挥发性化合物含量结合化学计量学用于建立江西烤烟的产地鉴别模型
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摘要
利用自动化静态顶空-气相色谱-质谱联用技术对江西三大产烟区(赣州、抚州、吉安)共120个烤烟样品进行了检测,匹配并定量了54个挥发性化合物。采用遗传算法(GA,Genetic algorithm)选择其中18种代表性化合物,并利用主成分分析法(PCA,Principal component analysis)对这120个烤烟样品进行产地分类,发现这种模式识别(Pattern recognition)方法可将烤烟样品基本分为3类:A类主体为赣州样品(兴国、宁都除外);B类主体为抚州样品(外加兴国、宁都,宜黄、崇仁除外);C类主体为吉安样品(外加宜黄、崇仁)。随后,我们将样品按照2:1的比例分为验证集和预报集,用有监督模式识别方法径向基函数-神经网络(Radial basis function-neural network,RBF-NN)对样品产地进行预报,正确率达到92.5%。据此,我们建立了用于江西烤烟样品的产地鉴别模型,该模型可用于研究不同产地间挥发性化合物含量的分布规律,为划分不同产地烤烟香型风格提供依据,实现对烟叶的质量控制。
In this paper,54 volatile compounds in a total of 120 flue-cured tobacco samples from three major tobacco-producing areas(Ganzhou,Fuzhou and Ji'an) in Jiangxi province were identified and quantified by automatic static headspace-gas chromatography-mass spectrometry(HS-GC-MS).18 compounds were selected by genetic algorithm(GA) for performing principal component analysis(PCA) on these 120 flue-cured tobacco samples,and all the samples could be classified into three classes:Class A are samples from Ganzhou excluding Xingguo and Ningdu counties;Class B are samples from Fuzhou plus Xingguo and Ningdu counties,minis Yihuang and Chongren counties;Class C are samples from Ji'an in addition of Yihuang and Chongren counties.Subsequently,we divided the samples into a calibration set and a prediction set according to the ratio of 2:1,Radial basis function-neural network(RBF-NN) was used to predict the origin of samples in prediction set with a correct rate of 92.5%.Thus we established a model for the identification of the origin of the flue-cured tobacco samples in Jiangxi,with can be used to study the content regulation of volatile compounds and provide a basis for dividing the flavor pattern of flue-cured tobacco from different areas,which can achieve the quality control of tobacco.
In this paper,54 volatile compounds in a total of 120 flue-cured tobacco samples from three major tobacco-producing areas(Ganzhou,Fuzhou and Ji'an) in Jiangxi province were identified and quantified by automatic static headspace-gas chromatography-mass spectrometry(HS-GC-MS).18 compounds were selected by genetic algorithm(GA) for performing principal component analysis(PCA) on these 120 flue-cured tobacco samples,and all the samples could be classified into three classes:Class A are samples from Ganzhou excluding Xingguo and Ningdu counties;Class B are samples from Fuzhou plus Xingguo and Ningdu counties,minis Yihuang and Chongren counties;Class C are samples from Ji'an in addition of Yihuang and Chongren counties.Subsequently,we divided the samples into a calibration set and a prediction set according to the ratio of 2:1,Radial basis function-neural network(RBF-NN) was used to predict the origin of samples in prediction set with a correct rate of 92.5%.Thus we established a model for the identification of the origin of the flue-cured tobacco samples in Jiangxi,with can be used to study the content regulation of volatile compounds and provide a basis for dividing the flavor pattern of flue-cured tobacco from different areas,which can achieve the quality control of tobacco.
引文
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[19] NEKOEI M.Genetic algorithm based wavelengths selection coupled with partial least squares for simultaneous spectrophotometric determination of phosphate and silicate in detergent products[J].Current Analytical Chemistry,2018,14(2):151-158.
[20] 杜一平,潘铁英,张玉兰.化学计量学应用[M].北京:化学工业出版社,2008.
