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

Research article (Food Chemistry, 2019) · cited 64× · AI/ML
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FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners

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FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners. Retrieved May 24, 2026, from https://4ort.xyz/entity/ftir-spectroscopy-coupled-with-machine-learning-approaches-as-a-rapid-tool-for-identification-and-quantification-of-arti
MLA “FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/ftir-spectroscopy-coupled-with-machine-learning-approaches-as-a-rapid-tool-for-identification-and-quantification-of-arti.
BibTeX @misc{4ortxyz_ftir-spectroscopy-coupled-with-machine-learning-approaches-as-a-rapid-tool-for-identification-and-quantification-of-arti_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners}}, year = {2026}, url = {https://4ort.xyz/entity/ftir-spectroscopy-coupled-with-machine-learning-approaches-as-a-rapid-tool-for-identification-and-quantification-of-arti}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners — https://4ort.xyz/entity/ftir-spectroscopy-coupled-with-machine-learning-approaches-as-a-rapid-tool-for-identification-and-quantification-of-arti (retrieved 2026-05-24)

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