Biology and Life Sciences Forum (Oct 2023)

Functional Foods or Over-Hyped? Observations on the Antioxidant and Phenolic Content of Australian Foodstuffs

  • Joel B. Johnson,
  • Janice S. Mani,
  • Ryan J. Batley,
  • Beatriz E. Hoyos,
  • Nicola Novello,
  • Parbat Raj Thani,
  • Charitha Priyadarshani Ekanayake Arachchige,
  • Pasmita Neupane,
  • Mani Naiker

DOI
https://doi.org/10.3390/Foods2023-15085
Journal volume & issue
Vol. 26, no. 1
p. 17

Abstract

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Consumers are showing increasing awareness of the concept of ‘functional foods’: foods that can provide health benefits in addition to their nutritional value. There is particular demand for foods with a high antioxidant and phenolic content, which may improve cardiovascular health, reduce inflammation, and slow or prevent the onset of chronic, non-communicable diseases. However, there is a lack of comprehensive databases using consistent analytical protocols to analyze the antioxidant and phenolic content of different food types, particularly in regional areas such as Australia. Over the past four years, our laboratory has analyzed over 1000 food-related samples using several antioxidant capacity assays (ferric reducing antioxidant power—FRAP—and cupric reducing antioxidant capacity—CUPRAC), as well as the total phenolic content (TPC) using the Folin–Ciocalteu method. Here, we provide a summary of these data by different food types to inform researchers, policy planners, nutritionists, and consumers about the typical levels of antioxidants and total phenolics found across a range of Australian foodstuffs, particularly grains. The highest antioxidant and phenolic contents were typically found in native Australian fruits, while grains, nuts, and non-native fruits showed lower antioxidant and phenolic contents. Spices, processed foodstuffs, and non-fruit native Australian foods showed an intermediate content. Furthermore, medicinally used plants showed a much higher phenolic content and antioxidant capacity compared to non-medicinal plants. Finally, we present correlations between the various analytes.

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