|
|
|
|
|
|
Study on the Fractional Baseline Correction Method of ATR-FTIR
Spectral Signal in the Fermentation Process of Sodium Glutamate |
HE Nian, SHAN Peng*, HE Zhong-hai, WANG Qiao-yun, LI Zhi-gang, WU Zhui |
School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066000, China
|
|
|
Abstract In this paper, Attenuated Total Reflection Fourier Transformed Infrared Spectroscopy (ATR-FTIR) combined with the multivariate calibration model was used to realize the indirect measurement of the concentration of two main substrates (glucose and sodium glutamate) during the fermentation process of γ-polyglutamic acid (γ-PGA), which could provide feedback information for the fermentation process. The frequent baseline drift phenomenon in the spectrum measurement will seriously affect the performance of the subsequent multivariate calibration model, and it is necessary to use the baseline calibration algorithm to preprocess the spectrum. Most of the popular baseline correction algorithms are based on the Whittaker Smoother (WS) smoothing algorithm. And use integer-order differentials with limited expressive power to constrain the fitted baseline. Because of the poor adaptability of integer-order differential in the existing baseline correction algorithms, we use more flexible fractional-order differentials to constrain the baseline and then propose a baseline correction algorithm based on fractional-order, which realizes the extension of the integral order baseline correction. 5 batches of γ-PGA fermentation experiments were carried out, and the ATR-FTIR spectra of different batches and all batches were subjected to fractional baseline correction respectively; subsequently, the prediction accuracy of each model was improved to some extent. The experimental results show that only in batch 2 the baseline correction effect based on the integer-order is the best; the orders to obtain the best baseline correction effect for other batches were all fractional-order. Italso reflects that the constraint of the fractional-order derivative (including the integer-order derivative) on the baseline is reasonable. At the same time, it is found that the overall baseline correction effect of all batches is far worse than that of a single batch. The reason may be that the baseline of the spectra for each fermentation batch is different. Different orders need to be selected for different batches to achieve the best effect of baseline correction. In addition, the background spectrum was acquired with distilled water as the reference before measuring each γ-PGA fermentation sample. Anegative water peak thus inevitably appears in the wavenumber range of 3 100~3 600 cm-1 and forms harmful interference signals; the fractional baseline-corrected spectra show that the fractional-order baseline correction algorithm regards the negative water peak as the baseline and eliminates it to a certain extent. In summary, the fractional-order baseline correction algorithm expands the application range of the traditional integer-order baseline correction algorithm and provides a new solution to eliminate negative water peaks in the ATR spectra with water as the background spectrum.
|
Received: 2021-05-11
Accepted: 2021-07-29
|
|
Corresponding Authors:
SHAN Peng
E-mail: peng.shan@neuq.edu.cn
|
|
[1] Schorn-García D, Cavaglia J, Giussani B, et al. Microchemical Journal, 2021, 166: 106215.
[2] Pu Y Y, O’Donnell C, Tobin J T, et al. International Dairy Journal, 2020, 103: 104623.
[3] Cavaglia J, Schorn-García D, Giussani B, et al. Food Control, 2020, 109: 106947.
[4] Eilers P H C. Analytical Chemistry, 2003, 75: 3631.
[5] Eilers P, Boelens H. Baseline Correction with Asymmetric Least Squares Smoothing,Leiden University Medical Center Report 1, 2005.
[6] Zhang Zhimin, Chen Shan, Liang Yizeng. Analyst, 2010, 135(5): 1138.
[7] Baek S J, Park A, Ahn Y J, et al. Analyst, 2015, 140(1): 250.
[8] JIANG An, PENG Jiang-tao, XIE Qi-wei, et al(姜 安, 彭江涛, 谢启伟,等). Computers and Applied Chemistry(计算机与应用化学), 2012, 29(5): 537.
[9] He Shixuan, Zhang Wei, Liu Lijuan, et al. Anal. Methods, 2014.
[10] Xu D G, Liu S, Cai Y Y, et al. Applied Optics, 2019, 58(14): 3913.
[11] Ye Jianfeng, Tian Ziyang, Wei Haoyun, et al. Applied Optics, 2020, 59(34): 10933.
[12] Loverro A. Fractional Calculus: History, Definitions and Applications for the Engineer. Report, 2004, Corpus ID: 18520731.
[13] Hong Yongsheng, Liu Yaolin, Chen Yiyun, et al. Geoderma, 2019, 337: 758.
