ESI(-)FT-ICR MS for the determination of best conditions for producing extract abundant in phenolic compounds from leaves of E. uniflora and FTIR-PCA as a sample screening method.
Fernanda M G de OliveiraMarcos Valério Vieira LyrioPaulo Roberto FilgueirasEustáquio V R de CastroRicardo Machado KusterPublished in: Analytical methods : advancing methods and applications (2024)
E. uniflora leaves are a rich source of phenolic compounds with biological activities, including myricitrin. In this study, the chemical profile of nine extracts prepared with leaves collected in three regions (mountain, beach, and mangrove) and at three different times of the day (8 am, 1 pm, and 6 pm) was evaluated from spectra originating from ultra-high resolution mass spectrometry (Fourier transform ion cyclotron resonance, FT-ICR) coupled to electrospray ionisation (ESI). The best time of the day and location for collecting the leaves of E. uniflora used as raw materials for producing extracts and the best ethanol concentration for obtaining an extract more abundant in compounds of interest were verified. Several flavonoids and phenolic acids were detected in their deprotonated form in the regions from m / z 200 to 1200. Myricitrin ([C 21 H 20 O 12 -H] - , m / z theo 463.08820), its chloride adduct ([C 21 H 20 O 12 +Cl] - , m / z theo 499.06488), other myricitrin derivatives, and some tannins were the main compounds detected. Considering obtaining an extract rich in phenolic compounds, including myricitrin, the best place and time of the day to collect E. uniflora leaves is in the beach region at 1 pm. In contrast, the best ethanol concentration for extract production is 70 wt%. Therefore, extraction at 96 wt% ethanol is better for obtaining an extract more abundant in phenolic acids, although 70 wt% ethanol also extracted these compounds. FTIR-PCA models were used to check for possible similarities in the data according to collection time of the day and location. These models demonstrated an excellent solution for sample screening.
Keyphrases
- oxidative stress
- ms ms
- particulate matter
- air pollution
- high resolution mass spectrometry
- anti inflammatory
- mass spectrometry
- liquid chromatography
- essential oil
- heavy metals
- polycyclic aromatic hydrocarbons
- multiple sclerosis
- magnetic resonance
- magnetic resonance imaging
- computed tomography
- water soluble
- deep learning
- artificial intelligence
- data analysis
- quantum dots