• Title/Summary/Keyword: lilac blossom

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Characterization of Fragrances from Lilac Blossom by Gas Chromatography-Mass Spectrometry (GC-MS에 의한 라일락 꽃 향기 분석)

  • Kim, Nam-Sun;Lee, Dong-Sun
    • Analytical Science and Technology
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    • v.17 no.1
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    • pp.85-89
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    • 2004
  • Fragrance components of lilac (Syringa vulgaris) blossom have been characterized in this paper. The accurate characterization of fragrances collected from lilac blossom was carried out by solid-phase trapping-solvent extraction and gas chromatography-ion trap mass spectrometry. According to lilac species, the chemical compositions were significantly different. Benzaldehyde, phenylacetaldehyde, and ${\alpha}$-farnesene were found as the predominant component of white lilac blossom whereas benzaldehyde, ${\alpha}$-pinene, and ocimene were those of pale purple lilac. The enantiomeric analysis of ${\alpha}$-pinene in lilac blossom was found in the form of ( ).

Headspace GC-MS Analysis of Spring Blossom Fragrance at Chungnam National University Daedeok Campus

  • Choi, Yeonwoo;Lee, Sanghyun;Kim, Young-Mi;Nguyen, Huu-Quang;Kim, Jeongkwon;Lee, Jaebeom
    • Mass Spectrometry Letters
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    • v.13 no.4
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    • pp.125-132
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    • 2022
  • There are many types of spring blossoms on the Daedeok campus of Chungnam National University (CNU) at the area of 1,600,000 square meters. As an assignment for the class of Analytical Chemistry I for second-year undergraduate students, 2021, flower petals collected from various floral groups (Korean azalea, Korean forsythia, Dilatata lilac, Lilytree, Lily magnolia, and Prunus yedoensis) were analyzed using headspace extraction coupled to gas chromatography-mass spectrometry (HS-GC-MS) to study the aromatic profiles and fragrance compounds of each sample group. Various types of compounds associated with the aroma profiles were detected, including saturated alcohols and aldehydes (ethanol, 1-hexanol, and nonanal), terpenes (limonene, pinene, and ocimene), and aromatic compounds (benzyl alcohol, benzaldehyde). The different contribution of these compounds for each floral type was visualized using statistical tools and classification models based on principal component analysis with high reliability (R2 = 0.824, Q2 = 0.616). These results showed that HS-GC-MS with statistical analysis is a powerful method to characterize the volatile aromatic profile of biological specimens.