A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis
Abstract
:1. Introduction
2. Results and Discussion
2.1. Spectral Features of LIBS and NIR
2.2. PLS-DA Model from LIBS Data
2.3. PLS-DA Model from NIR Data
2.4. PLS-DA Model from Data Fuion of LIBS and NIR
3. Materials and Methods
3.1. Sample Preparation
3.2. Sample Measurement
3.3. Spectral Pretreatment
3.4. Multivariate Analysis and Latent Variable Analysis
3.5. Data Fusion Strategy
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- National Pharmacopiea Committee. Pharmacopoeia of the People’S Republic of China, 1, 10th ed.; China Medical Science Press: Beijing, China, 2020; pp. 189–190.
- Li, X.; Shi, F.; Gong, L.; Hang, B.; Li, D.; Chi, L. Species-specific identification of collagen components in Colla corii asini using a nano-liquid chromatography tandem mass spectrometry proteomics approach. Int. J. Nanomed. 2017, 12, 4443–4454. [Google Scholar] [CrossRef]
- Zhang, S.; Xu, L.; Liu, Y.-X.; Fu, H.-Y.; Xiao, Z.-B.; She, Y.-B. Characterization of Aroma-Active Components and Antioxidant Activity Analysis of E-jiao (Colla Corii Asini) from Different Geographical Origins. Nat. Prod. Bioprosp. 2018, 8, 71–82. [Google Scholar] [CrossRef] [PubMed]
- Dong, W.-W.; Zeng, Z.-D.; Au, D.; Chan, C.-O.; Yang, D.-J.; Li, X.-B. Quality control of Colla corii asini using near-infrared spectroscopy and chemometrics clustering techniques. J. Food Drug Anal. 2012, 20, 152–158. [Google Scholar] [CrossRef]
- Li, W.-L.; Han, H.-F.; Zhang, L.; Zhang, Y.; Qu, H.-B. Manufacturer identification and storage time determination of “Dong’e Ejiao” using near infrared spectroscopy and chemometrics. J. Zhejiang Univ. Sci. B 2016, 17, 382–390. [Google Scholar] [CrossRef]
- Shen, L.; Chen, H.; Zhu, Q.; Wang, Y.; Wang, S.; Qian, J.; Wang, Y.; Qu, H. Identification of bioactive ingredients with immuno-enhancementand anti-oxidative effects from Fufang-Ejiao-Syrup by LC–MSn combined with bioassays. J. Pharm. Biomed. Anal. 2016, 117, 363–371. [Google Scholar] [CrossRef]
- Huang, H.; Liu, S.; Du, J.; Lin, J.; Liang, Q.; Liu, S.; Wei, Z. Structural analysis of glycosaminoglycans from Colla corii asini by liquid chromatography-electrospray ion trap mass spectrometry. Glycoconj. J. 2020, 37, 201–207. [Google Scholar] [CrossRef]
- Zhang, W.; Cui, S.; Cheng, X.-l.; Wei, F.; Ma, S. An optimized TaqMan real-time PCR method for authentication of ASINI CORII COLLA (donkey-hide gelatin). J. Pharm. Biomed. 2019, 170, 196–203. [Google Scholar] [CrossRef]
- De Queiroz Baddini, A.L.; de Paula Santos, J.L.V.; Tavares, R.R.; de Paula, L.S.; da Costa Araújo Filho, H.; Freitas, R. PLS-DA and data fusion of visible Reflectance, XRF and FTIR spectroscopy in the classification of mixed historical pigments. Spectrochim. Acta A Mol. Biomol. 2022, 265, 120384. [Google Scholar] [CrossRef]
- Liang, J.; Li, M.; Du, Y.; Yan, C.; Zhang, Y.; Zhang, T.; Zheng, X.; Li, H. Data fusion of laser induced breakdown spectroscopy (LIBS) and infrared spectroscopy (IR) coupled with random forest (RF) for the classification and discrimination of compound salvia miltiorrhiza. Chemometr. Intell. Lab. Syst. 2020, 207, 104179. [Google Scholar] [CrossRef]
- Song, X.-C.; Canellas, E.; Asensio, E.; Nerín, C. Predicting the antioxidant capacity and total phenolic content of bearberry leaves by data fusion of UV–Vis spectroscopy and UHPLC/Q-TOF-MS. Talanta 2020, 213, 120831. [Google Scholar] [CrossRef]
