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Journal of chromatography. B, Analytical technologies in the biomedical and life sciences, 2022-12, Vol.1213, p.123521-123521, Article 123521
2022
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Details

Autor(en) / Beteiligte
Titel
Rapid screening of phenolic compounds in extracts of photosynthetic organisms separated using a C18 monolithic column based HPLC-UV method
Ist Teil von
  • Journal of chromatography. B, Analytical technologies in the biomedical and life sciences, 2022-12, Vol.1213, p.123521-123521, Article 123521
Ort / Verlag
Elsevier B.V
Erscheinungsjahr
2022
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • •A HPLC-UV method was developed to resolve and quantify 23 phenolic compounds from biological extracts.•Chlorogenic acid was the most abundant phenolic compound in blueberry fruit extracts (26.0 mg. kg−1)•Kaempferol was the most abundant phenolic compound in basil leaf extracts (61.4 mg. kg−1)•The same amount of starting biological material used to generate the plant extracts only allowed to putatively detect phenolic compounds in two microalgae species. The sourcing of novel bioactive compounds from bioresources has become a sustainability priority for several industrial sectors. Reliable methods are hence needed for the screening and identification of desired molecules in complex extracts. As such, phenolic compounds have attracted increasing interests due to their antioxidant potential. Here, a HPLC-UV based method was developed for the determination of phenolic compounds using a monolithic column. This allowed the separation of 23 phenolic compounds within 11 min. The method was ground proofed in terms of chromatographic parameters and applied to identify polyphenols in extracts of blueberries, basil and marine microalgae. The dominant polyphenols in blueberries and basil were chlorogenic acid (26.0 mg. kg -1) and kaempferol (61.4 mg. kg -1), respectively, while the microalgae used only contained trace amounts of polyphenols. This study demonstrates the value of our new HPLC method to rapidly screen extracts and identify polyphenols from biological matrices.
Sprache
Englisch
Identifikatoren
ISSN: 1570-0232
eISSN: 1873-376X
DOI: 10.1016/j.jchromb.2022.123521
Titel-ID: cdi_proquest_miscellaneous_2740909447

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