RESUMEN
Caffeine is present in a large number of beverages and is an additive used in dietary supplements. Therefore, the concern about its quality and safety for consumers has been increasing and hence requires faster and simpler analytical methods to determine the caffeine amount. The high-throughput analysis is an appropriate solution to pharmaceuticals, bioanalysis, forensic and food laboratory routines. In this sense, Venturi easy ambient sonic-spray ionization mass spectrometry (V-EASI-MS), a specific ambient ionization source, is suitable to enable direct analysis of sample solutions in real time and is appropriate to be coupled to liquid chromatography (LC). The development of an on-line solid phase extraction system coupled to V-EASI-MS optimizes the advantages of LC-MS hyphenation by enhancing the figures of merit of the analytical method according to AOAC guidelines and simultaneously minimizing the runtime analysis to 1.5 min per sample, as well as sample preparation steps and solvent consumption, which is currently a challenge for quantitative applications of ambient ionization MS.
Asunto(s)
Cafeína , Suplementos Dietéticos , Extracción en Fase Sólida , Espectrometría de Masa por Ionización de Electrospray , Cafeína/análisis , Extracción en Fase Sólida/métodos , Suplementos Dietéticos/análisis , Espectrometría de Masa por Ionización de Electrospray/métodos , Ensayos Analíticos de Alto Rendimiento/métodos , Cromatografía Liquida/métodosRESUMEN
In the present study, foodomics approach was employed to investigate changes in the metabolism from the volatile terpenoids profile of mint(Mentha × gracillis Sole)from conventional, organic and permaculture (a type of agroecological agriculture system) farms using headspace solid-phase microextraction (HS-SPME) associated to gas chromatography coupled to mass spectrometry (GC-MS) and chemometric tools. The discrimination among the three types of mint was successfully achieved and demonstrated evidence of ecological interaction impact in the food metabolism. The agroecological mint presented as differential compounds: α-terpineol, bornyl formate, cis-carvyl propionate, cis-carveol, camphor, dihydrocarvyl acetate, dihydrocarveol, karahanaenone, nonanal, 3-octyl acetate, and trans-3-hexenyl-2 methylbutyrate. While organic and conventional mint presented as differential compounds: α-cedrene, ß -pinene, γ-muurolene, δ-cadinene, germacrene, terpinolene, and elemol. The majority of differential metabolites from agroecological mint are oxygenated monoterpenes, which have more intense flavor and biological activities than hydrocarbons monoterpenes and sesquiterpenes found in organic and conventional mint. Furthermore, the discrimination between organic and conventional mint was effectively performed, which demonstrated different terpenoid profiles though without implying benefits for one or another agriculture system.
Asunto(s)
Mentha , Compuestos Orgánicos Volátiles , Agricultura , Cromatografía de Gases y Espectrometría de Masas/métodos , Monoterpenos/análisis , Microextracción en Fase Sólida/métodos , Terpenos/análisis , Compuestos Orgánicos Volátiles/análisisRESUMEN
Venturi easy ambient sonic spray ionization (V-EASI) is a soft ambient ionization (AI) source that has the advantages of being suitable to the analysis of samples in solution (differently from the majority of AI sources), performing self-pumping, voltage- and heat-free ionization, and requiring minimum or no sample preparation. Since this ionization technique has not been fully explored, the present study provides a proof of principle of the coupling of liquid chromatography to mass spectrometry (LC-MS) using V-EASI as the interface. In order to test the performance of the developed LC-V-EASI-MS system, a quantification method for bixin, a natural dye from annatto (Bixa Orellana L.), which is known to be sensitive to the high voltage applied for electrospray ionization mass spectrometry (ESI-MS) analysis, was validated according to FDA criteria and tested in real samples. The analytical method was successfully applied and met the validation criteria, providing a detectability 10 times better than methods already reported to the quantification of bixin and no matrix effect was observed. Therefore, this proof of principle contributes to the continuous development of AI sources that represents the last great technological advance in MS towards becoming a miniaturized technique able to analyze samples closer to their actual state.