Integrated Metabolomics and Machine Learning Reveal Drying-Dependent Phenolic Markers in Asteraceae Edible Plants From Ulleungdo Island.

Lee IY, Lee DH, Park JH, Joo N.

DOI: 10.1002/fsn3.72297
Published: 2026-09-02
Container: Food Sci Nutr
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1002/fsn3.72297,
  title = {Integrated Metabolomics and Machine Learning Reveal Drying-Dependent Phenolic Markers in Asteraceae Edible Plants From Ulleungdo Island.},
  author = {Lee IY and  Lee DH and  Park JH and  Joo N.},
  year = {2026},
  journal = {Food Sci Nutr},
  doi = {10.1002/fsn3.72297},
  url = {https://doi.org/10.1002/fsn3.72297}
}

RIS

TY  - JOUR
TI  - Integrated Metabolomics and Machine Learning Reveal Drying-Dependent Phenolic Markers in Asteraceae Edible Plants From Ulleungdo Island.
AU  - Lee IY
AU  -  Lee DH
AU  -  Park JH
AU  -  Joo N.
PY  - 2026
JO  - Food Sci Nutr
DO  - 10.1002/fsn3.72297
UR  - https://doi.org/10.1002/fsn3.72297
ER  -

APA

IY, L., DH, L., JH, P., & N., J. (2026). Integrated Metabolomics and Machine Learning Reveal Drying-Dependent Phenolic Markers in Asteraceae Edible Plants From Ulleungdo Island.. Food Sci Nutr. https://doi.org/10.1002/fsn3.72297

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europe-pmc · retrieved 2026-09-25T03:39:04.931Z