摘要
采用静态顶空(Headspace,HS)联合气相色谱-质谱联用技术(Gas Chromatography-Mass Spectrometry,GC-MS)对陕西、山东、四川、甘肃4个省份共45个产地花椒的挥发性风味物质进行检测。利用自动质谱退卷积定性系统(AMDIS)结合Kováts保留指数(RI)分析,共得到99种挥发性风味物质。产自陕西、甘肃、山东和四川省的花椒分别鉴定出79、69、68和63种挥发性组分。建立多种数学模型进行产地鉴别,其中正交偏最小二乘法(Orthogonal partial least squares,OPLS-DA)模型能准确区分4个省份的花椒样品,模型拟合参数Q2为0.84,6种关键性差异物质(VIP>2)分别是胡椒酮、蒎烯、萜品烯、3-蒈烯、罗勒烯和α-水芹烯。进一步应用GC-MS全谱数据结合随机森林(Random Forest,RF)模型进行产地鉴别,可以成功区分产自陕西、甘肃、山东和四川省的花椒,准确率为100%。
The static headspace(HS) combined with gas chromatography-mass spectrometry(GC-MS) was used to analyze the volatile flavor compounds of Zanthoxylum bungeanum from 45 producing areas in Shanxi, Shandong, Sichuan and Gansu. Using automatic mass spectrometry deconvolution qualitative system(AMDIS) and Kováts Retention index(RI)analysis, a total of 99 volatile compounds were obtained. 79, 69, 68 and 63 volatile compounds were identified in Zanthoxylum bungeanum from Shanxi, Gansu, Shandong and Sichuan province. A variety of mathematical models were established to identify the origin. Among them, the Orthogonal partial least squares(OPLS-DA) model could accurately distinguish Zanthoxylum bungeanum samples from 4 provinces, the model fitting parameter Q2 was 0.84, and the 6 key difference substances(VIP>2) were piperonone, pinene, terpinene, 3-carene, ocirene and α-phellandrene. Further application of GC-MS full-spectrum data combined with Random Forest(RF) model for origin identification could successfully distinguish Zanthoxylum bungeanum from Shanxi, Gansu, Shandong and Sichuan provinces, with an accuracy rate of 100%.
作者
李亚南
崔传坚
陈江琳
运晶
金龙
侯如燕
LI Yanan;CUI Chuanjian;CHEN Jianglin;YUN Jing;JIN Long;HOU Ruyan(School of Tea and Food Science&Technology,Anhui Agricultural University,Hefei 230031,China;State Key Laboratory of Tea Plant Biology and Utilization,Anhui Agricultural University,Hefei 230031,China;Qiaqia Food Co.,Ltd.,Hefei 230601,China)
出处
《食品工业科技》
CAS
北大核心
2022年第2期293-303,共11页
Science and Technology of Food Industry
基金
洽洽食品股份有限公司资助(2019)。
