Qualitative analysis of flavors and fragrances added to tea by using GC-MS

Identification of characteristic aroma compounds in chicken meat and their metabolic mechanisms using gas chromatography-olfactometry, odor activity values, and metabolomics

Aroma has an important influence on the aroma quality of chicken meat. This study aimed to identify the characteristic aroma substances in chicken meat and elucidate their metabolic mechanisms. Using gas chromatography-olfactometry and odor activity values, we identified nonanal, octanal, and dimethyl tetrasulfide as the basic characteristic aroma compounds in chicken meat, present in several breeds. Hexanal, 1-octen-3-ol, (E)-2-nonenal, heptanal, and (E,E)-2,4-decadienal were breed-specific aroma compounds found in native Chinese chickens but not in the meat of white-feathered broilers. Metabolomics analysis showed that L-glutamine was an important metabolic marker of nonanal, hexanal, heptanal, octanal, and 1-octen-3-ol. Exogenous supplementation experiments found that L-glutamine increased the content of D-glucosamine-6-P and induced the degradation of L-proline, L-arginine, and L-lysine to enhance the Maillard reaction and promote the formation of nonanal, hexanal, heptanal, octanal, and 1-octen-3-ol, thus improving the aroma profile of chicken meat.

Deep Learning Based Prediction of Gas Chromatographic Retention Indices for a Wide Variety of Polar and Mid-Polar Liquid Stationary Phases

Prediction of gas chromatographic retention indices based on compound structure is an important task for analytical chemistry. The predicted retention indices can be used as a reference in a mass spectrometry library search despite the fact that their accuracy is worse in comparison with the experimental reference ones. In the last few years, deep learning was applied for this task. The use of deep learning drastically improved the accuracy of retention index prediction for non-polar stationary phases. In this work, we demonstrate for the first time the use of deep learning for retention index prediction on polar (e.g., polyethylene glycol, DB-WAX) and mid-polar (e.g., DB-624, DB-210, DB-1701, OV-17) stationary phases. The achieved accuracy lies in the range of 16–50 in terms of the mean absolute error for several stationary phases and test data sets. We also demonstrate that our approach can be directly applied to the prediction of the second dimension retention times (GC × GC) if a large enough data set is available. The achieved accuracy is considerably better compared with the previous results obtained using linear quantitative structure-retention relationships and ACD ChromGenius software. The source code and pre-trained models are available online.

Combined transcriptome sequencing and prokaryotic expression to investigate the key enzyme in the 2-C-methylerythritol-4-phosphate pathway of Osmanthus fragrans

Terpenoids are one of the main components of plant aromas. In the present study we investigated these compounds in Osmanthus fragrans Lour., which is a fragrant plant widely used for the production of essential oils. Quantitative real-time PCR (qRT-PCR) results of enzymes associated with the 2-C-methylerythritol-4-phosphate pathway confirmed that the TPS is a key enzyme for terpenoid synthesis in O. fragrans. In a series of experiments, we identified the TPS candidate genes in O. fragrans and revealed the underlying catalytic activity and subcellular localisation of the encoded proteins. Because there is no available O. fragrans reference genome, we sequenced and analysed its transcriptome and identified two putative TPS genes, OfTPS1 and OfTPS2. According to qRT-PCR analysis, both genes were most highly expressed at the full-bloom stage, suggesting that OfTPS1 and OfTPS2 contribute to O. fragrans terpenoid synthesis. To verify this hypothesis, we constructed prokaryotic expression vectors to obtain protein. In order to study the function of OfTPS1 and OfTPS2 in the synthesis of monoterpenes, the obtained proteins were reacted with geranyl pyrophosphate. As a result, two kinds of monoterpenes, (E)-β-ocimene and linalool, were detected from reaction products, respectively. In conclusion, OfTPS1 and OfTPS2 are both monoterpene synthases.

In-Situ Analysis of Essential Fragrant Oils Using a Portable Mass Spectrometer

A portable mass spectrometer was coupled to a direct inlet membrane (DIM) probe and applied to the direct analysis of active fragrant compounds (3-methylbutyl acetate, 2-methyl-3-furanthiol, methyl butanoate, and ethyl methyl sulfide) in real time. These fragrant active compounds are commonly used in the formulation of flavours and fragrances. Results obtained show that the portable mass spectrometer with a direct membrane inlet can be used to detect traces of the active fragrant compounds in complex mixtures such as essential fragrant oils and this represents a novel in-situ analysis methodology. Limits of detection (LOD) in the sub-ppb range (< 2.5 pg) are demonstrated. Standard samples in the gaseous phase presented very good linearity with RSD % at 5 to 7 for the selected active fragrant compounds (i.e., isoamyl acetate, 2-methyl-3-furanthiol, methyl butanoate, and methyl ethyl sulphide). The rise and fall times of the DIM probe are in the ranges from 15 to 31 seconds and 23 to 41 seconds, respectively, for the standard model compounds analysed. The identities of the fragrance active compounds in essential oil samples (i.e., banana, tangerine, papaya, and blueberry muffin) were first identified by comparison with a standard fragrance compounds mixture using their major fragment peaks, the NIST standard reference library, and gas chromatography mass spectrometry (GC-MS) analysis. No sample preparation is required for analysis using a portable mass spectrometer coupled to a DIM probe, so the cycle time from ambient air sampling to the acquisition of the results is at least 65 seconds.

Qualitative analysis of Schizonepeta annua (Pall.) Schischk essential oil by gas chromatography-quadrupole time-of-flight mass spectrometry

In this study, a method for the qualitative analysis of small molecular compounds in Schizonepeta annua (Pall.) Schischk essential oil was established based on gas chromatography-quadrupole time-of-flight mass spectrometry. In addition to an automated search of the NIST library, the identification of oxygenated monoterpenes, phenolic esters, and phenolic compounds was achieved by two additional strategies. One strategy involved comparing the relative errors of accurate masses measured for ions in the experimental spectra with those calculated for fragments identified from the NIST database of candidate matches. The second strategy involved combination of the product ion scans and positive chemical ionisation spectra for structural elucidation. Overall, 95.45% of the total essential oil volatile chemical content of Schizonepeta annua (Pall.) Schischk was identified, with phenolic monoterpenes dominating.