Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method

Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method

Direct quantification analysis of near-infrared (NIR) spectra is challenging because the number of spectral variables is usually considerably higher than the number of samples. To mitigate the so-called curse of dimensionality, var�iable selection is often performed before multivariate calibration...

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Main Authors: Ong, Pauline, Tung, I-Chun, Ching, Feng Chiu, I-Lin Tsai d ,, I-Lin Tsai d, Hsi, Chang Shih
Format: Article
Language:English
Published: Elsevier 2022
Subjects:
TK7800-8360 Electronics
Online Access:http://eprints.uthm.edu.my/6904/
http://eprints.uthm.edu.my/6904/1/J13942_fe1e071d4a672b5009a921fc69dc0ece.pdf
_version_ 1848888944754688000
author Ong, Pauline
Tung, I-Chun
Ching, Feng Chiu
I-Lin Tsai d ,, I-Lin Tsai d ,
Hsi, Chang Shih
author_facet Ong, Pauline
Tung, I-Chun
Ching, Feng Chiu
I-Lin Tsai d ,, I-Lin Tsai d ,
Hsi, Chang Shih
author_sort Ong, Pauline
building UTHM Institutional Repository
collection Online Access
description Direct quantification analysis of near-infrared (NIR) spectra is challenging because the number of spectral variables is usually considerably higher than the number of samples. To mitigate the so-called curse of dimensionality, var�iable selection is often performed before multivariate calibration. There has been much work in this regard, where the developed variable selection method can be categorized as individual variable selection, such as uninformative variable elimination or variable importance in projection, and continuous interval variable selection method such as interval partial least squares or moving window partial least squares. In this study, a new individual variable se�lection method, modified simulated annealing (MSA), was proposed and used in conjunction with the partial least squares regression (PLSR) model. The interpretability of the selected variables in the determination of aflatoxin B1 levels in white rice was assessed. The results revealed that the PLSR model combined with MSA not only yielded higher accuracy than the full-spectrum PLSR but also successfully shrank the variable space. The developed simplified PLSR model using MSA produced satisfactory performances, with root mean square error of calibration (RMSEC) of 0.11 μg/kg and 0.56 μg/kg, and root mean square error of prediction (RMSEP) of 7.16 μg/kg and 14.42 μg/kg, were obtained for the low-aflatoxin B1-level- and high-aflatoxin-B1-level samples, respectively. Specifically, the MSA-based models yielded improvements of 97.80% (calibration set) and 44.62% (prediction set) as well as 95.85% (calibration set) and 62.57% (prediction set) for both datasets when compared with the full-spectrum PLSR (low aflatoxin: RMSEC = 5.02 μg/kg, RMSEP = 12.93 μg/kg; high aflatoxin: RMSEC = 13.50 μg/kg, RMSEP = 38.53 μg/kg). Compared with the baseline method of simulated annealing (SA) (low aflatoxin: RMSEC = 0.21 μg/kg, RMSEP = 9.78 μg/kg; high aflatoxin: RMSEC = 12.27 μg/kg, RMSEP = 38.53 μg/kg), the MSA significantly improved the predictive performance of the regression models, with the number of selected variables being almost half of that in the SA. A comparison with other commonly used variable selection methods of selectivity ratio (low aflatoxin: RMSEC = 6.09 μg/kg, RMSEP = 13.75 μg/kg; high aflatoxin: RMSEC = 13.74 μg/kg, RMSEP = 41.13 μg/kg), unin�formative variable elimination (low aflatoxin: RMSEC = 0.32 μg/kg, RMSEP = 5.11 μg/kg; high aflatoxin: RMSEC = 3.80 μg/kg, RMSEP = 17.76 μg/kg), and variable importance in projection (low aflatoxin: RMSEC = 2.67 μg/kg, RMSEP = 10.71 μg/kg; high aflatoxin: RMSEC = 13.51 μg/kg, RMSEP = 32.53 μg/kg) also indicated the promising efficacy of the proposed MSA.
