Evaluation of Fourier deconvolution ion mobility spectrometer as high-performance gas chromatography detector for the analysis of plant extract flavors.

The Fourier deconvolution ion mobility spectrometer (FDIMS) offers multiplexing and improves the resolving power and signal-to-noise ratio. To evaluate the FDIMS as a detector for gas chromatography for the analysis of complex samples, we connected a drift tube ion mobility spectrometer to a commercial gas chromatograph and compared the performance including resolving power, sensitivity, and linear range using 2,6-di­tert-butylpyridine. Mixed standards were also injected into the tandem system to evaluate the performance under optimized conditions. A complex plant extract sample used as natural flavoring was investigated using the resulting system. The results show that the instrument implemented with the Fourier deconvolution multiplexing method demonstrated higher performance over the traditional signal averaging method including higher resolving power, better limit of detection, and wider linear range for a variety of compounds and natural plant extract flavorings.

Predicting minty compounds binary mixtures' pleasantness by odor intensity in aqueous solutions.

The aroma of mint is well-liked by the public, and key flavor odorants in mint aroma had been found, but how these molecules interact and form a satisfying odor remains a challenge. Quality, intensity, and pleasantness are our most basic perceptions of aromas; both intensity and pleasantness can be quantified. However, compared to intensity, research on pleasantness was lacking. Pleasantness was one of the most important indicators for formulating a satisfying mint flavor, and the study of binary mixtures was fundamental to our understanding of more complex mixtures. Therefore, the purpose of this study was to explore the characteristics of pleasantness as a function of concentration and, at the same time, to investigate the relationship between intensity and pleasantness in binary mixtures. Thirty sensory evaluation volunteers participated in the evaluation of the intensity and pleasantness of six key flavor odorants of mint and five binary mixtures. The results showed that the pleasantness increased first and then decreased or stabilized with the rising of concentration; even though the interactions in binary mixtures were not the same, their pleasantness could be predicted using the intensities of the components by Response Surface Design of Experiments, and the goodness of fit was greater than 0.92, indicating that the models had the great predictive ability. PRACTICAL APPLICATION: Whether blending flavors or evaluating them, a great deal of experience is required, yet the acquisition of this experience is a long process. Performing these tasks is difficult for the novice, and it helps to quantify the feeling for the flavor and build some mathematical models.

[Gas chromatography-mass spectrometry data analysis algorithm based on sparse model and its application in resolving severely overlapped peaks].

A Gas chromatography-mass spectrometry (GC-MS) data analysis algorithm is proposed. The mass spectrum at the top of the chromatographic peak is the spectrum to be solved. A certain amount of related reference spectra is retrieved from the spectral library, then, the equation of the chromatographic response value of each pure component is solved. A step by step strategy is used for the mass spectra retrieval. Firstly, an efficient indexing technology is used for rough selection, then, the "strong peak out with high probability" and the "extrusion" rules are used to exclude more unrelated mass spectra. A regression algorithm based on a sparse model is proposed to solve the equation of the chromatographic response value. Compared with the traditional algorithm, this algorithm can extract the main structure of the spectrum to be solved, and avoid over-fitting. The experimental results show that the proposed algorithm has a higher accuracy and smaller residual reference spectrum set, and the sparse model achieves satisfactory experimental results in the analysis of severely overlapped peaks. The proposed method provides an effective solution for resolving overlapped peaks, especially severely overlapped peaks, in GC-MS data.

[Simultaneous determination of 23 ester compounds in cigarette water-borne adhesives by liquid-liquid extraction and gas chromatography-mass spectrometry].

A method of gas chromatography-mass spectrometry (GC-MS) with liquid-liquid extraction has been developed for the simultaneous determination of 23 ester compounds including acetate esters, acrylic esters, metacrylic acid esters and phthalate acid esters in cigarette water-borne adhesives. After dispersed in water, the sample was extracted by n-hexane solution containing phenyl ethyl propionate as internal standard substance. Then, the solution was centrifuged and filtrated through a 0.45 microm organic membrane filter. Finally, the solution was separated on a DB-WAXETR column (60 m x 0.25 mm x 0.25 microm), and detected with MS in selected ion monitoring mode, and quantified by internal standard method. The results showed a good linear correlation in the range of 0.4-50.0 mg/L. The recoveries of the ester compounds spiked in the sample were 81.8%-109.1%, and the relative standard deviations (RSDs, n = 5) were less than 4%. The limits of detection (LODs) and limits of quantification (LOQs were in the ranges of 0.02-0.76 mg/kg and 0.04-2.52 mg/kg, respectively. The method is simple, time-saving, and has high sensitivity and good reproducibility. It can be applied to the determination of the 23 ester compounds in cigarette water-borne adhesives.