Concentration Monitoring of Paralytic Shellfish Poison Producing Algae Based on Three Dimensional Fluorescence Spectroscopy

Si-yuan WANG; Bao-jun ZHANG; Hao WANG; Si-yu GOU; Yu LI; Xin-yu LI; Ai-ling TAN; Tian-jiu JIANG; Wei-hong BI

doi:10.3964/j.issn.1000-0593(2021)11-3480-06

Journals >Spectroscopy and Spectral Analysis >Volume 41 >Issue 11 >Page 3480 > Article

Spectroscopy and Spectral Analysis
Vol. 41, Issue 11, 3480 (2021)

Concentration Monitoring of Paralytic Shellfish Poison Producing Algae Based on Three Dimensional Fluorescence Spectroscopy

Si-yuan WANG^1,*, Bao-jun ZHANG^1,1;, Hao WANG^1,1;, Si-yu GOU^2,2;..., Yu LI^1,1;, Xin-yu LI^1,1;, Ai-ling TAN^1,1;, Tian-jiu JIANG^2,2; and Wei-hong BI^{1,1; *;}|Show fewer author(s)

Author Affiliations

¹1. School of Information Science and Engineering, Yanshan University, The Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province, Qinhuangdao 066004, China

²2. Research Center for Harmful Algae and Marine Biology, Jinan University, Guangzhou 510632, China

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DOI: 10.3964/j.issn.1000-0593(2021)11-3480-06 Cite this Article

Si-yuan WANG, Bao-jun ZHANG, Hao WANG, Si-yu GOU, Yu LI, Xin-yu LI, Ai-ling TAN, Tian-jiu JIANG, Wei-hong BI. Concentration Monitoring of Paralytic Shellfish Poison Producing Algae Based on Three Dimensional Fluorescence Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2021, 41(11): 3480 Copy Citation Text

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Contour maps of Gymnodinium catenatum at different concentrations(a): 103 cells·mL-1; (b): 104 cells·mL-1; (c): 105 cells·mL-1; (d): 106 cells·mL-1

Fig. 1. Contour maps of Gymnodinium catenatum at different concentrations
(a): 10³ cells·mL^-1; (b): 10⁴ cells·mL^-1; (c): 10⁵ cells·mL^-1; (d): 10⁶ cells·mL^-1

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Contour maps of Alexandrium pacificum at different concentrations(a): 103 cells·mL-1; (b): 104 cells·mL-1; (c): 105 cells·mL-1; (d): 106 cells·mL-1

Fig. 2. Contour maps of Alexandrium pacificum at different concentrations
(a): 10³ cells·mL^-1; (b): 10⁴ cells·mL^-1; (c): 10⁵ cells·mL^-1; (d): 10⁶ cells·mL^-1

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Fig. 3. Contour maps of Alexandrium minimum at different concentrations
(a): 10³ cells·mL^-1; (b): 10⁴ cells·mL^-1; (c): 10⁵ cells·mL^-1

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Fig. 4. Relationship between predicted value and true value in training set and prediction set
(a): Relationship between predicted value and true value in training set;(b): Relationship between predicted value and true value in prediction set

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Fig. 5. Linear fitting results of predicted value and true value in test set

