Rapid Determination of TBARS Contents in Tan Mutton Using Hyperspectral Imaging

Fig. 1. Linear fitting diagrams of measured and predicted values of TBARS contents
(a): Raw-PLSR; (b): SG-PLSR; (c): De-trending-PLSR; (d): SG+De-trending-PLSR

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Fig. 2. Two-dimensional correlation spectra and its slice spectra
(a): Synchronous contour map; (b): Slice spectra

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Fig. 3. Characteristic wavelength extracted by variable selection algorithm
(a): VCPA algorithm; (b): SPA algorithm

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Table 1. Statistics of measured TBARS contents in Tan mutton
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Table 1. Statistics of measured TBARS contents in Tan mutton
Data set Samples TBARS contents/(mg·kg^-1)
Max Min Mean Standard
deviation
Calibration set 135 1.47 0.16 0.67 0.30
Prediction set 45 1.37 0.17 0.61 0.35

Table 2. PLSR modeling results of TBARS content with different pretreatment methods

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Table 2. PLSR modeling results of TBARS content with different pretreatment methods

Pretreatment method	No. LV	Calibration set		Cross-validation		Prediction set
Pretreatment method	No. LV	$R_{C}^{2}$	RMSEC/(mg·kg^-1)	$R_{CV}^{2}$	RMSECV/(mg·kg^-1)	$R_{P}^{2}$	RMSEP/(mg·kg^-1)
Raw	17	0.830	0.123	0.722	0.159	0.821	0.157
SG	20	0.829	0.123	0.706	0.164	0.805	0.189
de-trending	20	0.874	0.106	0.770	0.144	0.853	0.139
SG+de-trending	20	0.850	0.115	0.749	0.150	0.827	0.243

Table 3. Signs of cross-peaks generated from two-dimensional correlation analysis
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Table 3. Signs of cross-peaks generated from two-dimensional correlation analysis
Wavelength/nm 579 699 756 867
Synchronous
579 + - - +
699 + + -
756 + -
867 +

Table 4. The results of extracting characteristic wavelengths

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Table 4. The results of extracting characteristic wavelengths

Wavelength extraction method	Variable number	Characteristic wavelength/nm
FS+VCPA	7	636, 641, 646, 660, 675, 694, 915
FS+CARS	16	415, 713, 727, 732, 751, 756, 785, 862, 895, 915, 924, 939, 958, 972, 977, 982
FS+SPA	20	401, 449, 458, 468, 492, 516, 559, 593, 603, 631, 675, 723, 795, 819, 843, 852, 943, 953, 972, 987
2DCOS+VCPA	8	631, 641, 646, 651, 660, 675, 689, 761
2DCOS+CARS	24	588, 593, 598, 603, 612, 622, 631, 636, 646, 655, 675, 684, 689, 703, 713, 727, 742, 751, 775, 780, 790, 799, 809, 819
2DCOS+SPA	14	593, 598, 603, 612, 622, 631, 641, 651, 660, 675, 689, 785, 809, 823

Table 5. Comparison of PLSR models based on different wavelength extraction methods

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Table 5. Comparison of PLSR models based on different wavelength extraction methods

Extraction method	No. LV	Calibration set		Cross-validation		Prediction set
Extraction method	No. LV	$R_{C}^{2}$	RMSEC/(mg·kg^-1)	$R_{CV}^{2}$	RMSECV/(mg·kg^-1)	$R_{P}^{2}$	RMSEP/(mg·kg^-1)
FS	20	0.874	0.106	0.770	0.144	0.853	0.139
FS+VCPA	7	0.794	0.135	0.770	0.143	0.858	0.139
FS+CARS	15	0.821	0.126	0.771	0.143	0.806	0.148
FS+SPA	19	0.792	0.136	0.717	0.159	0.842	0.140
2DCOS	20	0.850	0.115	0.751	0.150	0.854	0.139
2DCOS+VCPA	8	0.795	0.135	0.769	0.143	0.839	0.146
2DCOS+CARS	19	0.857	0.113	0.790	0.137	0.862	0.132
2DCOS+SPA	14	0.815	0.128	0.771	0.143	0.845	0.143

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Nai-yun FAN, Gui-shan LIU, Jing-jing ZHANG, Rui-rui YUAN, You-rui SUN, Yue LI. Rapid Determination of TBARS Contents in Tan Mutton Using Hyperspectral Imaging[J]. Spectroscopy and Spectral Analysis, 2022, 42(3): 713

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Paper Information

Category: Research Articles

Received: Feb. 22, 2021

Accepted: Jun. 6, 2021

Published Online: Apr. 19, 2022

The Author Email: FAN Nai-yun (fny0606@163.com)

DOI:10.3964/j.issn.1000-0593(2022)03-0713-06

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Statistics of measured TBARS contents in Tan mutton

Table 1. Statistics of measured TBARS contents in Tan mutton

Table 2. PLSR modeling results of TBARS content with different pretreatment methods

Table 2. PLSR modeling results of TBARS content with different pretreatment methods

Table 3. Signs of cross-peaks generated from two-dimensional correlation analysis

Table 3. Signs of cross-peaks generated from two-dimensional correlation analysis

Table 4. The results of extracting characteristic wavelengths

Table 4. The results of extracting characteristic wavelengths

Table 5. Comparison of PLSR models based on different wavelength extraction methods

Table 5. Comparison of PLSR models based on different wavelength extraction methods