Abstract

Two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS) is a powerful tool for identification of compounds in complex samples. Herein, we compared the GC × GC-TOFMS and GC-TOFMS systems for polar metabolite profiling of rice seeds. Forty-seven and thirty-six metabolites were detected in a Korean rice cultivar, Dongjin, using GC × GC-TOFMS and GC-TOFMS, respectively. The limits of detection of shikimic, p-coumaric, and sinapinic acids were 30.0-, 1.6-, and 2.5-times lower, respectively, with GC × GC-TOFMS than with GC-TOFMS. The overlapped peaks of glycerol and phosphoric acid in GC-TOFMS were separated in GC × GC-TOFMS. Polar metabolite profiling of two white and six red rice cultivars was performed using GC × GC-TOFMS and the obtained data were subjected to principal component analysis. Remarkably, principal component 1 separated Heugdaegu from other cultivars, indicating that Heugdaegu has high levels of caffeic, sinapinic, and vanillic acids. Findings from this work may aid breeding programs aimed at improving the quality of rice seeds.

Highlights

  • Polar primary metabolites are essential for vital activities of organisms

  • Comprehensive two-dimensional gas chromatography (GC × GC) is an advanced technique that improves the resolution of one-dimensional gas chromatography (GC)

  • The metabolic profiling data were analysed by principal component analysis (PCA) for comparing the metabolites among the eight rice cultivars

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Summary

Introduction

Polar primary metabolites are essential for vital activities of organisms. In contrast, secondary metabolites are not directly involved in the normal growth, development, and reproduction, but several such metabolites are present in plants for ecological purposes. Non-targeted profiling of polar metabolites in five brown cultivars was performed using GC × GC-TOFMS in combination with GC-TOFMS analysis for investigating the metabolite diversity of rice variants [10]. Non-targeted profiling of polar metabolites in grains of three rice cultivars was performed using GC-TOFMS and the results were compared with those obtained using GC × GC-TOFMS analysis for assessing the data processing and analysis methods [11].

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