Soria Ana Cristina, Martínez-Castro Isabel, Sanz Jesús
Instituto de Química Orgánica General (CSIC), Madrid, Spain.
J Chromatogr A. 2009 Apr 10;1216(15):3300-4. doi: 10.1016/j.chroma.2009.01.065. Epub 2009 Jan 29.
Data precision in the analysis by purge-and-trap coupled on-line to gas chromatography-mass spectrometry (P&T-GC-MS) of honey volatiles has been studied by statistical analysis. The contribution of non-random factors to dispersion of quantitative results was proven by comparing several statistical parameters (correlation coefficients, principal component analysis (PCA) eigenvalues and loadings) from both experimental and simulated data. PCA was also useful for grouping volatiles with similar dispersion behaviour; these groups being generally related to compounds with common properties or structural features. The use of area ratios improves data precision for compounds within the same group. Results from this study could be used for a better selection of internal standards in quantitative analysis of volatiles by P&T-GC-MS.
通过统计分析研究了吹扫捕集与气相色谱-质谱联用(P&T-GC-MS)分析蜂蜜挥发物时的数据精度。通过比较实验数据和模拟数据的几个统计参数(相关系数、主成分分析(PCA)特征值和载荷),证明了非随机因素对定量结果离散度的影响。PCA还可用于对具有相似离散行为的挥发物进行分组;这些组通常与具有共同性质或结构特征的化合物相关。使用面积比可提高同一组内化合物的数据精度。本研究结果可用于在P&T-GC-MS定量分析挥发物时更好地选择内标。