- Dai, S.; Lin, Z.; Xu, B.; Wang, Y.; Shi, X.; Qiao, Y.; Zhang, J. Metabolomics data fusion between near infrared spectroscopy and high resolution mass spectrometry: A synergetic approach to boost performance or induce confusion. Talanta 2018, 189, 641–648. [Google Scholar] [CrossRef]
- Hahn, D.W.; Omenetto, N. Laser-Induced Breakdown Spectroscopy (LIBS), Part II: Review of instrumental and methodogical approaches to material analysis and applications to different fields. Appl. Spectrosc. 2012, 66, 347–419. [Google Scholar] [CrossRef] [PubMed]
- Nagy, M.; Wang, S.P.; Farag, M. Quality analysis and authentication of nutraceuticals using near IR (NIR) spectroscopy: A comprehensive review of novel trends and applications. Trends Food Sci. Technol. 2022, 123, 290–309. [Google Scholar] [CrossRef]
- Guo, L.-B.; Zhang, D.; Sun, L.-X.; Yao, S.-C.; Zhang, L.; Wang, Z.-Z.; Wang, Q.-Q.; Ding, H.-B.; Lu, Y.; Hou, Z.-Y.; et al. Development in the application of laser-induced breakdown spectroscopy in recent years: A review. Front. Phys. 2021, 16, 22500. [Google Scholar] [CrossRef]
- Wang, Z.; Afgan, M.S.; Gu, W.; Song, Y.; Wang, Y.; Hou, Z.; Song, W.; Li, Z. Recent advances in laser-induced breakdown spectroscopy quantification: From fundamental understanding to data processing. Trends Analyt. Chem. 2021, 143, 116385. [Google Scholar] [CrossRef]
- Zhao, S.Y.; Song, W.R.; Hou, Z.Y.; Wang, Z. Classification of ginseng according to plant species, geographical origin, and age using laser-induced breakdown spectroscopy and hyperspectral imaging. J. Anal. At. Spectrom. 2021, 36, 1704–1711. [Google Scholar] [CrossRef]
- De Oliveira, D.M.; Fontes, L.M.; Pasquini, C. Comparing laser induced breakdown spectroscopy, near infrared spectroscopy, and their integration for simultaneous multi-elemental determination of micro- and macronutrients in vegetable samples. Anal. Chim. Acta 2019, 1062, 28–36. [Google Scholar] [CrossRef]
- Liu, X.; Che, X.; Li, K.; Wang, X.; Lin, Z.; Wu, Z.; Zheng, Q. Geographical authenticity evaluation of Mentha haplocalyx by LIBS coupled with multivariate analyzes. Plasma Sci. Technol. 2020, 22, 074006. [Google Scholar] [CrossRef]
- Chen, Q.; Lin, H.; Zhao, J. Near-infrared spectroscopy technology in food. In Advanced Nondestructive Detection Technologies in Food; Springer: Singapore, 2021. [Google Scholar]
- Tsuchikawa, S.; Ma, T.; Inagaki, T. Application of near-infrared spectroscopy to agriculture and forestry. Anal. Sci. 2022, 38, 635–642. [Google Scholar] [CrossRef]
- Wang, Y.; Yang, Y.; Sun, H.; Dai, J.; Zhao, M.; Teng, C.; Ke, Z.; Yang, M.; Zhong, L.; Zhu, W. Application of a data fusion strategy combined with multivariate statistical analysis for quantification of puerarin in Radix puerariae. Vib. Spectrosc. 2020, 108, 103057. [Google Scholar] [CrossRef]
- Tao, L.; Via, B.; Wu, Y.; Xiao, W.; Liu, X. NIR and MIR spectral data fusion for rapid detection of Lonicera japonica and Artemisia annua by liquid extraction process. Vib. Spectrosc. 2019, 102, 31–38. [Google Scholar] [CrossRef]
- Shen, T.; Li, W.; Zhang, X.; Kong, W.; Liu, F.; Wang, W.; Peng, J. High-Sensitivity Determination of Nutrient Elements in Panax notoginseng by Laser-induced Breakdown Spectroscopy and Chemometric Methods. Molecules 2019, 24, 1525. [Google Scholar] [CrossRef] [PubMed]
