A comparative phytochemical study of nine Lauraceae species by using chemometric data analysis
The diversity of secondary metabolites of individual plants results from multiple enzymatic processes in planta and various environmental factors, such as temperature, moisture, and soil conditions. Chemical composition analysis of plants can lead to a new method to understand relationship among com...
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| Veröffentlicht in: | PloS one 2022-09, Vol.17 (9), p.e0273616-e0273616 |
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| creator | Oh, Mira Park, Hyun-Seung Um, Soohyun Yang, Tae-Jin Kim, Seung Hyun |
| description | The diversity of secondary metabolites of individual plants results from multiple enzymatic processes in planta and various environmental factors, such as temperature, moisture, and soil conditions. Chemical composition analysis of plants can lead to a new method to understand relationship among comparable plants along with biological classification such as genetic and anatomical method. In this study, the chemical diversity of nine different Lauraceae species was investigated, and the plant samples were chemically analyzed and classified. Multivariate analysis methods, such as PLS-DA, were used to select important metabolites distinguishing the nine Lauraceae species. The selected metabolites were identified through preparative LC-MS or MS/MS fragment pattern analysis. In addition, the chemical dendrogram for the nine Lauraceae species was interpreted through molecular network analysis and compared with the genetic dendrogram. This approach enabled us to compare the complete chemical compositions of multiple plant samples to identify relationships among plants. |
| doi_str_mv | 10.1371/journal.pone.0273616 |
| format | Article |
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Chemical composition analysis of plants can lead to a new method to understand relationship among comparable plants along with biological classification such as genetic and anatomical method. In this study, the chemical diversity of nine different Lauraceae species was investigated, and the plant samples were chemically analyzed and classified. Multivariate analysis methods, such as PLS-DA, were used to select important metabolites distinguishing the nine Lauraceae species. The selected metabolites were identified through preparative LC-MS or MS/MS fragment pattern analysis. In addition, the chemical dendrogram for the nine Lauraceae species was interpreted through molecular network analysis and compared with the genetic dendrogram. This approach enabled us to compare the complete chemical compositions of multiple plant samples to identify relationships among plants.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0273616</identifier><identifier>PMID: 36084027</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Acids ; Algorithms ; Analysis ; Biology and Life Sciences ; Chemical analysis ; Chemical composition ; Computer and Information Sciences ; Data analysis ; Discriminant analysis ; Environmental factors ; Gas flow ; Genetic analysis ; Identification and classification ; Lauraceae ; Laurel ; Metabolites ; Moisture effects ; Multivariate analysis ; Network analysis ; Pattern analysis ; Physical Sciences ; Phytochemicals ; Plant metabolites ; Research and Analysis Methods ; Retention ; Secondary metabolites ; Soil chemistry ; Soil conditions ; Soil moisture ; Soil temperature ; Species ; Statistical analysis</subject><ispartof>PloS one, 2022-09, Vol.17 (9), p.e0273616-e0273616</ispartof><rights>COPYRIGHT 2022 Public Library of Science</rights><rights>2022 Oh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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Chemical composition analysis of plants can lead to a new method to understand relationship among comparable plants along with biological classification such as genetic and anatomical method. In this study, the chemical diversity of nine different Lauraceae species was investigated, and the plant samples were chemically analyzed and classified. Multivariate analysis methods, such as PLS-DA, were used to select important metabolites distinguishing the nine Lauraceae species. The selected metabolites were identified through preparative LC-MS or MS/MS fragment pattern analysis. In addition, the chemical dendrogram for the nine Lauraceae species was interpreted through molecular network analysis and compared with the genetic dendrogram. 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| subjects | Acids Algorithms Analysis Biology and Life Sciences Chemical analysis Chemical composition Computer and Information Sciences Data analysis Discriminant analysis Environmental factors Gas flow Genetic analysis Identification and classification Lauraceae Laurel Metabolites Moisture effects Multivariate analysis Network analysis Pattern analysis Physical Sciences Phytochemicals Plant metabolites Research and Analysis Methods Retention Secondary metabolites Soil chemistry Soil conditions Soil moisture Soil temperature Species Statistical analysis |
| title | A comparative phytochemical study of nine Lauraceae species by using chemometric data analysis |
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