Rapid measurement of indole levels in Brassica vegetables using one millilitre binary organic extraction solvent and capillary electrophoresis-UV analysis

Suparman, Suparman and Prawpan, Inpota and Apichai, Phonchai and Prapin, Wilairat and Rattikan, Chantiwas (2019) Rapid measurement of indole levels in Brassica vegetables using one millilitre binary organic extraction solvent and capillary electrophoresis-UV analysis. ARTIKEL JURNAL.

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Abstract

Introduction: Brassica vegetables contain high levels of indole compounds which have been found to provide health benefits, especially as cancer-preventive agents. An efficient and rapid method using solvent extraction with capillary electrophoresis (CE) and ultraviolet (UV) detection was developed for the determination of four major indoles from four types of Brassica vegetables. Materials and Methods: Freeze-dried samples of four Brassica vegetables, i.e. broccoli, cauliflower, Chinese cabbage and cabbage, were selected. Hence, 1 mL of the binary solvent dimethylformamide (DMF)–methanol, 4:1 (v/v), was used for sample extraction. The extracts were diluted with the running buffer and directly analysed using CE with UV detection of four indole compounds. Results: The binary solvent DMF–methanol, 4:1 (v/v) was selected from studies of the extraction efficiency of standard indoles spiked in ivy gourd (as the negative control sample) and using diphenylamine as the internal standard. Recovery was 80(±10)–120(±3)% for the four indoles: indole-3-carbinol (I3C), indole-3-acetonitrile (I3A), indole-3-acetic acid (IAA), and 3,3 -diindolylmethane (DIM). For direct analysis suitable dilution of the extract with the running buffer was required. The linear range of the quantitation is 0.75–25.0 μg/mL, limit of detection (LOD) of 0.14–0.52 μg/mL and r 2 0 > 0.998. The amount of indole in the Brassica vegetables are in the order I3C > > IAA, I3A > DIM. Conclusion: A rapid method for extraction and quantitation of four indoles in four Brassica vegetables using CE with UV detection was developed. It has the potential as an efficient technique for generating data for use in agricultural and nutritional studies.

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