Multi-Way Analysis Coupled with Near-Infrared Spectroscopy in Food Industry: Models and Applications

Overview

Journal Foods

Specialty Biotechnology

Date 2021 Apr 30

PMID 33917964

Citations 10

Authors

Huiwen Yu

Lili Guo

Mourad Kharbach

Wenjie Han

Affiliations

Soon will be listed here.

Abstract

Near-infrared spectroscopy (NIRS) is a fast and powerful analytical tool in the food industry. As an advanced chemometrics tool, multi-way analysis shows great potential for solving a wide range of food problems and analyzing complex spectroscopic data. This paper describes the representative multi-way models which were used for analyzing NIRS data, as well as the advances, advantages and limitations of different multi-way models. The applications of multi-way analysis in NIRS for the food industry in terms of food process control, quality evaluation and fraud, identification and classification, prediction and quantification, and image analysis are also reviewed. It is evident from this report that multi-way analysis is presently an attractive tool for modeling complex NIRS data in the food industry while its full potential is far from reached. The combination of multi-way analysis with NIRS will be a promising practice for turning food data information into operational knowledge, conducting reliable food analyses and improving our understanding about food systems and food processes. To the best of our knowledge, this is the first paper that systematically reports the advances on models and applications of multi-way analysis in NIRS for the food industry.

Citing Articles

The Role of Near-Infrared Spectroscopy in Food Quality Assurance: A Review of the Past Two Decades.

Fodor M, Matkovits A, Benes E, Jokai Z Foods. 2024; 13(21).

PMID: 39517284 PMC: 11544831. DOI: 10.3390/foods13213501.

Hyperspectral imaging as a non-destructive technique for estimating the nutritional value of food.

Marin-Mendez J, Luri Esplandiu P, Alonso-Santamaria M, Remirez-Moreno B, Urtasun Del Castillo L, Echavarri Dublan J Curr Res Food Sci. 2024; 9:100799.

PMID: 39040225 PMC: 11261282. DOI: 10.1016/j.crfs.2024.100799.

Determination of Carbohydrate Composition in Lentils Using Near-Infrared Spectroscopy.

Lopez-Calabozo R, Liberal A, Fernandes A, Revilla I, Ferreira I, Barros L Sensors (Basel). 2024; 24(13).

PMID: 39001010 PMC: 11244296. DOI: 10.3390/s24134232.

Tensor methods in data analysis of chromatography/mass spectroscopy-based plant metabolomics.

Guo L, Yu H, Li Y, Zhang C, Kharbach M Plant Methods. 2023; 19(1):130.

PMID: 37990220 PMC: 10662285. DOI: 10.1186/s13007-023-01105-y.

Near-infrared spectroscopy of low-transmittance samples by a high-power time-stretch spectrometer using an arrayed waveguide grating (AWG).

Kawagoe H, Sera H, Sahara J, Akai S, Watanabe K, Shinoyama K Sci Rep. 2023; 13(1):17261.

PMID: 37828139 PMC: 10570277. DOI: 10.1038/s41598-023-44359-1.

References

Kharbach M, Yu H, Kamal R, Barra I, Marmouzi I, Cherrah Y . New insights into the Argan oil categories characterization: Chemical descriptors, FTIR fingerprints, and chemometric approaches. Talanta. 2021; 225:122073. DOI: 10.1016/j.talanta.2020.122073. View

Yang R, Liu R, Dong G, Xu K, Yang Y, Zhang W . Two-dimensional hetero-spectral mid-infrared and near-infrared correlation spectroscopy for discrimination adulterated milk. Spectrochim Acta A Mol Biomol Spectrosc. 2015; 157:50-54. DOI: 10.1016/j.saa.2015.12.017. View

Chen J, Qi J, Chen C, Chen J, Liu L, Gao R . Tocilizumab-Conjugated Polymer Nanoparticles for NIR-II Photoacoustic-Imaging-Guided Therapy of Rheumatoid Arthritis. Adv Mater. 2020; 32(37):e2003399. DOI: 10.1002/adma.202003399. View

Zhao J, Tian G, Qiu Y, Qu H . Rapid quantification of active pharmaceutical ingredient for sugar-free Yangwei granules in commercial production using FT-NIR spectroscopy based on machine learning techniques. Spectrochim Acta A Mol Biomol Spectrosc. 2020; 245:118878. DOI: 10.1016/j.saa.2020.118878. View

Basile T, Marsico A, Perniola R . NIR Analysis of Intact Grape Berries: Chemical and Physical Properties Prediction Using Multivariate Analysis. Foods. 2021; 10(1). PMC: 7827816. DOI: 10.3390/foods10010113. View

