量子化学计算白藜芦醇与芝麻酚在油脂中的抗氧化协同作用OACSTPCD
Quantum chemistry calculation of antioxidant synergistic effect of resveratrol and sesamol in oil
目的:研究白藜芦醇与芝麻酚间的抗氧化协同机理.方法:通过DPPH和氢过氧化物分别检测葵花子油中自由基和过氧自由基的含量变化,并结合诱导期的测定,优化组合白藜芦醇与芝麻酚二者比例,并采用量子化学计算模拟反应过程.结果:在180 ℃加热2 h,添加白藜芦醇与芝麻酚的葵花籽油中,总 自由基含量分别为(0.08±0.03),(0.20±0.03)mol/L,相比于空白[(0.44± 0.01)mol/L],白藜芦醇具有最佳抑制效率,且芝麻酚清除过氧自由基的能力最强.二者在纯化的葵花籽油中发生协同作用的最佳添加量为1 400,200 mg/kg,且在180 ℃降解速率下,白藜芦醇具有保护芝麻酚的作用.结论:利用量子化学的手段发现二者存在动态平衡的过程,由于白藜芦醇的添加量是芝麻酚的7倍,所以反应更倾向于白藜芦醇向芝麻酚自由基供H.
Objective:This study focused on the antioxidant synergistic mechanism between resveratrol and sesamol.Methods:The levels of free radicals and peroxide free radicals in sunflower seed oil were assessed using the 2,2-diphenyl-l-picrylhydrazyl(DPPH)and hydrogen peroxide assays,respectively.The proportion of resveratrol and sesamol were optimized by integrating the measurements with the determination of the induction period.Additionally,quantum chemical simulations were employed to elucidate the underlying reaction processes.Results:Upon heating sunflower seed oil supplemented with resveratrol and sesamol at 180 ℃ for 2 hours,the total content of free radicals was determined as(0.08± 0.03)mol/L and(0.20±0.03)mol/L,respectively,in comparison to(0.44+0.01)mol/L in the control sample.Resveratrol exhibited the highest inhibitory efficiency,while sesamol has the strongest scavenging ability of peroxide radicals.The optimal concentrations for their synergistic effect in purified sunflower seed oil were determined as 1 400,200 mg/kg,and resveratrol had protective effect on sesamol at the degradation rate of 180 ℃.Conclusion:By utilizing quantum chemical methods,it was found that a dynamic equilibrium process exists between the two compounds.As the amount of resveratrol added is seven times that of sesamol,and the reaction is more inclined to supply hydrogen to sesamol radicals by resveratrol.
高伟洪;曲潇笛;姚云平;李昌模
天津科技大学食品科学与工程学院,天津 300457
芝麻酚白藜芦醇自由基量子计算协同作用
sesamolresveratrolfree radicalquantum computationsynergistic effect
《食品与机械》 2024 (001)
11-16 / 6
国家重点研发计划(编号:2019YFC160620202)
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