论文部分内容阅读
目的:寻求色谱分离条件的优化策略以获得具有良好稳定性和重现性的中药指纹图谱。方法:以中药葛根为例,采用网格搜索算法分别对3种不同的梯度洗脱模式单线性梯度、多线性梯度以及混合梯度模式下的分离条件进行了优化,并比较了这3种模式分离的利弊。结果:混合梯度能较好地分离粉葛提取液中14个组分,且分析时间最短,但优化较复杂;单线性梯度需优化的参数最少,分析时间相对较长,且难分离物质对的分离度稍差;多线性梯度则介于两者之间。结论:对于复杂体系中组分的分离,首选单线性梯度,在分离效果达不到定性或定量分析要求时,可以在此基础上选择更为复杂的分离模式。
Objective: To seek an optimization strategy for chromatographic separation conditions to obtain Chinese herbal fingerprints with good stability and reproducibility. Methods: Taking Pueraria radix as an example, the grid search algorithm was used to optimize the separation conditions of three different gradient elution modes: single linear gradient, multi-linear gradient and mixed gradient mode. The three modes were compared. The pros and cons. RESULTS: The mixed gradient could better separate the 14 components in the extract of Pueraria lobata with the shortest analysis time, but the optimization was more complex. The single linear gradient had the least parameters to be optimized, the analysis time was relatively long, and the difficult to separate substances were The degree of separation is slightly poor; multi-linear gradients fall somewhere in between. Conclusion: For the separation of components in a complex system, single-linear gradients are preferred. When the separation effect cannot meet the requirements of qualitative or quantitative analysis, a more complex separation mode can be selected on this basis.