Desenvolvimento, otimização e validação de método analítico para o estudo quimiossistemático do gênero Ocotea (Lauraceae) na Amazônia

Abstract

The Ocotea genus is one of the most biodiverse and economically interesting in the Lauraceae family. However, its commercial and scientific exploitation is scarce due to the great difficulty on the species identification by taxonomy features. Thus, this Thesis propose to develop, optimize and validate a method for the metabolic study of Ocotea , using species leaves samples, to develop the genus chemosystematic. The development and optimization of the extraction method was performed by a factorial design which evaluated the effects of the extractor solvent composition, extraction temperature, particle size and the proportion between sample and solvent, on the quality extractor chemical profile, considering qualitative and quantitative features. The optimized extraction method was applied on 13 different species of Ocotea. The metabolomic study used chemometric tools and high performance liquid chromatography techniques combined with mass spectrometry. At last, the method was validated for untargeted metabolomics goals, by the study of linearity, precision and reproducibility with a quality control sample. The experimental conditions with best performance, regarding extraction yield and the quality of the chemical profile applied 70% ethanol, extraction temperature of 40°C, particle size of 0.595 mm and the proportion between sample and solvent of 1:12 g:mL. The composition of the extracting solvent and the extraction temperature were the factors that most influence the data quality for untargeted metabolomics. The use of the optimized method enabled a metabolic evaluation of the 14 Ocotea species, enabling to define chemical markers capable to specifically distinguishing O. splendens and O. canaliculata species and classifying the others within 3 distinct groups. Still, through analytical validation, the analytical method demonstrated satisfactory performance for the production of holistic chemical fingerprints, presenting precise and reproduceable data. In conclusion, the developed method can be satisfactorily applied in the untargeted metabolic study of the genus Ocotea, being able to contribute on species identification and circumscription.