HPLC-MS/MS测定保健食品中6种大麻素
Determination of six Cannabinoid in health food by HPLC-MS/MS
侯巧红 1张勋 2赵宇 3齐鹤鸣 4李孟璇 5步献功 5董昕 2李燕鹭 2宋清莲 2邹明强 6金明华 5胡婷婷2
作者信息
- 1. 吉林大学公共卫生学院,吉林长春 130021;长春海关技术中心,吉林长春 130062
- 2. 长春海关技术中心,吉林长春 130062
- 3. 吉林省体育科学研究所(吉林省反兴奋剂中心),吉林长春 130000
- 4. 中国海关科学技术研究中心,北京 100026
- 5. 吉林大学公共卫生学院,吉林长春 130021
- 6. 中国检验检疫科学研究院,北京 100176
- 折叠
摘要
目的:利用高效液相色谱-串联三重四极杆质谱(HPLC-MS/MS)对保健食品中 6种大麻素进行定性定量分析.方法:HLB固相萃取小柱净化,采用XBridge C18色谱柱,乙腈溶液作为有机相,10mmol·L-1乙酸铵水溶液作为水相,2种离子模式同时扫描,同位素内标定量.结果:所测大麻素在 1-100μg·L-1浓度范围均呈现良好线性关系,相关系数(r2)均＞0.999.方法的检出限和定量限分别为 5μg·kg-1和 10μg·kg-1.该方法稳定性好,灵敏度高,适用于常见保健食品中 6 种大麻素的定性定量分析.结论:本研究成功建立了保健食品中 6 种大麻素的定性定量分析,为保健食品品质评价、安全监管及风险防范提供技术支持.
Abstract
Objective:Qualitative and quantitative analysis of six cannabinoids in health food using high-performance liquid chromatography tandem triple quadrupole mass spectrometry(HPLC-MS/MS).Methods:HLB solid phase extraction column purification,using XBridge C18 chromatography column,with acetonitrile solution as the organic phase and 10 mmol·L-1 ammonium acetate aqueous solution as the aqueous phase.Two ions modes were scanned simultaneously and isotope internal standard quantification was performed.Results:The measured Cannabinoids between 1-100μg·L-1 concentration range shows a good linear relationship,and the correlation coefficients(r2)is greater than 0.999.The detection limit and quantification limit of the method are 5 μg·kg-1 and 10 μg·kg-1.The method has good stability and high sensitivity,and is suitable for qualitative and quantitative analysis of six Cannabinoid in common health products.Conclusion:This study successfully established established a qualitative and quantitative analysis of six cannabinoids in health food,providing technical support for quality evaluation,safety supervision,and risk prevention of health food.
关键词
大麻素/保健食品/高效液相色谱-串联质谱Key words
Cannabinoids/Health food/High performance liquid chromatography-tandem mass spectrometry引用本文复制引用
基金项目
海关总署科研项目(2020HK182)
海南省重点研发计划(ZDYF2021SHFZ069)
吉林省科技发展计划重点研发项目(20210203045SF)
中国海关科学技术研究中心研课题(2023HX07)
出版年
2024
国家科技期刊平台
NSTL
万方数据