs), biodegradable and biocompatible material, offers a sustainable solution aligned with circular economy principles. WCO usually requires minimal or no pretreatment and can be effectively used as a carbon source for microbial fermentation. Free fatty acids (FFAs) from WCO are readily metabolized by PHA producing bacteria such as Cupriavidus necator and Pseudomonas spp., enabling PHA accumulation ranging from 27 % to 96 % (w/w). Depending on the microbial strain and fermentation strategy, both short chain length (scl-PHA) and medium chain length (mcl-PHA) polymers with varied properties can be synthesized. The coproduction of other products, such as carotenoids and surfactants, may further improve the process economics. However, variability in the composition of various oils can cause inconsistent productivity and monomer distribution, highlighting the need for thorough feedstock characterization. Insights from recent studies highlight that oils rich in long chain unsaturated fatty acids (LC-UFA), such as rapeseed or canola oil, enable the highest biomass and PHA yields, while oils dominated by medium chain saturated fatty acids (MC-SFA) favor flexible mcl-PHAs but with lower productivity. Integrating artificial intelligence (AI) and machine learning could further improve predictive analysis, process control, and strain selection. This review emphasizes the importance of aligning feedstock composition, microbial selection, coproduction, and improved fermentation strategies to advance sustainable PHA production from WCO. © 2025 Elsevier B.V.
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College of Life Science and Biotechnology (식품바이오융합공학과)
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