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Updated: Sep 12, 2025

Scalable Step-by-Step Approach of Sustainable Bioplastic Production from Food Waste
Published on: July 18, 2025
A review on upcycling waste cooking oil into polyhydroxyalkanoates (bioplastic): A pathway for sustainable material
Shashi Kant Bhatia1, Anil Kumar Patel2, Ganesh Dattatraya Saratale3
1Advanced Material Program, Department of Biological Engineering, College of Engineering, Konkuk University, Seoul 05029, Republic of Korea; Institute for Ubiquitous Information Technology and Applications, Seoul 05029, Republic of Korea.
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.
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