Fast Detection of Chlorpyrifos Residues in Tea via Surface-Enhanced Raman Spectroscopy Combined with Two-Dimensional Correlation Spectroscopy

Xiao Hu; Ruimei Wu; Xiaoyu Zhu; Peng Liu; Aihua Xiong; Junshi Huang; Puxiang Yang; Junfei Xiong; Shirong Ai

doi:10.3788/AOS201939.0730001

Acta Optica Sinica, Volume. 39, Issue 7, 0730001(2019)

Fast Detection of Chlorpyrifos Residues in Tea via Surface-Enhanced Raman Spectroscopy Combined with Two-Dimensional Correlation Spectroscopy

Xiao Hu¹, Ruimei Wu², Xiaoyu Zhu³, Peng Liu², Aihua Xiong², Junshi Huang², Puxiang Yang⁴, Junfei Xiong², and Shirong Ai^1,2、*

Author Affiliations

¹ School of Computer and Information Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi 330045, China

² School of Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi 330045, China

³ School of Food Science and Engineering, Jiang Xi Agricultural University, Nanchang, Jiangxi 330045, China

⁴ Jiangxi Sericulture and Tea Research Institute, Nanchang, Jiangxi 330043, China

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Figures & Tables(11)

Fig. 1. Comparison of Raman spectra of Chlorpyrifos. (a) SERS of 10-mg/L chlorpyrifos standard solution; (b) theoretical Raman spectrum of chlorpyrifos

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Fig. 2. Raman spectra of tea samples. (a) Original spectra; (b) spectra after SNV pre-treatment

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Fig. 3. Two-dimensional correlation spectra of chlorpyrifos residues in tea samples at different bands. (a) Synchronization spectra; (b) autocorrelation spectra

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Fig. 4. Characteristic peaks of chlorpyrifos pesticide residues in tea

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Fig. 5. RMSECV of corresponding SVM model built with different principal components

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Fig. 6. Iteration curve of GWO

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Fig. 7. Scatter plots of predicted and measured values of model. (a) Calibration set; (b) prediction set

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Table 1. Preparation of tea samples with chlorpyrifos pesticide residue
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Table 1. Preparation of tea samples with chlorpyrifos pesticide residue
Mass concentration /(mg·L^-1) Number Interval mass fraction /10^-6
0 1
5-10 2-6 0.83
11-20 7-26 0.50
21-30 27-67 0.24
31-40 68-93 0.38
41-50 94-100 1.43

Table 2. Theoretical and experimental SERS spectra of chlorpyrifos

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Table 2. Theoretical and experimental SERS spectra of chlorpyrifos

Theoretical wavenumber /cm^-1	Experimental wavenumber /cm^-1	Assignment
434	450	v(Cl—H)
524	524	v(P—O)
570	560	v(P S)+v(C—CL)
604	-	v_breathe
674	668	v_ring
752	760	v(P—O—C)
814	824	v(P—O—C)
846	846	v(C—Cl)
936	936	v(P—O—C)
-	972	v(P—O—C)
1080	1096	δ(C-H)ip
-	1164	v_ring
-	1268	v_ring
1322	1322	v_ring
1352	1352	v(C-N)
1416	1420	δ(C-H)ip
-	1494	v_ring
1538	1538	v(C-N)
1568	1566	v(C C)
1610	-	v(C C)
Abbreviations: v-stretching; δ-deformation; ip-in plane bending

Table 3. Performance of different models

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Table 3. Performance of different models

Model	Variable selected method	Variables	PCs	Calibration		Prediction
Model	Variable selected method	Variables	PCs	${R^{2}}_{c}$	RMSEC	${R^{2}}_{p}$	RESEP	RPD
PLS	1096 cm^-1	1	1	0.54	7.28	0.61	5.40	1.54
	Full	701	8	0.97	1.76	0.94	1.91	4.19
	2DCOS	15	4	0.96	2.06	0.96	1.62	5.13
SVM	1096 cm^-1	1	1	0.57	7.30	0.66	4.80	1.73
	Full	701	15	0.97	1.94	0.94	2.23	3.58
	2DCOS	15	6	0.98	1.44	0.98	1.32	6.32

Table 4. Predicted and measured values of chlorpyrifos residue in tea based on SVM model
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Table 4. Predicted and measured values of chlorpyrifos residue in tea based on SVM model
Sample True mass fraction /10^-6 Predicted mass fraction /10^-6 Recovery /% Relative deviation /%
1 4.23 4.49 106.15 6.15
2 13.79 14.33 103.92 3.92
3 22.34 21.81 97.63 -2.37
4 34.53 33.99 98.44 -1.56
5 45.12 43.83 97.14 -2.86

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Xiao Hu, Ruimei Wu, Xiaoyu Zhu, Peng Liu, Aihua Xiong, Junshi Huang, Puxiang Yang, Junfei Xiong, Shirong Ai. Fast Detection of Chlorpyrifos Residues in Tea via Surface-Enhanced Raman Spectroscopy Combined with Two-Dimensional Correlation Spectroscopy[J]. Acta Optica Sinica, 2019, 39(7): 0730001

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