Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares

Rongguo Su; Xiaona Chen; Zhenzhen Wu; Peng Yao; Xiaoyong Shi

doi:10.1007/s00343-015-4179-6

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Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares

OriginalPaper | Updated：2023-05-16

- Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares
- Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares
- 海洋湖沼学报（英文） 2015年33卷第4期页码：878-889
- Affiliations：
  
  1. College of Chemistry and Chemical Engineering Ocean University of China
  2. Tianjin University Center for Marine Environmental Ecology School of Environmental Science and Engineering Tianjin University
- Author bio：
- Funds：
  
  Supported by the National Natural Science Foundation of China (Nos. 41376106, 41176063) and the Shandong Provincial Natural Science Foundation of China (No. ZR2013DM017)
- DOI：10.1007/s00343-015-4179-6
  中图分类号：
- 网络首发：2015-06-30，
  
  纸质出版：2015
- Accepted：
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Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares[J]. 海洋湖沼学报（英文）, 2015,33(4):878-889.

Su, R., Chen, X., Wu, Z. et al. Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares., Chin. J. Ocean. Limnol. 33, 878–889 (2015). https://doi.org/10.1007/s00343-015-4179-6
Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares[J]. 海洋湖沼学报（英文）, 2015,33(4):878-889. DOI： 10.1007/s00343-015-4179-6.

Su, R., Chen, X., Wu, Z. et al. Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares., Chin. J. Ocean. Limnol. 33, 878–889 (2015). https://doi.org/10.1007/s00343-015-4179-6 DOI：

摘要

Abstract

The feasibility of using fluorescence excitation-emission matrix (EEM) along with parallel factor analysis (PARAFAC) and nonnegative least squares (NNLS) method for the differentiation of phytoplankton taxonomic groups was investigated. Forty-one phytoplankton species belonging to 28 genera of five divisions were studied. First

the PARAFAC model was applied to EEMs

and 15 fluorescence components were generated. Second

15 fluorescence components were found to have a strong discriminating capability based on Bayesian discriminant analysis (BDA). Third

all spectra of the fluorescence component compositions for the 41 phytoplankton species were spectrographically sorted into 61 reference spectra using hierarchical cluster analysis (HCA)

and then

the reference spectra were used to establish a database. Finally

the phytoplankton taxonomic groups was differentiated by the reference spectra database using the NNLS method. The five phytoplankton groups were differentiated with the correct discrimination ratios (CDRs) of 100% for single-species samples at the division level. The CDRs for the mixtures were above 91% for the dominant phytoplankton species and above 73% for the subdominant phytoplankton species. Sixteen of the 85 field samples collected from the Changjiang River estuary were analyzed by both HPLC-CHEMTAX and the fluorometric technique developed. The results of both methods reveal that Bacillariophyta was the dominant algal group in these 16 samples and that the subdominant algal groups comprised Dinophyta

Chlorophyta and Cryptophyta. The differentiation results by the fluorometric technique were in good agreement with those from HPLC-CHEMTAX. The results indicate that the fluorometric technique could differentiate algal taxonomic groups accurately at the division level.

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references

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