[2] WANG H M,LIU H Y,GUO B,et al.A novel poly(NMA-co-DEA-co-EDMA) monolithic column as a sorbent for online solid-phaseextraction and its application in the determination of beta-sitosterol in plant oil samples[J].Food Chemistry,2019,278:594-600.
[3] JIANG H,HU X R,LI Y,et al.Large-pore ordered mesoporous carbon as solid-phase microextraction coating for analysis of polycyclic aromatic hydrocarbons from aqueous media[J].Talanta,2019,195:647-654.
[4] BAJER T,SURMOVA S,EISNER A,et al.Use of simultaneous distillation-extraction,supercritical fluid extraction and solid-phase microextraction for characterisation of the volatile profile of Dipteryx odorata(Aubl.) Willd[J].Industrial Crops and Products.2018,119:313-321.
[5] DARAEE A,GHOREISHI S M,HEDAYATI A,et al.Supercritical CO2 extraction of chlorogenic acid from sunflower(Helianthus annuus) seed kernels:modeling and optimization by response surface methodology[J].Industrial Crops and Products,2019,144:19-27.
[6] 杨承清,雷凌华,夏更寿等.利用气质联用技术研究不同方法提取的黄心夜合鲜叶挥发油成分[J].南昌大学学报(理科版),2018,42(1):51-58.
[7] TSACHAKI M,LINFORTH R S T,TAYLOR A J.Dynamic headspace analysis of the release of volatile organic compounds from ethanolic systems by direct APCI-MS[J].Journal of Agricultural and Food Chemistry,2005,53(21):8328-8333.
[8] BICCHI C,CORDERO C,LIBERTO E,et al.Automated headspace solid-phase dynamic extraction to analyse the volatile fraction of food matrices[J].Journal of Chromatography A,2004,1024(1-2):217-226.
[9] CAMELEYRE M,LYTRA G,BARBE J C.Static Headspace analysis using low-pressure gas chromatography and mass spectrometry,application to determining multiple partition coefficients:a practical tool for understanding red wine fruity volatile perception and the sensory impact of higher alcohols[J].Analytical Chemistry,2018,90(18):10812-10818.
[10] VARONA-TORRES E,CARLTON D D,HILDENBRAND Z L,et al.Matrix-effect-free determination of BTEX in variable soil compositions using room temperature ionic liquid co-solvents in static headspace gas chromatography mass spectrometry[J].Analytica Chimica Acta.2018,1021:41-50.
[11] 江勇,袁美兰,赵利等.啤酒中挥发性成分的测定及产地鉴别[J].南昌大学学报(理科版),2014,38(5):472-476.
[12] 周秀锦,杨会成,邵宏宏等.HS/GC-MS/MS法检测海产品中二甲苯[J].分析测试学报,2018,37(7):844-848.
[13] JIA W,WANG H,SHI L,et al.High-throughput foodomics strategy for screening flavor components in dairy products using multiple mass spectrometry[J].Food Chemistry,2019,279:1-11.
[14] CRUSE C A,GOODPASTER J V.Generating highly specific spectra and identifying thermal decomposition products via Gas Chromatography / Vacuum Ultraviolet Spectroscopy(GC/VUV):Application to nitrate ester explosives[J].Talanta,2019,195:580-586.
[15] 倪永年.化学计量学在分析化学中的应用[M].北京:科学出版社,2004:2-3.
[16] YC/T 31-1996 烟草及烟草制品试样的制备和水分测定烘箱法[S].
[17] 谢剑平.烟草与烟气化学成分[M].北京:化学工业出版社,2010.
[18] NI Y N,SONG R M,KOKOT S.Discrimination of Radix Isatidis and Rhizoma et Radix Baphicacanthis Cusia samples by near infrared spectroscopy with the aid of chemometrics[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy,2012,96:252-258.
[19] NEKOEI M.Genetic algorithm based wavelengths selection coupled with partial least squares for simultaneous spectrophotometric determination of phosphate and silicate in detergent products[J].Current Analytical Chemistry,2018,14(2):151-158.
[20] 杜一平,潘铁英,张玉兰.化学计量学应用[M].北京:化学工业出版社,2008.