Lim Dong Kyu, Long Nguyen Phuoc, Mo Changyeun, Dong Ziyuan, Lim Jongguk, Kwon Sung Won
Seoul National University, Research Institute of Pharmaceutical Sciences and College of Pharmacy, Seoul 08826, Korea.
Rural Development Administration, National Institute of Agricultural Sciences, Jeonju 54875, Korea.
J AOAC Int. 2018 Mar 1;101(2):498-506. doi: 10.5740/jaoacint.17-0158. Epub 2017 Jul 31.
In this study, we examined the effects of different extraction methods for the GC-MS- and LC-MS-based metabolite profiling of white rice (Oryza sativa L.). In addition, the metabolite divergence of white rice cultivated in either Korea or China was also evaluated. The discrimination analysis of each extraction method for white rice from Korea and China and the corresponding discriminatory markers were estimated by unpaired t-test, principal component analysis, k-means cluster analysis, partial least-squares discriminant analysis (PLS-DA), and random forest (RF). According to the prediction parameters obtained from PLS-DA and RF classifiers as well as features that could be identified, the extraction method using 75% isopropanol heated at 100°C coupled with LC-MS analysis was confirmed to be superior to the other extraction methods. Noticeably, lysophospholipid concentrations were significantly different in white rice between Korea and China, and they are novel markers for geographical discrimination. In conclusion, our study suggests an optimized extraction and analysis method as well as novel markers for the geographical discrimination of white rice.
在本研究中,我们考察了不同提取方法对基于气相色谱 - 质谱联用(GC-MS)和液相色谱 - 质谱联用(LC-MS)的白米(Oryza sativa L.)代谢物谱分析的影响。此外,还评估了韩国或中国种植的白米的代谢物差异。通过非配对t检验、主成分分析、k均值聚类分析、偏最小二乘判别分析(PLS-DA)和随机森林(RF)对来自韩国和中国的白米的每种提取方法进行判别分析,并估计相应的判别标记。根据从PLS-DA和RF分类器获得的预测参数以及可识别的特征,证实100°C加热的75%异丙醇结合LC-MS分析的提取方法优于其他提取方法。值得注意的是,韩国和中国白米中的溶血磷脂浓度存在显著差异,它们是地理判别的新标记。总之,我们的研究提出了一种优化的提取和分析方法以及用于白米地理判别的新标记。