Discrimination of conventional and organic rice using untargeted LC-MS-based metabolomics

作者：Xiao, Ran; Ma, Ying^*; Zhang, Dongjie; Qian, Lili

来源：Journal of Cereal Science, 2018, 82: 73-81.

DOI：10.1016/j.jcs.2018.05.012

• Organic rice
• Metabolite profiling
• UHPLC-QTOF MS
• Multivariate statistical analysis

A metabolite profiling method was developed for rice samples under conventional and organic agricultural practices. In this study, an ultra-high performance liquid chromatography combined with quadrupole time-of-flight MS based (UHPLC-QTOF based) metabolite approach in combination with multivariate statistical analyses, including principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA), was applied to determine metabolite patterns among rice samples. In addition, an orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied to identify key constituents to efficiently distinguish between cultivation methods. In total, 30 discriminant components were chosen from these two kinds of rice samples, in which 8 secondary metabolites could be considered to be potential biomarkers for the discrimination of organic and conventional rice. These results suggest that a metabolomics approach could be a reliable, precise, and effective method for the identification of rice under different cultivation practices.

• 出版日期2018-7
• 单位哈尔滨工业大学