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spelling uthm-69042022-04-12T06:51:16Z http://eprints.uthm.edu.my/6904/ Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method Ong, Pauline Tung, I-Chun Ching, Feng Chiu I-Lin Tsai d ,, I-Lin Tsai d , Hsi, Chang Shih TK7800-8360 Electronics Direct quantification analysis of near-infrared (NIR) spectra is challenging because the number of spectral variables is usually considerably higher than the number of samples. To mitigate the so-called curse of dimensionality, var�iable selection is often performed before multivariate calibration. There has been much work in this regard, where the developed variable selection method can be categorized as individual variable selection, such as uninformative variable elimination or variable importance in projection, and continuous interval variable selection method such as interval partial least squares or moving window partial least squares. In this study, a new individual variable se�lection method, modified simulated annealing (MSA), was proposed and used in conjunction with the partial least squares regression (PLSR) model. The interpretability of the selected variables in the determination of aflatoxin B1 levels in white rice was assessed. The results revealed that the PLSR model combined with MSA not only yielded higher accuracy than the full-spectrum PLSR but also successfully shrank the variable space. The developed simplified PLSR model using MSA produced satisfactory performances, with root mean square error of calibration (RMSEC) of 0.11 μg/kg and 0.56 μg/kg, and root mean square error of prediction (RMSEP) of 7.16 μg/kg and 14.42 μg/kg, were obtained for the low-aflatoxin B1-level- and high-aflatoxin-B1-level samples, respectively. Specifically, the MSA-based models yielded improvements of 97.80% (calibration set) and 44.62% (prediction set) as well as 95.85% (calibration set) and 62.57% (prediction set) for both datasets when compared with the full-spectrum PLSR (low aflatoxin: RMSEC = 5.02 μg/kg, RMSEP = 12.93 μg/kg; high aflatoxin: RMSEC = 13.50 μg/kg, RMSEP = 38.53 μg/kg). Compared with the baseline method of simulated annealing (SA) (low aflatoxin: RMSEC = 0.21 μg/kg, RMSEP = 9.78 μg/kg; high aflatoxin: RMSEC = 12.27 μg/kg, RMSEP = 38.53 μg/kg), the MSA significantly improved the predictive performance of the regression models, with the number of selected variables being almost half of that in the SA. A comparison with other commonly used variable selection methods of selectivity ratio (low aflatoxin: RMSEC = 6.09 μg/kg, RMSEP = 13.75 μg/kg; high aflatoxin: RMSEC = 13.74 μg/kg, RMSEP = 41.13 μg/kg), unin�formative variable elimination (low aflatoxin: RMSEC = 0.32 μg/kg, RMSEP = 5.11 μg/kg; high aflatoxin: RMSEC = 3.80 μg/kg, RMSEP = 17.76 μg/kg), and variable importance in projection (low aflatoxin: RMSEC = 2.67 μg/kg, RMSEP = 10.71 μg/kg; high aflatoxin: RMSEC = 13.51 μg/kg, RMSEP = 32.53 μg/kg) also indicated the promising efficacy of the proposed MSA. Elsevier 2022 Article PeerReviewed text en http://eprints.uthm.edu.my/6904/1/J13942_fe1e071d4a672b5009a921fc69dc0ece.pdf Ong, Pauline and Tung, I-Chun and Ching, Feng Chiu and I-Lin Tsai d ,, I-Lin Tsai d , and Hsi, Chang Shih (2022) Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method. Food Control, 136. https://doi.org/10.1016/j.foodcont.2022.108886
spellingShingle TK7800-8360 Electronics
Ong, Pauline
Tung, I-Chun
Ching, Feng Chiu
I-Lin Tsai d ,, I-Lin Tsai d ,
Hsi, Chang Shih
Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method
title Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method
title_full Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method
title_fullStr Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method
title_full_unstemmed Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method
title_short Determination of aflatoxin B1 level in rice (Oryza sativa L.) through near-infrared spectroscopy and an improved simulated annealing variable selection method
title_sort determination of aflatoxin b1 level in rice (oryza sativa l.) through near-infrared spectroscopy and an improved simulated annealing variable selection method
topic TK7800-8360 Electronics
url http://eprints.uthm.edu.my/6904/
http://eprints.uthm.edu.my/6904/
http://eprints.uthm.edu.my/6904/1/J13942_fe1e071d4a672b5009a921fc69dc0ece.pdf

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