Skip to main content

Advertisement

Log in

Multi-elements linear discriminant analysis of herbaceous and woody plants in southwest china karst region using orthogonal partial least squares model

  • Published:
Plant Ecology Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

Data available on request from the authors.

References

Download references

Acknowledgements

The authors thank Man Liu for field sampling.

Funding

This work was supported by 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 Universities) [grant number 2652023001]; National Natural Science Foundation of China [grant number 41325010].

Author information

Authors and Affiliations

Authors

Contributions

Yuqing Zhao: Conceptualization, Methodology, Software, Formal analysis, Writing—original draft, Writing—review & editing; Guilin Han: Conceptualization, Validation, Resources, Investigation, Data curation, Writing—original draft, Writing—review & editing, Supervision, Project administration, Funding acquisition; Rui Qu: Writing—original draft, Writing—review & editing; Qian Zhang: Writing—original draft, Writing—review & editing. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Guilin Han.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Communicated by Dafeng Hui.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOC 100 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, Y., Han, G., Qu, R. et al. Multi-elements linear discriminant analysis of herbaceous and woody plants in southwest china karst region using orthogonal partial least squares model. Plant Ecol (2024). https://doi.org/10.1007/s11258-024-01424-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11258-024-01424-7

Keywords

Navigation