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利用分子描述符的主成分估计香稻中挥发性代谢物在气相色谱/质谱联用仪中的保留时间

Estimation of Retention Time in GC/MS of Volatile Metabolites in Fragrant Rice Using Principle Components of Molecular Descriptors.

作者信息

Wijit Nataporn, Prasitwattanaseree Sukon, Mahatheeranont Sugunya, Wolschann Peter, Jiranusornkul Supat, Nimmanpipug Piyarat

机构信息

Department of Chemistry and Center of Excellence for Innovation in Chemistry, Faculty of Science and Graduate School, Chiang Mai University.

Department of Statistics, Faculty of Science, Chiang Mai University.

出版信息

Anal Sci. 2017;33(11):1211-1217. doi: 10.2116/analsci.33.1211.

Abstract

A quantitative structure-retention relationship (QSRR) study was applied for an estimation of retention times of secondary volatile metabolites in Thai jasmine rice. In this study, chemical components in rice seed were extracted using solvent extraction, then separated and identified by gas chromatography-mass spectrometry (GC-MS). A set of molecular descriptors was generated for these substances obtained from GC-MS analysis to numerically represent the molecular structure of such compounds. Principal component analysis (PCA) and principal component regression analysis (PCR) were used to model the retention times of these compounds as a function of the theoretically derived descriptors. The best fitted regression model was obtained with R-squared of 0.900. The informative chemical properties related to retention time were elucidated. The results of this study demonstrate clearly that the combination of molecular weight and autocorrelation functions of two dimensional interatomic distance, which are molecular polarizability, atom identity, sigma charge, sigma electronegativity and polarizability, can be considered as comprehensive factors for predicting the retention times of volatile compounds in rice.

摘要

采用定量结构-保留关系(QSRR)研究来估算泰国香米中次生挥发性代谢物的保留时间。在本研究中,使用溶剂萃取法提取水稻种子中的化学成分,然后通过气相色谱-质谱联用仪(GC-MS)进行分离和鉴定。为从GC-MS分析中获得的这些物质生成了一组分子描述符,以数字方式表示此类化合物的分子结构。主成分分析(PCA)和主成分回归分析(PCR)用于将这些化合物的保留时间建模为理论推导描述符的函数。获得了最佳拟合回归模型,决定系数R²为0.900。阐明了与保留时间相关的信息性化学性质。本研究结果清楚地表明,分子量和二维原子间距离的自相关函数(即分子极化率、原子特性、σ电荷、σ电负性和极化率)的组合可被视为预测水稻中挥发性化合物保留时间的综合因素。

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