FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners-Reference-Cited by-同舟云学术

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FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners

Published:2020-01 Issue: Volume:303 Page:125404
ISSN:0308-8146
Container-title:Food Chemistry
language:en
Short-container-title:Food Chemistry

Author:

Wang Yu-Tang,Li Bin,Xu Xiao-Juan,Ren Hai-Bin,Yin Jia-Yi,Zhu Hao,Zhang Ying-Hua

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

General Medicine,Food Science,Analytical Chemistry

Reference26 articles.

1. Application of mid-infrared spectroscopy and PLS-Kernel calibration for quick detection of pork in higher value meat mixes;Abu-Ghoush;Journal of Food Measurement and Characterization,2017

2. FTIR determination of aspartame and acesulfame-K in tabletop sweeteners;Armenta;Journal of Agricultural and Food Chemistry,2004

3. Partial least squares for discrimination;Barker;Journal of Chemometrics,2003

4. Blends of non-caloric sweeteners saccharin and cyclamate show reduced off-taste due to TAS2R bitter receptor inhibition;Behrens;Cell Chemical Biology,2017

5. Theoretical structural and vibrational properties of the artificial sweetener sucralose;Brizuela;Computational and Theoretical Chemistry,2013

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1. A homogeneous binary matrix assisted laser desorption/ionization time-of-flight mass spectrometry assay for determination of artificial sweeteners in beverages;Food Chemistry;2024-12

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3. Discrimination and quantification of volatile compounds in beer by FTIR combined with machine learning approaches;Food Chemistry: X;2024-06

4. Machine learning-assisted FTIR spectra to predict freeze-drying curve of food;LWT;2024-04

5. Seeking for non‐friendly chemical elements in tabletop sugar and zero to low‐calorie sweetener sachets;X-Ray Spectrometry;2024-01-09

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