How Chemometrics Revives the UV-Vis Spectroscopy Applications as an Analytical Sensor for Spectralprint (Nontargeted) Analysis

被引:33
作者
Rios-Reina, Rocio [1 ]
Azcarate, Silvana M. [2 ]
机构
[1] Univ Seville, Fac Farm Area Nutr & Bromatol, C-P Garcia Gonzalez 2, Seville 41012, Spain
[2] Univ Nacl Pampa, Fac Ciencias Exactas & Nat, Inst Ciencias Tierra & Ambientales Pampa INCITAP C, Ave Uruguay 151, RA-L6300CLB Santa Rosa, Argentina
关键词
UV-Vis; chemometrics; spectralprint; quantification; pattern recognition; ULTRAVIOLET-VISIBLE SPECTROSCOPY; PATTERN-RECOGNITION; FLUORESCENCE SPECTROSCOPY; REFLECTANCE SPECTROSCOPY; OLIVE OILS; DISCRIMINATION; ADULTERATION; AUTHENTICATION; CLASSIFICATION; COMBINATION;
D O I
10.3390/chemosensors11010008
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In recent years, methodologies based on spectral analysis, using ultraviolet-visible (UV-Vis) radiation, have experienced an amazing development and have been widely applied in various fields such as agricultural, food, pharmaceutical, and environmental sciences. This straightforward technique has re-emerged with novel and challenging proposals to solve, in a direct and fast way, a wide variety of problems. These reaches would not have been possible without the essential support of chemometrics. In this sense, under the general background of the development in data and computer science, and other technologies, the emergence of innovative ideas, approaches, and strategies endows UV-Vis spectroscopy with a new vitality as an analytical sensor with the capability of significantly improving both the robustness and accuracy of results. This review presents modern UV-Vis spectral analysis, which is on the rise, associated with comprehensive chemometric methods that have become known in the last six years, especially from the perspective of practicability, including spectral preprocessing, wavelength (variable) selection, data dimension reduction, quantitative calibration, pattern recognition, and multispectral data fusion. Most importantly, it will foresee future trends of UV-Vis spectroscopy as an analytical sensor for a spectralprint (nontargeted) analysis.
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页数:22
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共 96 条
[11]   Model Optimization for the Prediction of Red Wine Phenolic Compounds Using Ultraviolet-Visible Spectra [J].
Beaver, Chris ;
Collins, Thomas S. ;
Harbertson, James .
MOLECULES, 2020, 25 (07)
[12]   WinMLR, a software program for the simultaneous determination of several components in mixtures using multilinear regression analysis [J].
Becerra, Eduardo ;
Danchana, Kaewta ;
Cerda, Victor .
TALANTA, 2020, 213
[13]   UV-Vis Spectroscopy and Chemometrics for the Monitoring of Organosolv Pretreatments [J].
Beisl, Stefan ;
Binder, Mathias ;
Varmuza, Kurt ;
Miltner, Angela ;
Friedl, Anton .
CHEMENGINEERING, 2018, 2 (04) :1-14
[14]   Application of Chemometrics Tools to the Study of the Fe(III)-Tannic Acid Interaction [J].
Berto, Silvia ;
Alladio, Eugenio .
FRONTIERS IN CHEMISTRY, 2020, 8
[15]  
Bian XH, 2020, ANAL METHODS-UK, V12, P3499, DOI [10.1039/d0ay00285b, 10.1039/D0AY00285B]
[16]   Feasibility of UV-VIS-Fluorescence spectroscopy combined with pattern recognition techniques to authenticate a new category of plant food supplements [J].
Boggia, Raffaella ;
Turrini, Federica ;
Anselmo, Marco ;
Zunin, Paola ;
Donno, Dario ;
Beccaro, Gabriele L. .
JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE, 2017, 54 (08) :2422-2432
[17]   Simultaneous determination of food colorants in liquid samples by UV-Visible spectroscopy and multivariate data analysis using a reduced calibration matrix [J].
Bordagaray, Ane ;
Davila, Sergio ;
Garcia-Arrona, Rosa ;
Vidal, Maider ;
Ostra, Miren .
JOURNAL OF CHEMOMETRICS, 2019, 33 (10)
[18]   Fast pattern recognition of malted and unmalted beer: An investigation using FTIR, UV-VIS, fluorescence spectroscopy and chemometrics [J].
Braga, Filipe Leoncio ;
Braga, Soraia .
SCIENTIA AGROPECUARIA, 2021, 12 (03) :361-367
[19]   Detection of vinegar adulteration with spirit vinegar and acetic acid using UV-visible and Fourier transform infrared spectroscopy [J].
Cavdaroglu, Cagri ;
Ozen, Banu .
FOOD CHEMISTRY, 2022, 379
[20]   From mono- to multicomponent methods in UV-VIS spectrophotometric and fluorimetric quantitative analysis e A review [J].
Cerda, Victor ;
Phansi, Piyawan ;
Ferreira, Sergio .
TRAC-TRENDS IN ANALYTICAL CHEMISTRY, 2022, 157