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SUSTAINABLE SQUALENE SYNTHESIS: ETHANOLYSIS OPTIMIZATION OF GMELINA ARBOREA LEAF BIOMASS USING RESPONSE SURFACE METHODOLOGY

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Squalene is a high-value triterpene widely utilized in pharmaceutical formulations, vaccine adjuvants, nutraceuticals, cosmetics, and specialty industrial applications. Growing environmental concerns associated with shark-derived squalene have intensified the search for sustainable, plant-based, and biomass-derived alternatives. This study investigates the potential of Gmelina arborea leaf biomass as a renewable feedstock for squalene production using a green ethanolysis approach under mild thermal conditions. A Box-Behnken Response Surface Methodology (RSM) was employed to evaluate the effects and interactions of temperature (40-60 °C), reaction time (40-60 min), and Ca(OH)2 catalyst loading (1-2%) on squalene yield. Seventeen experimental runs were conducted, and products were analyzed using GC-MS after derivatization with TMSH and TEA. The results revealed that catalyst loading was the most significant linear factor (p = 0.0083), while reaction time exhibited a notable quadratic effect (p = 0.0347). The quadratic model was statistically significant (F = 4.12; p = 0.0377) with an R² of 0.841, indicating strong predictive capacity. The highest squalene yield of 123.7 mg/g was obtained at 50 °C, 40 min, and 2% catalyst loading, confirming the effectiveness of ethanolysis as a greener alternative to methanolysis, which had previously yielded 171.98 mg/g under harsher conditions (90 oC). Significant variability among center-point runs highlighted the sensitivity of the process to catalyst concentration and thermal conditions. Overall, this study provides the first optimized ethanolysis pathway for producing squalene from Gmelina arborea leaves, demonstrating a sustainable, efficient, and environmentally compatible route for renewable squalene synthesis. The findings offer strong potential for scale-up and integration into biomass valorization and green chemical production systems.
Title: SUSTAINABLE SQUALENE SYNTHESIS: ETHANOLYSIS OPTIMIZATION OF GMELINA ARBOREA LEAF BIOMASS USING RESPONSE SURFACE METHODOLOGY
Description:
Squalene is a high-value triterpene widely utilized in pharmaceutical formulations, vaccine adjuvants, nutraceuticals, cosmetics, and specialty industrial applications.
Growing environmental concerns associated with shark-derived squalene have intensified the search for sustainable, plant-based, and biomass-derived alternatives.
This study investigates the potential of Gmelina arborea leaf biomass as a renewable feedstock for squalene production using a green ethanolysis approach under mild thermal conditions.
A Box-Behnken Response Surface Methodology (RSM) was employed to evaluate the effects and interactions of temperature (40-60 °C), reaction time (40-60 min), and Ca(OH)2 catalyst loading (1-2%) on squalene yield.
Seventeen experimental runs were conducted, and products were analyzed using GC-MS after derivatization with TMSH and TEA.
The results revealed that catalyst loading was the most significant linear factor (p = 0.
0083), while reaction time exhibited a notable quadratic effect (p = 0.
0347).
The quadratic model was statistically significant (F = 4.
12; p = 0.
0377) with an R² of 0.
841, indicating strong predictive capacity.
The highest squalene yield of 123.
7 mg/g was obtained at 50 °C, 40 min, and 2% catalyst loading, confirming the effectiveness of ethanolysis as a greener alternative to methanolysis, which had previously yielded 171.
98 mg/g under harsher conditions (90 oC).
Significant variability among center-point runs highlighted the sensitivity of the process to catalyst concentration and thermal conditions.
Overall, this study provides the first optimized ethanolysis pathway for producing squalene from Gmelina arborea leaves, demonstrating a sustainable, efficient, and environmentally compatible route for renewable squalene synthesis.
The findings offer strong potential for scale-up and integration into biomass valorization and green chemical production systems.

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