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首页> 外文期刊>Food Chemistry >Application of an advanced and wide scope non-target screening workflow with LC-ESI-QTOF-MS and chemometrics for the classification of the Greek olive oil varieties
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Application of an advanced and wide scope non-target screening workflow with LC-ESI-QTOF-MS and chemometrics for the classification of the Greek olive oil varieties

机译:具有LC-ESI-QTOF-MS和化学计量学的先进,广泛范围的非目标筛选工作流程在希腊橄榄油品种分类中的应用

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摘要

An optimized and validated LC-ESI-QTOF-MS method with an integrated non-target screening workflow was applied in the investigation of the metabolomic profile of 51 Greek monovarietal extra virgin olive oils (EVOOs) from the varieties: Manaki, Ladoelia, Koroneiki, Amfissis, Chalkidikis and Kolovi. Data processing was carried out with the R language and XCMS package. A local database consisting of 1608 compounds naturally occurring in different organs of Olea Europa L. was compiled in order to accelerate the identification workflow. The preliminary examination of the distribution of EVOOs toward their cultivars was achieved by Principal Component Analysis (PCA). Ant Colony Optimization-Random Forest (ACO-RF) was developed to prioritize over 250 features and to establish a classification tree. Apigenin, vanillic acid, luteolin 7-methyl ether and oleocanthal were suggested as the markers responsible for the classification of Greek EVOOs' cultivars.
机译:经过优化和验证的具有集成非目标筛选工作流程的LC-ESI-QTOF-MS方法被用于研究以下品种的51种希腊单品种特级初榨橄榄油(EVOOs)的代谢组学谱: Amfissis,哈尔基迪基斯和科洛维。数据处理使用R语言和XCMS软件包进行。为了加快鉴定工作流程,编制了一个本地数据库,该数据库由自然存在于欧洲油橄榄的不同器官中的1608种化合物组成。通过主成分分析(PCA)初步评估了EVOOs向其品种的分布。蚁群优化随机森林(ACO-RF)的开发旨在优先考虑250多个特征并建立分类树。芹菜素,香草酸,木犀草素7-甲基醚和油橄榄素被认为是对希腊EVOOs品种进行分类的标记。

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