- Ma, L.; Liu, D.; Du, C.; Lin, L.; Zhu, J.; Huang, X.; Liao, Y.; Wu, Z. Novel NIR modeling design and assignment in process quality control of Honeysuckle flower by QbD. Spectrochim. Acta A Mol. Biomol. 2020, 242, 118740. [Google Scholar] [CrossRef] [PubMed]
- Fu, H.; Shi, Q.; Wei, L.; Xu, L.; Guo, X.; Hu, O.; Lan, W.; Xie, S.; Yang, T. Rapid Recognition of Geoherbalism and Authenticity of a Chinese Herb by Data Fusion of Near-Infrared Spectroscopy (NIR) and Mid-Infrared (MIR) Spectroscopy Combined with Chemometrics. J. Raman Spectrosc. 2019, 2019, 2467185. [Google Scholar] [CrossRef]
- Aints, M.; Paris, P.; Laan, M.; Piip, K.; Riisalu, H.; Tufail, I. Determination of Heating Value of Estonian Oil Shale by Laser-Induced Breakdown Spectroscopy. J. Spectrosc. 2018, 2018, 4605925. [Google Scholar] [CrossRef]
- Li, Z.; Song, J.; Ma, Y.; Yu, Y.; He, X.; Guo, Y.; Dou, J.; Dong, H. Identification of aged-rice adulteration based on near-infrared spectroscopy combined with partial least squares regression and characteristic wavelength variables. Food Chem. X 2023, 17, 100539. [Google Scholar] [CrossRef]
- Barker, M.; Rayens, W. Partial least squares for discrimination. J. Chemom. 2003, 17, 166–173. [Google Scholar] [CrossRef]
- De Oliveira, V.M.A.T.; Baqueta, M.; Março, P.; Valderrama, P. Authentication of organic sugars by NIR spectroscopy and partial least squares with discriminant analysis. Anal. Methods 2020, 12, 701–705. [Google Scholar] [CrossRef]
- Liu, X.; Zhang, Q.; Wu, Z.; Shi, X.; Zhao, N.; Qiao, Y. Rapid elemental analysis and provenance study of Blumea balsamifera DC using laser-induced breakdown spectroscopy. Sensors 2015, 15, 642–655. [Google Scholar] [CrossRef]
- Sun, F.; Chen, Y.; Wang, K.-Y.; Wang, S.-M.; Liang, S.-W. Identification of Genuine and Adulterated Pinellia ternata by Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopy with Partial Least Squares—Discriminant Analysis (PLS-DA). Anal. Lett. 2020, 53, 937–959. [Google Scholar] [CrossRef]
- Kramida, A.; Ralchenko, Y.; Reader, J.; NIST ASD Team. NIST Atomic Spectra Database (Version 5.10); National Institute of Standards and Technology: Gaithersburg, MD, USA, 2022. Available online: https://physics.nist.gov/asd (accessed on 10 February 2023). [CrossRef]
- Ozaki, Y. Near-Infrared Spectroscopy-Its Versatility in Analytical Chemistry. Anal. Sci. 2012, 28, 545–563. [Google Scholar] [CrossRef]
- Zhang, H.; Liu, Z.; Zhang, J.; Zhang, L.; Wang, S.; Wang, L.; Chen, J.; Zou, C.; Hu, J. Identification of Edible Gelatin Origins by Data Fusion of NIRS, Fluorescence Spectroscopy, and LIBS. Food Anal. Methods 2021, 14, 525–536. [Google Scholar] [CrossRef]
- Biancolillo, A.; Bucci, R.; Magrì, A.L.; Magrì, A.D.; Marini, F. Data fusion for multiplatform characterization of an Italian craft beer aimed at its authentication. Anal. Chim. Acta 2014, 820, 23–31. [Google Scholar] [CrossRef] [PubMed]
- Assis, C.; Gama, E.M.; Nascentes, C.C.; de Oliveira, L.S.; Anzanello, M.J.; Sena, M.M. A data fusion model merging information from near infrared spectroscopy and X-ray fluorescence. Searching for atomic-molecular correlations to predict and characterize the composition of coffee blends. Food Chem. 2020, 325, 126953. [Google Scholar] [CrossRef] [PubMed]
- Spiteri, M.; Dubin, E.; Cotton, J.; Poirel, M.; Corman, B.; Jamin, E.; Lees, M.; Rutledge, D. Data fusion between high resolution 1H-NMR and mass spectrometry: A synergetic approach to honey botanical origin characterization. Anal. Bioanal. Chem. 2016, 408, 4389–4401. [Google Scholar] [CrossRef]
