Screening of Indian bee pollen based on antioxidant properties and polyphenolic composition using UHPLC-DAD-MS/MS: A multivariate analysis and ANN based approach

Food Res Int. 2021 Feb:140:110041. doi: 10.1016/j.foodres.2020.110041. Epub 2020 Dec 24.

Abstract

The present investigation aims to examine the polyphenolic composition and antioxidant capacity of bee pollen samples procured from various regions of India. Total phenolic (TPC) and flavonoid (TFC) content ranged from 15.50 ± 1.25-25.63 ± 1.42 mg GAE/g and 9.72 ± 0.28-15.61 ± 0.74 mg RE/g, respectively. Coriander pollen showed the significantly (p < 0.05) higher antioxidant activity than other samples, demonstrated by DPPH radical scavenging activity (93.75 ± 0.05%), ferric reducing antioxidant power (103.98 ± 0.82 mmol Fe2+/g), ABTS+• radical scavenging activity (96.58 ± 0.65%) and metal chelating activity (84.62 ± 4.37%). The observed antioxidant properties were strongly correlated with TPC and effectively predicted using artificial neural network. Sixty polyphenolic compounds including 38 flavonoids and derivatives, 21 phenolic acid and derivatives and one glucosinolates were identified using UHPLC-DAD-MS/MS wherein the presence of daidzein and sinigrin was acknowledged for the first time. Further, principal component analysis identified three principal components, illustrating 91.24% of total variation to differentiate the pollen samples which were also classified by hierarchical cluster analysis.

Keywords: Antioxidant potential; Artificial neural network; Bee pollen; Polyphenolic composition; Principal component analysis; Total phenolic and flavonoid content.

MeSH terms

  • Animals
  • Antioxidants*
  • Bees
  • Chromatography, High Pressure Liquid
  • India
  • Multivariate Analysis
  • Pollen
  • Tandem Mass Spectrometry*

Substances

  • Antioxidants