[14] Xia Zhenzhen, Yang Jie, Wang Jing, et al. Applied Spectroscopy, 2020, 74(4): 417.
[15] Fourie E, Aleixandre-Tudo J L, Mihnea M, et al. Food Control, 2020, 115: 107303.
|
[1] |
JIAO Qing-liang1, LIU Ming1*, YU Kun2, LIU Zi-long2, 3, KONG Ling-qin1, HUI Mei1, DONG Li-quan1, ZHAO Yue-jin1. Spectral Pre-Processing Based on Convolutional Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(01): 292-297. |
[2] |
XU Bo1, XU Tong-yu1, 2*, YU Feng-hua1, 2, ZHANG Guo-sheng1, FENG Shuai1, GUO Zhong-hui1, ZHOU Chang-xian1. Inversion Method for Cellulose Content of Rice Stem in Northeast Cold Region Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(06): 1775-1781. |
[3] |
LI Qing-bo1, BI Zhi-qi1, SHI Dong-dong2. The Method of Fishmeal Origin Tracing Based on EDXRF Spectrometry Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(03): 745-749. |
[4] |
LIU Long1, FAN Xian-guang1, 2*, KANG Zhe-ming1, WU Yi1, WANG Xin1, 2*. Baseline Correction Algorithm for Raman Spectroscopy Based on Adaptive Window Spline Fitting[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(01): 111-115. |
[5] |
LI Xin-xing1, LIANG Bu-wen1, BAI Xue-bing1, LI Na2*. Research Progress of Spectroscopy in the Detection of Soil Moisture Content[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(12): 3705-3710. |
[6] |
LÜ Mei-rong1, REN Guo-xing1, 2, LI Xue-ying1, FAN Ping-ping1, LIU Jie1, SUN Zhong-liang1, HOU Guang-li1, LIU Yan1*. The Effect of Spectral Pretreatment on the LSSVM Model of Nitrogen in Intertidal Sediments[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(08): 2409-2414. |
[7] |
ZHAO Man1, GUO Yi-xin1, HE Yu-qing1*, GUO Hong1, JIN Wei-qi1, REN Lin-mao1,2. Baseline Correction of UV Raman Spectrum Based on Improved Piecewise Linear Fitting[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(06): 1862-1868. |
[8] |
LUO Long-qiang1, YAO Xin-li1, HE Sai-ling1, 2*. Study on the Method of Determining the Survival Rate of Rice Seeds Based on Visible-Near Infrared Multispectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(01): 221-226. |
[9] |
TIAN An-hong1, 2, XIONG Hei-gang3, 4*, ZHAO Jun-san1, FU Cheng-biao1, 2. Mechanism Improvement for Pretreatment Accuracy of Field Spectra of Saline Soil Using Fractional Differential Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(08): 2495-2500. |
[10] |
HAO Yong1, SHANG Qing-yuan1, RAO Min2, HU Yuan2. Identification of Wood Species Based on Near Infrared Spectroscopy and Pattern Recognition Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(03): 705-710. |
[11] |
WU Xiao-ping1, GUAN Ye-peng1, 2*, LI Wei-dong3, LUO Hong-jie4. Visible-Near Infrared Spectroscopy Based Chronological Classification and Identification of Ancient Ceramic[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(03): 756-764. |
[12] |
WANG Xin1, 2, Lü Shi-long2, LI Yan2, WEI Hao-yun2, CHEN Xia3. Automatic Baseline Correction of Gas Spectra Based on Baseline Drift Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(12): 3946-3951. |
[13] |
ZHANG Ya-kun1, 2, 3, LUO Bin2, 3, PAN Da-yu2, 3, SONG Peng2, 3, LU Wen-chao2, 3, WANG Cheng2, 3, ZHAO Chun-jiang1, 2, 3*. [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(10): 3221-3230. |
[14] |
KE Ke1, 2, Lü Yong1, 2, YI Can-can1, 2, 3*. Improvement of Convex Optimization Baseline Correction in Laser-Induced Breakdown Spectral Quantitative Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2256-2261. |
[15] |
WANG Xin-qiang1,3, ZHANG Li-juan1,3, XIONG Wei2, ZHANG Wen-tao1,3, WANG Jie-jun1,3, YE Song1,3*. Study on Adaptive Baseline Correction of Spatial Heterodyne Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(09): 2933-2936. |
|
|
|
|