摘要
目的通过气味测定研究,快速识别不同产地枸杞子及气味差异物质。方法收集甘肃、内蒙古、宁夏、新疆及青海等5个产地枸杞子,利用超快速气相电子鼻对样品进行检测,建立气味指纹图谱,并利用AroChemBase数据库对13个共有气味峰进行指认。运用判别因子分析(Discriminant factor analysis,DFA)、卷积神经网络(Convolutional neural networks,CNN)判别模型、主成分分析(Principal component analysis,PCA)及偏最小二乘判别分析(Partial least squares discriminant analysis,PLS-DA)对所得数据进行处理,并通过变量权重重要性排序(Variable importance in projection,VIP)值作图筛选差异成分。结果不同产地枸杞子能区分开,气味色谱峰峰8(己醛)、峰9(糠醛)为5个产地枸杞子样品间的主要差异成分,己醛含量排序为:内蒙古>甘肃>宁夏>新疆>青海;糠醛含量排序为:甘肃>新疆>宁夏>青海>内蒙古。结论超快速气相电子鼻可较好分析枸杞子气味特征,并快速、准确识别差异物质,为不同产地枸杞子的用药选择和综合利用提供参考。
OBJECTIVE To identify origin-derived Lycium barbarum L.and its odor differential markers via detecting odors.METHODS The Lycium barbarum L.selected from five distinct origins(Gansu,Neimenggu,Ningxia,Xinjiang and Qinghai)was detected based on ultra-fast gas phase electronic nose,and the odor fingerprint was subsequently built.Thirteen shared odor peaks were identified through AroChemBase.The discriminant models of discriminant facor analysis(DFA),convolutional neural networks(CNN),principal component analysis(PCA)combined with partial least squares discriminant analysis(PLS-DA)were applied to analyze data.The differential components of distinct origin-derived Lycium barbarum L.were analyzed based on variable importance in projection(VIP).RESULTS The 56 batches of Lycium barbarum L.from distinct origins were distinguished.Besides,peak 8(hexanal)and peak 9(furfural)were found as the main differential components of the five distinct origin-derived Lycium barbarum L.through variable importance in projection(VIP).The content of hexanal was Neimenggu>Gansu>Ningxia>Xinjiang>Qinghai,and the content of furfural was Gansu>Xinjiang>Ningxia>Qinghai>Neimenggu.CONCLUSION This study found that the odor characteristic and differential markers of Lycium barbarum L.could be analyzed through Heracles NEO ultra-fast gas phase electronic nose,providing references for choosing and utilizing Lycium barbarum L.from different origins comprehensively.
作者
赵秋龙
江群艳
严辉
瞿城
郭盛
樊欢
包蓉蓉
何润天
康宏杰
段金廒
ZHAO Qiu-long;JIANG Qun-yan;YAN Hui;QU Cheng;GUO Sheng;FAN Huan;BAO Rong-rong;HE Run-tian;KANG Hong-jie;DUAN Jin-ao(National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine,Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization,State Administration of Traditional Chinese Medicine Key Laboratory of Chinese Medicine Resources Recycling Utilization,Nanjing University of Chinese Medicine,Nanjing 210023,China;Ningxia Innovation Center of Goji R&D,Yinchuan 750002,China)
出处
《南京中医药大学学报》
CAS
CSCD
北大核心
2023年第6期513-522,共10页
Journal of Nanjing University of Traditional Chinese Medicine
基金
宁夏重点研发计划东西部合作专项(2021BEF02010)
国家自然科学基金区域创新发展联合基金重点项目(U21A20408)
国家现代农业产业技术体系专项(CARS-21)
江苏省“333高层次人才培养工程”
江苏省高校“青蓝工程”资助项目。
关键词
枸杞子
超快速气相电子鼻
气味差异物质
判别因子分析
卷积神经网络
主成分分析
偏最小二乘判别分析
Lycium barbarum L.
ultra-fast gas phase electronic nose
odor differential markers
discriminant factor analysis
convolutional neural networks
principal component analysis
partial least squares discriminant analysis