Headspace gas chromatography-mass spectrometry in the analysis of lavender's essential oil: Optimization by response surface methodology.

A static headspace gas chromatography - mass spectrometry (HS-GC/MS) method was developed and optimized with the aim to be applied in the analysis of lavender essential oil. To obtain a comprehensive profile of the essential oil, the optimum HS-GC/MS method parameters were selected based on a Design of Experiments (DοE) process. Plackett-Burman experimental design was applied by utilizing seven parameters of the HS injection system. Incubation equilibration temperature and time, agitator's vortex speed, post injection dwell time, inlet temperature, split ratio and injection flow rate were screened to select the optimum conditions on the basis of the number and the intensity of the identified compounds. Other parameters, such as sample volume and dilution solvent ratio, were also examined to achieve a comprehensive profile in a chromatographic run of 55 min. With the obtained optimum method, more than 40 volatile compounds were identified in lavender's essential oils from different geographical regions in Greece. The method can be utilized for the quality assessment of lavender's essential oil and provide information on its characteristic aroma and discrimination among species based on the acquired GC-MS profiles.

QSRR Modeling for Metabolite Standards Analyzed by Two Different Chromatographic Columns Using Multiple Linear Regression.

Modified quantitative structure retention relationships (QSRRs) are proposed and applied to describe two retention data sets: A set of 94 metabolites studied by a hydrophilic interaction chromatography system under organic content gradient conditions and a set of tryptophan and its major metabolites analyzed by a reversed-phase chromatographic system under isocratic as well as pH and/or simultaneous pH and organic content gradient conditions. According to the proposed modification, an additional descriptor is added to a conventional QSRR expression, which is the analyte retention time, tR(R), measured under the same elution conditions, but in a second chromatographic column considered as a reference one. The 94 metabolites were studied on an Amide column using a Bare Silica column as a reference. For the second dataset, a Kinetex EVO C18 and a Gemini-NX column were used, where each of them was served as a reference column of the other. We found in all cases a significant improvement of the performance of the QSRR models when the descriptor tR(R) was considered.

Protocol for quality control in metabolic profiling of biological fluids by U(H)PLC-MS.

The process of untargeted metabolic profiling/phenotyping of complex biological matrices, i.e., biological fluids such as blood plasma/serum, saliva, bile, and tissue extracts, provides the analyst with a wide range of challenges. Not the least of these challenges is demonstrating that the acquired data are of "good" quality and provide the basis for more detailed multivariate, and other, statistical analysis necessary to detect, and identify, potential biomarkers that might provide insight into the process under study. Here straightforward and pragmatic "quality control (QC)" procedures are described that allow investigators to monitor the analytical processes employed for global, untargeted, metabolic profiling. The use of this methodology is illustrated with an example from the analysis of human urine where an excel spreadsheet of the preprocessed LC-MS output is provided with embedded macros, calculations and visualization plots that can be used to explore the data. Whilst the use of these procedures is exemplified on human urine samples, this protocol is generally applicable to metabonomic/metabolomic profiling of biofluids, tissue and cell extracts from many sources.