Home ›
Entities
› academia
› FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners
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
FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners
Summary
FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners is a scholarly article[1].
Key Facts
FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.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 promptAccording 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)