Quantitative Determination of Benzoic Acid in Flour Based on Terahertz Time-Domain Spectroscopy and BPNN Model

Jun Hu; Yande Liu; Xudong Sun; Bin Li; Jia Xu; Aiguo Ouyang

doi:10.3788/LOP57.073002

Laser & Optoelectronics Progress, Volume. 57, Issue 7, 073002(2020)

Quantitative Determination of Benzoic Acid in Flour Based on Terahertz Time-Domain Spectroscopy and BPNN Model

Jun Hu, Yande Liu^*, Xudong Sun, Bin Li, Jia Xu, and Aiguo Ouyang

Author Affiliations

School of Mechatronics Engineering, East China Jiaotong University, Nanchang, Jiangxi 330013, China

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Figures & Tables(9)

Fig. 1. Topology structure of BP neural network

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$Terahertz absorption spectra of benzoic acid with different mass fraction in flour$

Fig. 2. Terahertz absorption spectra of benzoic acid with different mass fraction in flour

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Fig. 3. Root-mean-square error of benzoic acid-doped flour changed with principal component factor

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Fig. 4. Regression coefficient of terahertz absorption spectrum of benzoic acid-doped flour in PLS model

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Fig. 5. Optimized results of BPNN for number of input vectors and hidden layers

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$Relationship between predicted values and actual values of mass fraction in different models$

Fig. 6. Relationship between predicted values and actual values of mass fraction in different models

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Table 1. Mass fraction of benzoic acid in calibration and prediction sets
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Table 1. Mass fraction of benzoic acid in calibration and prediction sets
Data set Number ofsamples Mass fraction /%
Minimum Maximum Mean Standard deviation
Total 176 0.0479 19.999 9.332 6.243
Calibration 132 0.0479 19.999 9.332 6.297
Prediction 44 0.0479 19.999 9.332 6.249

Table 2. Results of terahertz absorption coefficient in PLS model by correction processing for flour doped with benzoic acid

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Table 2. Results of terahertz absorption coefficient in PLS model by correction processing for flour doped with benzoic acid

Pretreatment method	P_C	r_C	RMSEC	r_p	RMSEP
Original	4	0.9722	0.0143	0.9747	0.0156
Savitzky-Golay	4	0.9719	0.0142	0.9746	0.0155
MSC	3	0.9758	0.0133	0.9755	0.0136
Baseline correction	5	0.9799	0.0124	0.9697	0.0143
Normalization	4	0.9806	0.0120	0.9790	0.0128

Table 3. Results of terahertz spectral absorption coefficient of benzoic acid-doped flour samples in LS-SVM model

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Table 3. Results of terahertz spectral absorption coefficient of benzoic acid-doped flour samples in LS-SVM model

Type ofkernel function	Equation	Parameter	Number ofinput variables	r_p	RMSEP	t /s
Lin	K(x_i,x_j)=x_ix_j	γ= 12.670	264	0.983	0.012	6.162
RBF	K(x,x_i)=exp(- $\begin{matrix} ‖ x, x_{i} ‖^{2} \end{matrix}$ /2σ²)	γ=16690σ²=229.418	264	0.987	0.011	4.368
Lin	K(x_i,x_j)=x_ix_j	γ= 7.2903	10	0.9802	0.0126	5.7252
RBF	K(x,x_i)=exp(- $\begin{matrix} ‖ x, x_{i} ‖^{2} \end{matrix}$ /2σ²)	γ=219380σ²=3276.1	10	0.9820	0.0128	4.8204

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Jun Hu, Yande Liu, Xudong Sun, Bin Li, Jia Xu, Aiguo Ouyang. Quantitative Determination of Benzoic Acid in Flour Based on Terahertz Time-Domain Spectroscopy and BPNN Model[J]. Laser & Optoelectronics Progress, 2020, 57(7): 073002

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Paper Information

Category: Spectroscopy

Received: Jun. 26, 2019

Accepted: Sep. 26, 2019

Published Online: Mar. 31, 2020

The Author Email: Liu Yande (jxliuyd@163.com)

DOI:10.3788/LOP57.073002

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Mass fraction of benzoic acid in calibration and prediction sets

Table 1. Mass fraction of benzoic acid in calibration and prediction sets

Table 2. Results of terahertz absorption coefficient in PLS model by correction processing for flour doped with benzoic acid

Table 2. Results of terahertz absorption coefficient in PLS model by correction processing for flour doped with benzoic acid

Table 3. Results of terahertz spectral absorption coefficient of benzoic acid-doped flour samples in LS-SVM model

Table 3. Results of terahertz spectral absorption coefficient of benzoic acid-doped flour samples in LS-SVM model