The identification of microplastics based on vibrational spectroscopy data- A critical review of data analysis routines

被引:26
作者
Weisser, Jana [1 ]
Pohl, Teresa [1 ,4 ]
Heinzinger, Michael [2 ]
Ivleva, Natalia P. [3 ]
Hofmann, Thomas [1 ]
Glas, Karl [1 ]
机构
[1] Tech Univ Munich, Chair Food Chem & Mol Sensory Sci, Lise Meitner Str 34, D-85354 Freising Weihenstephan, Germany
[2] Tech Univ Munich, Chair Bioinformat, Boltzmannstr 3, D-85748 Garching, Germany
[3] Tech Univ Munich, Chair Analyt Chem & Water Chem, Elisabeth Winterhalter Weg 6, D-81377 Munich, Germany
[4] Johann-Strauss-Str 8, Unterhaching, Germany
关键词
Microplastics; Fourier-transform Infrared spectroscopy; Raman spectroscopy; Hyperspectral imaging; Chemometrics; Machine learning; Database; Library; PLASTIC PARTICLES; SPECTRAL LIBRARIES; FTIR; MICROSPECTROSCOPY; MICROSCOPY; SYSTEM; URBAN; TOOL;
D O I
10.1016/j.trac.2022.116535
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
With worldwide aims to monitor microplastics (MP) in the environment, food and drinking water, there is a growing need for fast, reliable and high-throughput analysis methods. While on the instrumental side, spectroscopic techniques are used widely as they proved suitable for identifying even micron-range plastic particles, there is a gap to fill on the data analysis side. Vibrational spectra of MP are highly complex, and often, large data sets need to be evaluated. Methods range from classical library search to complex artificial intelligence models, each of which has its strengths and weaknesses. This critical review discusses the accuracy, robustness and expenditure of data analysis routines proposed for identification of MP using vibrational spectra. Programs provided by the scientific community dedicated to MP analysis are introduced. Thereby, this review aims to provide guidance for everyone who wants to set up or enhance a data analysis routine for vibrational spectra of MP.(c) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页数:15
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