Multi-elements linear discriminant analysis of herbaceous and woody plants in southwest china karst region using orthogonal partial least squares model
文献类型：期刊论文
| 作者 | Zhao, Yuqing2,3,4; Han, Guilin2,3,4; Qu, Rui2,3,4; Zhang, Qian1 |
| 刊名 | PLANT ECOLOGY
 |
| 出版日期 | 2024-05-07 |
| 页码 | 15 |
| 关键词 | Karst areas Herbaceous plants Woody plants Trace elements Multivariate statistical analysis OPLS-DA |
| ISSN号 | 1385-0237 |
| DOI | 10.1007/s11258-024-01424-7 |
| 通讯作者 | Han, Guilin(hanguilin@cugb.edu.cn) |
| 英文摘要 | The karst region in southwest China is one of world's largest continuous karst landforms in the world, renowned for its unique landscapes and abundant biodiversity. This study collected 49 leaf samples (21 herbaceous plants and 28 woody plants) from the typical karst zone in Puding County, China, and determined the content of elements in plant leaves using ICP-OES. The concentration characteristics and discrepancy of trace elements (Cr, Cu, Fe, Mn, Pb, Sr, and Zn) in herbaceous and woody plants were analyzed employing statistical analysis models. The results revealed that there were significant differences in the concentrations of trace elements between herbaceous and woody plants. The median concentrations of trace elements in herbaceous plants and woody plants, ranked from high to low, were: Fe > Sr > Mn > Zn > Cr > Cu > Pb and Fe > Sr > Mn > Cr > Zn > Pb > Cu. The outcomes of the correlation analysis revealed discernible differences in the interactions of trace elements within the leaves of herbaceous and woody plants. Principal component analysis (PCA) indicated that Cu, Mn and Zn were influenced by different mechanisms from Cr, Fe, Pb and Sr in plant system. Orthogonal partial least squares discriminant analysis (OPLS-DA) showed that Pb and Cr had stronger distinguishing capabilities between herbaceous and woody plants compared to other elements. The OPLS-DA model was likely considered an optimized model for tracing element sources from different plant species, which has a greatly applied potential in source identification of plant-derived trace elements in a complex environment. |
| WOS关键词 | HEAVY-METALS ; SOIL ; MULTIVARIATE ; GUIZHOU |
| 资助项目 | The Deep-time Digital Earth Science and Technology Leading Talents Team Funds for the Central Universities for the Frontiers Science Center for Deep-time Digital Earth, China University of Geosciences (Beijing) (Fundamental Research Funds for the Central[2652023001] ; National Natural Science Foundation of China[41325010] |
| WOS研究方向 | Plant Sciences ; Environmental Sciences & Ecology ; Forestry |
| 语种 | 英语 |
| WOS记录号 | WOS:001219526800001 |
| 出版者 | SPRINGER |
| 资助机构 | The Deep-time Digital Earth Science and Technology Leading Talents Team Funds for the Central Universities for the Frontiers Science Center for Deep-time Digital Earth, China University of Geosciences (Beijing) (Fundamental Research Funds for the Central ; National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/205879]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Han, Guilin |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.China Univ Geosci Beijing, Frontiers Sci Ctr Deep Time Digital Earth, Beijing 100083, Peoples R China 3.China Univ Geosci Beijing, Inst Earth Sci, Beijing 100083, Peoples R China 4.China Univ Geosci Beijing, State Key Lab Biogeol & Environm Geol, Beijing 100083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Yuqing,Han, Guilin,Qu, Rui,et al. Multi-elements linear discriminant analysis of herbaceous and woody plants in southwest china karst region using orthogonal partial least squares model[J]. PLANT ECOLOGY,2024:15. |
| APA | Zhao, Yuqing,Han, Guilin,Qu, Rui,&Zhang, Qian.(2024).Multi-elements linear discriminant analysis of herbaceous and woody plants in southwest china karst region using orthogonal partial least squares model.PLANT ECOLOGY,15. |
| MLA | Zhao, Yuqing,et al."Multi-elements linear discriminant analysis of herbaceous and woody plants in southwest china karst region using orthogonal partial least squares model".PLANT ECOLOGY (2024):15. |
入库方式： OAI收割
来源：地理科学与资源研究所
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