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基于高效薄层色谱和多变量统计分析的依兰依兰精油的自由基清除活性和代谢组学研究。

Radical scavenging activity and metabolomic profiling study of ylang-ylang essential oils based on high-performance thin-layer chromatography and multivariate statistical analysis.

机构信息

Australian Centre for Research on Separation Science (ACROSS), School of Natural Sciences, University of Tasmania, Hobart, TAS, Australia; ARC Industrial Transformation Research Hub for Processing Advanced Lignocellulosics Products (PALs), School of Natural Sciences, University of Tasmania, Hobart, TAS, Australia.

Australian Centre for Research on Separation Science (ACROSS), School of Natural Sciences, University of Tasmania, Hobart, TAS, Australia.

出版信息

J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Aug 1;1179:122861. doi: 10.1016/j.jchromb.2021.122861. Epub 2021 Jul 15.

Abstract

Ylang-ylang (YY) essential oil (EO) is distilled from the fresh-mature flowers of the Annonaceae family tropical tree Cananga odorata [Lam.] Hook. f. & Thomson, and is widely used in perfume and cosmetic industries for its fragrant character. Herein, two different metabolomic profiles obtained using high-performance thin-layer chromatography (HPTLC), applying different stains, namely 2,2-diphenyl-1-picrylhydrazyl (DPPH·) and p-anisaldehyde, were used for discrimination of 52 YY samples across geographical origins and distillation grades. The first profile is developed using the DPPH· stain based on the radical scavenging activity (RSA) of YY EOs. Results of the HPTLC-DPPH· assay confirmed that RSA of YY EOs is in proportion to the length of distillation times. Major components contributing to the RSA of YY EOs were tentatively identified as germacrene D and α-farnesene, eugenol and linalool, by gas chromatography-mass spectrometry (GC-MS) and GC-flame ionisation detector (GC-FID). The second profile was developed using the general-purpose p-anisaldehyde stain based on the general chemical composition of YY EOs. Untargeted metabolomic discrimination of YY EOs from different geographical origins was performed based on the HPTLC-p-anisaldehyde profiles, followed by principal component analysis (PCA). A discrimination and prediction model for identification of YY distillation grade was developed using PCA and partial least squares regression (PLS) based on binned HPTLC-ultraviolet (254 nm) profiles, which was successfully applied to distillation grade determination of blended YY Complete EOs.

摘要

依兰依兰(YY)精油是从热带树木茄科植物依兰树(Cananga odorata [Lam.] Hook. f. & Thomson)的新鲜成熟花朵中蒸馏而来的,因其具有芳香特性而广泛应用于香水和化妆品行业。在此,使用两种不同的基于不同显色剂的高效薄层色谱(HPTLC)代谢组学图谱,即 2,2-二苯基-1-苦肼基(DPPH·)和对茴香醛,对来自不同地理来源和蒸馏级别的 52 个 YY 样本进行区分。第一个图谱是使用 DPPH·显色剂基于 YY 精油的自由基清除活性(RSA)开发的。HPTLC-DPPH·测定结果证实,YY 精油的 RSA 与蒸馏时间的长短成正比。通过气相色谱-质谱联用(GC-MS)和气相色谱-火焰离子化检测器(GC-FID),初步鉴定出对 YY 精油 RSA 有贡献的主要成分是大根香叶烯 D 和α-法呢烯、丁香酚和芳樟醇。第二个图谱是使用基于 YY 精油一般化学成分的通用对茴香醛显色剂开发的。基于 HPTLC-对茴香醛图谱对来自不同地理来源的 YY 精油进行非靶向代谢组学区分,然后进行主成分分析(PCA)。使用 PCA 和偏最小二乘回归(PLS)基于分箱 HPTLC-紫外(254nm)图谱建立了用于识别 YY 蒸馏级别的判别和预测模型,并成功应用于混合 YY 完整精油的蒸馏级别的确定。

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