Characterization of scents from Juniperus chinensis by headspace in-needle microextraction using graphene oxide-polyaniline nanocomposite coated wire followed by gas chromatography-mass spectrometry

Talanta(2022)

引用 3|浏览0
暂无评分
摘要
Scents released by trees are the secondary metabolites that play various roles, including indirect plant defense against insects, attraction to pollinators, communication, adaptation to heat resistance, environmental stress, and protection from predators. In this study, the scents of three individual trees designated as Korean natural monuments (pair of Chinese junipers, Chinese juniper, and horizontal Chinese juniper tree) were analyzed using headspace in-needle microextraction (HS-INME) method with graphene oxide-polyaniline (GO-PANI) adsorbent followed by gas chromatography-mass spectrometry (GC/MS). GO-PANI layer was coated on a stainless steel wire using cyclic voltammetry (CV). It was characterized through thermogravimetric analysis (TGA), Fourier transform-infrared spectroscopy (FT-IR), and field emission-scanning electron microscope (FE-SEM). As a result, it was confirmed that the GO-PANI coating was successfully prepared. α-Longipinene, α-cedrene, and cedrol, which are representative scent components of common juniper trees, were selected as target compounds through a preliminary test and used in the optimization processes. Response surface methodology (RSM) with Box Behnken Design (BBD) was applied to optimize the experimental conditions. The developed analytical method was validated by checking the limit of detection (LOD), the limit of quantitation (LOQ), recovery rate, sensitivity, and reproducibility. Significant scientific findings from three Korean natural monuments of Juniperus chinensis were characterized by their major scent components such as α-cedrene, γ-cadinene, thujopsene, and cedrol of pungent-woody base note.
更多
查看译文
关键词
Juniperus chinensis,Scent or volatile organic compounds,Natural monuments,Graphene oxide-polyaniline,In-needle microextraction (INME),Response surface methodology (RSM)
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要