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篇名
Enhanced co-production of biopolymer polyhydroxybutyrate (PHB) and biopigment (carotenoid) through wild Bacillus chungangensis by utilizing agro-waste substrates
並列篇名
Enhanced co-production of biopolymer polyhydroxybutyrate (PHB) and biopigment (carotenoid) through wild Bacillus chungangensis by utilizing agro-waste substrates
英文摘要
The biopolymer polyhydroxybutyrate (PHB) and biopigment carotenoid produced by microbes holds significant industrial and environmental potential. This research aimed at isolating pigmented bacteria from the Western Ghats of Tamil Nadu, India, which effectively co-produced PHB, adding novelty to the study. The orange pigmented bacterium was further screened for PHB synthesis by Sudan Black B staining. Subsequent 16S rRNA gene sequencing identified the positive isolate as Bacillus chungangensis. The isolate exhibited optimal performance at a pH of 10, a temperature of 45°C, and a salinity of 6%, confirming its extremophilic nature. The isolate achieved cost-effective biopolymer and biopigment production by leveraging agro-waste substrates like sugarcane bagasse, groundnut shell, and coconut oil cake. Notably, sugarcane bagasse yielded a remarkable 63% PHB yield and groundnut shell yielded more biopigment, 4.89 g/L surpassing other waste substrates and control. The biopigment exhibitedλmax at 450 nm and the FTIR studies confirmed the carotenoid nature of biopigment. Fourier transform infrared (FTIR) analysis of extracted biopolymer from fermented samples of these substrates exhibited a C=O stretch at 1635.64/cm and 1627.92/cm, confirming the presence of polyhydroxybutyrates. This study unveils the potential of Bacillus chungangensis for sustainable PHB synthesis with biopigment carotenoid as a co-product by utilizing agro-waste substrates and contributing to ecofriendly biopigment and biopolymer.
起訖頁 1-13
關鍵詞 Polyhydroxybutyrate (PHB)Agro-wasteBiopigmentsBiopolymerBacillusEcofriendlyCo-productionCarotenoid
刊名 國際應用科學與工程學刊  
期數 202406 (21:2期)
出版單位 朝陽科技大學理工學院
該期刊-上一篇 Improving service quality through classifying chatbot messages based on natural language processing: A bidirectional long short-term memory network model
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