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Discrimination of Malus Taxa with Different Scent Intensities Using Electronic Nose and Gas Chromatography–Mass Spectrometry

机译:利用电子鼻和气相色谱 - 质谱法辨别不同气味强度的杀菌群

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摘要

Floral scent is important in plant reproduction and also has aesthetic implications. However, the accurate determination of aroma is presently limited by the available collection and analysis tools. In this study, the floral scents of four crabapple taxa exhibiting faint, weak, clear, and strong scent intensities were comparatively analyzed by electronic nose (E-nose) and gas chromatography–mass spectrometry (GC–MS). The E-nose was able to effectively group the different taxa in the principal component analysis in correspondence with scent intensity. GC–MS analysis identified a total of 60 volatile compounds. The content of nitrogen-containing compounds and aliphatics and the number of unique components of the more aromatic taxa was significantly higher than the less aromatic taxa. α-Cedrene, β-cedrene, 5-methyl-1,3-dihydro-2H-benzimidazol-2-one, benzyl alcohol, linalool, and 4-pyrrolidinopyridine contributed significantly to taxon separation. The pattern recognition results confirmed that the E-nose results corroborated the GC–MS results. Furthermore, partial least squares regression analysis between the aromatic constituents and sensors indicated that particular sensors were highly sensitive to N-containing compounds, aliphatics, and terpenes. In conclusion, the E-nose is capable of discriminating crabapple taxa of different scent intensities in both a qualitative and quantitative respect, presenting a rapid and accurate reference approach for future applications.
机译:花香气味在植物繁殖中很重要,并且也具有审美的影响。然而,准确地确定香气的目前受到可用的收集和分析工具的限制。在这项研究中,通过电子鼻子(E-鼻子)和气相色谱 - 质谱(GC-MS)对呈微弱,弱,清晰和强烈的气味强度的四种Crabapple含量的花卉气味具有相对分析的。 E-鼻子能够在与气味强度的对应关系中有效地将不同的分类群分析。 GC-MS分析鉴定了总共60种挥发性化合物。含氮化合物和脂肪层的含量和更多芳族分类群的独特组分的数量显着高于较少的芳香素。 α-氯烯,β-氯烯,5-甲基-1,3-二氢-2H-苯并咪唑-2-一,苄醇,烯丙基和4-吡咯烷吡啶与分类分离有显着贡献。模式识别结果证实,电子鼻源结果证实了GC-MS结果。此外,芳族成分和传感器之间的局部最小二乘回归分析表明,特定的传感器对含N含N的化合物,脂肪族和萜烯非常敏感。总之,电子鼻子能够在定性和定量方面歧视不同香味强度的Crabapple分类群,提出了对未来申请的快速准确的参考方法。

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