Retention index based approach for simulation of results and application for validation of compound identification in...

In this work, first and second dimensional retention index (¹I and ²I) based calculation approach is established to simulate peak retention times (¹t_R and ²t_R) of samples for the given sets of volatile compounds in comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS). For the result without ¹t_R and ²t_R data of alkane references (¹t_R(n) and ²t_R(n)), the following steps were applied: (1) curve fitting based on van den Dool and Kratz relationship in order to simulate ¹t_R(n) using a training set of volatile compounds in a sample with their experimental ¹t_R data, and (2) simulation of ²t_R(n) at different ¹t_R(n) to construct their isovolatility curves based on a nonlinear equation with p₁-p₅ parameters and a constant (within the ranges of -0.0052 to 0.0049, -0.6181 to -0.0230, -26.4775 to -0.2698, 0.0050 to 9.6259, -7.2976 to -3.9524 and 0.9157 to 4.0779, respectively). These parameters were obtained by performing curve fitting according to the experimental ²t_R data of the same training set with the least square values ranging from 4.58×10^-15 to 32.55. Simulation of ¹t_R and ²t_R of target analytes (¹t_R,sim and ²t_R,sim) with known ¹I and ²I were performed using ¹t_R(n) and the simulated isovolatility curves. All the calculations and curve fittings were carried out by using Solver in Microsoft Excel. The approach was applied to simulate results for 542 compounds in several samples including analysis of saffron (Crocus sativas L.), Boswellia papyrifera, acacia honey and incense powder/smoke, perfume and cannabis either reported from literature or from the experiments in this work using different experimental approaches. These were compared with the experimental data showing correlation with the R² ranges of 0.98-1.00 and 0.80-0.97 for ¹t_R and ²t_R, respectively. This approach was then applied to propose 6 compounds which may be incorrectly identified based on the differences of >2 times of the standard deviations between ²t_R,sim and the experimental ²t_R in both residue and leave-one-out analyses.