HPLC-QTOF-MS-based chemical Profiling and antioxidant activity of Qatari propolis

The chemical composition of propolis (a phytochemical-rich, health-promoting bee product) varies highly with region and season, necessitating its thorough characterization. In this study, the chemical profiling of Qatari propolis (QP) was investigated using HPLC-QTOF-MS, along with its antioxidant activity in the ABTS assay. The yield of QP hydroalcoholic extracts (70%), their total flavonoid content (TFC), and total phenolic content (TPC) were in the ranges of 7.83–33.47%, 4.2–21.6%, and 3–14%, respectively. With increasing extract yield, the amount of TFC and TPC also increased. However, the observed promising antioxidant activity of QP samples was not linked to their TPC and TFC, probably because it depends on phenolic and flavonoid composition rather than their quantities. In the QP samples, compounds from different classes, such as flavonoids, fatty acyl glycosides, peptides, monoacyl glycerols, alkaloids, amino glycosides, cinnamic acids and derivatives, coumarins, phenolic glycosides, fatty amides, fatty acids, and derivatives were identified. Among these, flavonoids was the largest class, of which more than half of the compounds were prenylated flavonoids. This highlights the presence of prenylated flavonoids as a unique characteristic of QP. Altogether, QP samples could be a unique natural ingredient for the healthcare and food sectors.

Authors

Institutions

Publication Details

Journal
International Journal of Food Properties
Published
2025-12-12
DOI
https://doi.org/10.1080/10942912.2025.2602276
Citations
1
Primary Topic
Bee Products Chemical Analysis
Type
article
Field-Weighted Citation Impact
1.67
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

HPLC-QTOF-MS-based chemical Profiling and antioxidant activity of Qatari propolis

Mohammed Alsafran, Deepak M. Kasote
1 citations
International Journal of Food Properties
Bee Products Chemical Analysis
1.67
article

HPLC-QTOF-MS-based chemical Profiling and antioxidant activity of Qatari propolis

Mohammed Alsafran, Deepak M. Kasote
article en
1 citations

Abstract

The chemical composition of propolis (a phytochemical-rich, health-promoting bee product) varies highly with region and season, necessitating its thorough characterization. In this study, the chemical profiling of Qatari propolis (QP) was investigated using HPLC-QTOF-MS, along with its antioxidant activity in the ABTS assay. The yield of QP hydroalcoholic extracts (70%), their total flavonoid content (TFC), and total phenolic content (TPC) were in the ranges of 7.83–33.47%, 4.2–21.6%, and 3–14%, respectively. With increasing extract yield, the amount of TFC and TPC also increased. However, the observed promising antioxidant activity of QP samples was not linked to their TPC and TFC, probably because it depends on phenolic and flavonoid composition rather than their quantities. In the QP samples, compounds from different classes, such as flavonoids, fatty acyl glycosides, peptides, monoacyl glycerols, alkaloids, amino glycosides, cinnamic acids and derivatives, coumarins, phenolic glycosides, fatty amides, fatty acids, and derivatives were identified. Among these, flavonoids was the largest class, of which more than half of the compounds were prenylated flavonoids. This highlights the presence of prenylated flavonoids as a unique characteristic of QP. Altogether, QP samples could be a unique natural ingredient for the healthcare and food sectors.

International Journal of Food PropertiesVol. 29(1)
Qatar University (QA)
Openalex Percentile: Top 12%
Bee Products Chemical Analysis
1.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.