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篇名
Simultaneous green extraction of tea saponins from Camellia oleifera leaf waste using deep eutectic solvents for potential animal feed and bioethanol applications
並列篇名
Simultaneous green extraction of tea saponins from Camellia oleifera leaf waste using deep eutectic solvents for potential animal feed and bioethanol applications
英文摘要
Saponins exhibit significant potential in animal feed applications due to their roles in enhancing nutrient absorption and providing antimicrobial properties. However, conventional extraction methods using organic solvents pose potential health risks. This study proposes a sustainable extraction approach using deep eutectic solvents (DESs), a green solvent, to recover saponins from Camellia oleifera leaf waste, a food industry byproduct. Choline chloride (ChCl) and lactic acid (Lac) are selected as DES components, with response surface methodology (RSM) and genetic algorithm (GA) employed for process optimization. RSM achieves a saponin yield of 249.87 mg/g (raw material) at a ChCl-Lac ratio of 1:4, solid content of 17.5%, and pretreatment temperature of 57°C, while GA yields 232.17 mg/g at a ChCl-Lac ratio of 1:1, solid content of 21.5%, and pretreatment temperature of 54°C. Both DES extraction outperforms ethanol-based extraction (157.76 mg/g). Fermentation of hydrolysates produces ethanol concentrations of 6.14 mg/mL (RSM) and 7.07 mg/mL (GA), with yields of 42.35% and 41.58%, respectively, based on initial reducing sugar content. Minimal inhibition from residual saponins confirms the compatibility of DES-based pretreatment with fermentation. These findings establish DES-based extraction as a sustainable and efficient method for saponin recovery, with strong potential for integration into biorefinery applications, including bioethanol production.
起訖頁 2-2
關鍵詞 BioethanolBiorefineryDeep eutectic solventsGenetic algorithmResponse surface methodologySaponin extraction.
刊名 國際應用科學與工程學刊  
期數 202506 (22:2期)
出版單位 朝陽科技大學理工學院
該期刊-上一篇 Development of microwave-assisted pyrolysis apparatus and some experiments on agricultural biomass wastes: cashew shells, bagasse, and dried algae
該期刊-下一篇 Streamflow prediction using machine learning approaches with different shared socioeconomic pathways (SSPs)
 

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