- Sampaio, P.S.; Calado, C.R.C. Comparison of partial least squares-discriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on mid-infrared spectroscopy. J. Chemom. 2021, 35, e3340. [Google Scholar] [CrossRef]
Elements | Wavelength (nm) | Elements | Wavelength (nm) |
---|---|---|---|
C | 247.722 | Ba | 455.360, 493.385 |
Mg | 279.422, 280.124, 285.085, 383.825 516.730, 517.270, 518.359 | Fe | 526.987 |
Si | 288.031 | Na | 588.958, 589.551 |
Ca | 315.866, 317.921, 370.621, 393.378 396.814, 422.639, 428.287, 430.226 442.643, 443.500, 445.444, 558.850 | N | 742.400, 744.294, 746.927 |
612.923, 616.233, 643.966, 646.212 649.394, 714.856, 720.259 | Li | 670.746 | |
C-N | 385.461, 386.105, 387.087, 388.302 | H | 656.309 |
Al | 394.422, 396.096 | K | 766.515, 769.947 |
Sr | 407.786, 421.500 | O | 777.216, 777.505 |
Sample No. | Manufacturer |
---|---|
1–40 | Shandong Dong’e Ejiao Co., Ltd. Liaocheng city, Shandong, China |
41–48 | Shandong Huaxin Pharmaceutical Group Co., Ltd. Heze city, Shandong, China |
49–61 | Shandong Yanggu Guajing Ejiao factory Liaocheng city, Shandong, China |
62 | Shandong Dong’a Xiuyuan Ejiao biological group Neihuang Ejiao Pharmaceutical Co., Ltd. Anyang city, Henan, China |
63 | Shandong Jishui Ejiao Co., Ltd. Heze city, Shandong, China |
64–65 | Shandong Hongjitang Pharmaceutical Group Co., Ltd. Jinan city, Shandong, China |
66–72 | Shandong Dong’e Guojiaotang Ejiao Pharmaceutical Co., Ltd. Liaocheng city, Shandong, China |
73–75 | Shandong Fupai Ejiao Co., Ltd. Jinan city, Shandong, China |
76–78 | Shandong Yixiaotang Ejiao group Bainian Pharmaceutical Co., Ltd. Zaozhuang city, Shandong, China |
Pretreatment | LVs | Training Set | Testing Set | ||||
---|---|---|---|---|---|---|---|
Se (%) | Sp (%) | Ta (%) | Se (%) | Sp (%) | Ta (%) | ||
Raw | 7 | 100 | 100 | 100 | 93.33 | 100 | 96.3 |
MSC | 10 | 100 | 100 | 100 | 100 | 100 | 100 |
SNV | 7 | 100 | 100 | 100 | 100 | 92.86 | 96.3 |
SG9 | 9 | 100 | 100 | 100 | 82.35 | 100 | 88.89 |
1st d | 6 | 100 | 100 | 100 | 92.86 | 92.31 | 96.3 |
Pretreatment | LVs | Training Set | Testing Set | ||||
---|---|---|---|---|---|---|---|
Se (%) | Sp (%) | Ta (%) | Se (%) | Sp (%) | Ta (%) | ||
Raw | 7 | 96.15 | 96.15 | 98.04 | 93.33 | 100 | 96.3 |
MSC | 11 | 100 | 100 | 100 | 100 | 100 | 100 |
SNV | 10 | 100 | 100 | 100 | 100 | 100 | 100 |
SG9 | 13 | 100 | 100 | 100 | 82.35 | 100 | 88.89 |
1st d | 7 | 100 | 100 | 100 | 93.33 | 100 | 96.3 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Xia, Z.; Che, X.; Ye, L.; Zhao, N.; Guo, D.; Peng, Y.; Lin, Y.; Liu, X. A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis. Molecules 2023, 28, 1778. https://doi.org/10.3390/molecules28041778
Xia Z, Che X, Ye L, Zhao N, Guo D, Peng Y, Lin Y, Liu X. A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis. Molecules. 2023; 28(4):1778. https://doi.org/10.3390/molecules28041778
Chicago/Turabian StyleXia, Ziyi, Xiaoqing Che, Lei Ye, Na Zhao, Dongxiao Guo, Yanfang Peng, Yongqiang Lin, and Xiaona Liu. 2023. "A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis" Molecules 28, no. 4: 1778. https://doi.org/10.3390/molecules28041778
APA StyleXia, Z., Che, X., Ye, L., Zhao, N., Guo, D., Peng, Y., Lin, Y., & Liu, X. (2023). A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis. Molecules, 28(4), 1778. https://doi.org/10.3390/molecules28041778