Evaluation of Italian extra virgin olive oils based on the phenolic compounds composition using multivariate statistical methods

被引:0
作者
Jitka Klikarová
Lenka Česlová
Petra Kalendová
Paola Dugo
Luigi Mondello
Francesco Cacciola
机构
[1] University of Pardubice,Department of Analytical Chemistry, Faculty of Chemical Technology
[2] University of Messina,Department of Chemical, Biological, Pharmaceutical and Environmental Sciences
[3] University of Pardubice,Department of Inorganic Technology, Faculty of Chemical Technology
[4] University of Messina,Chromaleont S.R.L., c/o Department of Chemical, Biological, Pharmaceutical and Environmental Sciences
[5] University Campus Bio-Medico of Rome,Department of Sciences and Technologies for Human and Environment
[6] University of Messina,BeSep S.R.L., c/o Department of Chemical, Biological, Pharmaceutical and Environmental Sciences
[7] University of Messina,Department of Biomedical, Dental, Morphological and Functional Imaging Sciences
来源
European Food Research and Technology | 2020年 / 246卷
关键词
Extra virgin olive oils; Phenols; Factor analysis; Discriminant analysis; HPLC;
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学科分类号
摘要
The content of 40 phenolic compounds was determined in 68 samples of extra virgin olive oils (EVOOs) coming from 9 Italian regions using high-performance liquid chromatography coupled to diode array detector and mass spectrometry. Oleuropein isomers (M = 540 g/mol) and derivatives (M = 378 g/mol) together with ligstroside aglycone isomers (M = 362 g/mol) and derivatives (M = 394 g/mol) were the major EVOOs compounds (median of 44–228 mg/kg). On the other hand, verbascoside isomers (M = 624 g/mol) and apigenin (M = 270 g/mol) were the minor compounds (median < 2 mg/kg). Different techniques of multivariate data analysis were applied to find important parameters for discrimination of EVOOs. Principal component analysis and factor analysis distributed the samples into two groups according to the total amount of phenols and quantity of elenolic acid giving information about ripeness of olives. Linear discriminant analysis successfully classified the samples according to their geographical origin into three groups (Northern Italy, Southern Italy, and Sicily).
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页码:1241 / 1249
页数:8
相关论文
共 284 条
[1]  
Fiorini D(2018)undefined Food Res Int 105 65-75
[2]  
Boarelli MCh(2016)undefined Food Anal Method 9 712-723
[3]  
Conti P(2016)undefined Food Anal Method 9 1713-1718
[4]  
Alfei B(2014)undefined Food Anal Method 7 1824-1833
[5]  
Caprioli G(2005)undefined Electrophoresis 26 3538-3551
[6]  
Ricciutelli M(2016)undefined Food Chem 212 628-634
[7]  
Sagratini G(1998)undefined Biochem Biophys Res Commun 247 60-64
[8]  
Fedeli D(2017)undefined LWT Food Sci Technol 78 226-234
[9]  
Gabbianelli R(2010)undefined Food Chem 118 956-965
[10]  
Pacetti D(2016)undefined Food Anal Method 9 275-279