Tucker L . Some mathematical notes on three-mode factor analysis. Psychometrika. 1966; 31(3):279-311. DOI: 10.1007/BF02289464. View

Qiu Z, Zhao S, Feng X, He Y . Transfer learning method for plastic pollution evaluation in soil using NIR sensor. Sci Total Environ. 2020; 740:140118. DOI: 10.1016/j.scitotenv.2020.140118. View

Liu J, Han J, Xie J, Wang H, Tong W, Ba Y . Assessing heavy metal concentrations in earth-cumulic-orthic-anthrosols soils using Vis-NIR spectroscopy transform coupled with chemometrics. Spectrochim Acta A Mol Biomol Spectrosc. 2019; 226:117639. DOI: 10.1016/j.saa.2019.117639. View

Naethe P, Delaney M, Julitta T . Changes of NOx in urban air detected with monitoring VIS-NIR field spectrometer during the coronavirus pandemic: A case study in Germany. Sci Total Environ. 2020; 748:141286. PMC: 7383166. DOI: 10.1016/j.scitotenv.2020.141286. View

10.

Vigni M, Cocchi M . Near infrared spectroscopy and multivariate analysis to evaluate wheat flour doughs leavening and bread properties. Anal Chim Acta. 2013; 764:17-23. DOI: 10.1016/j.aca.2012.12.018. View

11.

Desai P, Acharya S, Armstrong C, Wu E, Zaidi S . Underpinning mechanistic understanding of the segregation phenomena of pharmaceutical blends using a near-infrared (NIR) spectrometer embedded segregation tester. Eur J Pharm Sci. 2020; 154:105516. DOI: 10.1016/j.ejps.2020.105516. View

12.

Puertas G, Vazquez M . Fraud detection in hen housing system declared on the eggs' label: An accuracy method based on UV-VIS-NIR spectroscopy and chemometrics. Food Chem. 2019; 288:8-14. DOI: 10.1016/j.foodchem.2019.02.106. View

13.

Rosa L, Goncalves T, Gomes S, Matsushita M, Goncalves R, Marco P . N-Way NIR Data Treatment through PARAFAC in the Evaluation of Protective Effect of Antioxidants in Soybean Oil. Molecules. 2020; 25(19). PMC: 7583810. DOI: 10.3390/molecules25194366. View

14.

Feng L, Zhu S, Liu F, He Y, Bao Y, Zhang C . Hyperspectral imaging for seed quality and safety inspection: a review. Plant Methods. 2019; 15:91. PMC: 6686453. DOI: 10.1186/s13007-019-0476-y. View

15.

Tian K, Wu L, Min S, Bro R . Geometric search: A new approach for fitting PARAFAC2 models on GC-MS data. Talanta. 2018; 185:378-386. DOI: 10.1016/j.talanta.2018.03.088. View

16.

Tiwari R, Shinde P, Sreedharan S, Dey A, Vallis K, Mhaske S . Photoactivatable prodrug for simultaneous release of mertansine and CO along with a BODIPY derivative as a luminescent marker in mitochondria: a proof of concept for NIR image-guided cancer therapy. Chem Sci. 2021; 12(7):2667-2673. PMC: 8179275. DOI: 10.1039/d0sc06270g. View

17.

Andrade L, Farhat I, Aeberhardt K, Bro R, Engelsen S . Modeling of temperature-induced near-infrared and low-field time-domain nuclear magnetic resonance spectral variation: chemometric prediction of limonene and water content in spray-dried delivery systems. Appl Spectrosc. 2009; 63(2):141-52. DOI: 10.1366/000370209787392094. View

18.

Rosa L, Coqueiro A, Marco P, Valderrama P . Thermal rice oil degradation evaluated by UV-Vis-NIR and PARAFAC. Food Chem. 2018; 273:52-56. DOI: 10.1016/j.foodchem.2018.03.065. View

19.

Alcala M, Ropero J, Vazquez R, Romanach R . Deconvolution of chemical and physical information from intact tablets NIR spectra: two- and three-way multivariate calibration strategies for drug quantitation. J Pharm Sci. 2008; 98(8):2747-58. DOI: 10.1002/jps.21634. View

20.

Truong V, Dupont M, Elbourne A, Gangadoo S, Rajapaksha Pathirannahalage P, Cheeseman S . From Academia to Reality Check: A Theoretical Framework on the Use of Chemometric in Food Sciences. Foods. 2019; 8(5). PMC: 6560398. DOI: 10.3390/foods8050164. View