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Ex/nm	Em(650~700 nm)				Em(650~750 nm)
Ex/nm	RMSECV	RMSEP	R_c	R_p	RMSECV	RMSEP	R_c	R_p
400	1.219 8	1.272 2	0.466 1	0.502 7	0.851 1	0.902 9	0.897 1	0.896 4
410	1.220 1	1.273 9	0.468 8	0.457 3	0.851 4	0.903 9	0.895 3	0.885 8
420	0.017 3	0.280 8	0.973 0	0.128 5	0.850 5	0.900 3	0.897 3	0.880 8
430	0.983 0	1.153 8	0.597 9	0.406 6	0.293 4	0.404 7	0.931 4	0.898 4
440	0.976 0	1.136 0	0.606 0	0.428 7	0.791 7	0.837 2	0.897 7	0.875 5
450	0.962 9	1.147 2	0.631 4	0.417 2	0.356 1	0.431 3	0.911 1	0.892 5
460	0.966 7	1.146 6	0.616 7	0.423 7	0.277 2	0.361 8	0.932 8	0.918 6
470	1.206 8	1.266 8	0.520 8	0.430 2	0.280 8	0.409 7	0.931 6	0.898 2
480	1.212 7	1.270 3	0.509 8	0.476 0	0.261 7	0.341 8	0.937 2	0.927 8
490	0.980 6	1.146 2	0.602 3	0.407 5	0.196 6	0.424 2	0.954 1	0.887 4
500	0.015 3	0.975 8	0.973 0	0.611 4	0.360 3	0.474 8	0.911 1	0.869 1
510	0.254 4	0.958 6	0.956 7	0.632 7	0.275 8	0.424 2	0.933 1	0.886 1
520	0.011 5	1.122 7	0.973 0	0.481 4	0.258 8	0.351 6	0.938 0	0.912 9
530	0.721 1	1.206 3	0.831 2	0.407 0	0.264 0	0.391 2	0.936 5	0.901 8
540	0.612 0	1.176 3	0.865 3	0.412 9	0.856 7	0.916 3	0.890 2	0.858 5
550	0.449 1	1.071 7	0.925 4	0.578 5	0.619 9	1.044 5	0.973 0	0.365 0
560	0.243 7	0.983 1	0.961 7	0.660 1	0.340 2	0.494 4	0.911 7	0.859 2
570	1.106 5	1.172 6	0.430 3	0.336 5	0.190 4	0.425 0	0.953 6	0.893 9
580	1.105 6	1.189 4	0.446 5	0.300 2	0.868 8	0.939 9	0.860 1	0.865 3
590	0.919 8	1.172 2	0.506 1	0.452 7	0.409 0	0.444 6	0.891 4	0.891 7
600	0.960 1	1.276 8	0.446 2	0.407 3	0.291 7	0.409 0	0.928 2	0.896 9

Table 1. Results of PSO-LSSVM quantitative model for paralytic shellfish algae under single excitation wavelength

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Ex/nm	RMSE	R	Ex/nm	RMSE	R
410	0.988 1	0.595 9	490	0.964 0	0.618 8
420	0.966 9	0.615 5	500	1.005 9	0.578 3
430	0.984 3	0.598 8	530	1.125 7	0.431 0
440	0.971 1	0.613 6	540	1.110 0	0.438 8
450	0.951 4	0.626 9	550	1.111 2	0.437 3
460	0.972 2	0.609 6	560	1.089 3	0.471 2
470	0.964 9	0.614 0	530	1.125 7	0.431 0
480	0.964 9	0.614 0

Table 2. Quantitative model results of PLSR algorithm under single excitation wavelength

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Ex/nm	RMSEC	RMSEP	R_c	R_p
460, 530	0.017 1	0.291 0	0.999 9	0.949 2
480, 530	0.197 7	0.348 4	0.952 8	0.942 6
460, 550	0.134 0	0.322 6	0.964 0	0.937 9
430, 470	0.140 7	0.304 3	0.963 0	0.934 5
460, 560	0.187 3	0.361 9	0.955 0	0.932 3
420, 480	0.194 5	0.378 3	0.953 6	0.932 0
420, 460	0.182 5	0.355 6	0.956 0	0.931 7
460, 480	0.227 8	0.328 9	0.973 0	0.931 4
420, 470	0.158 0	0.350 7	0.960 3	0.930 4
440, 530	0.134 2	0.346 6	0.963 9	0.929 5
470, 480	0.199 2	0.318 6	0.952 6	0.928 4
480, 560	0.194 8	0.400 1	0.953 5	0.926 6
430, 480	0.208 1	0.373 7	0.950 6	0.922 7
430, 460	0.203 3	0.349 8	0.951 8	0.922 1
480, 550	0.177 2	0.365 4	0.956 9	0.920 6
430, 530	0.189 8	0.378 8	0.954 5	0.920 4

Table 3. Quantitative model results of PSO-LSSVM algorithm with two excitation wavelengths

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