Investigates phytochemical composition and biological activities of quinoa extracts under salt stress, suggesting therapeutic potential.
Background: This study investigated the effects of increasing levels of salinity on leaf phytochemical composition and the antioxidant, antidiabetic, and anti-obesity activities. Method: Three quinoa accessions grown under escalating NaCl treatments had their leaves exposed to various chemical analyses. Polyphenols, tannins, and flavonoids were among the phenolic substances whose concentrations were measured. The phenolic chemicals in the water extract were identified using HPLC-DAD-ESI-MS/MS. In vitro and in silico methods were used to measure anti-radical (DPPH), anti-alpha glucosidase, anti-alpha-amylase, and anti-lipase activities. Results: The results showed that water and ethanol, due to their polarity, were the most effective solvents for extracting phenolic compounds. Additionally, salt application led to a dose-dependent increase in total phenols (TPC), flavonoids (TFC), and tannins (CT) across all accessions. The accession DE-1 exhibited the highest contents with average values of 1453.03–4398.36 mg EGA/100 g DW, 322.7–1090.7 mg CAE/100 g DW, and 77.9–335.96 mg CAE/100 g DW of TPC, TFC, and Tannins, respectively. HPLC-ESI-DAD-MS/MS profiling of phenolic compounds led to identifying 18 constituents, including five major compounds (p-coumaric acid, caffeic acid, vanillic acid, p-coumaroyl hexose, and HHDP-galloyl glucose). Except for p-coumaroyl hexose and HHDP-galloyl glucose, which were extensively biosynthesized/accumulated in the salt-tolerant accession DE-1, the remaining phenolic compounds showed irregular evolution depending on accession and salt concentration. Moreover, ethanol and water extracts were evaluated for their anti-radical and enzyme-inhibitory activities. Conclusion: Salt-stressed DE-1 water extract showed strong antioxidant and enzyme inhibitory activities, indicating potential antidiabetic and anti-obesity effects. These activities were confirmed by in silico analysis.
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Arraouadi et al. (2026) studied this question.
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