Investigation of Rosa species by an optimized LC-QTOF-MS/MS method using targeted and non-targeted screening strategies combined with multivariate chemometrics.

Abstract

Plants of the Rosa genus are renowned for their pronounced and pleasant aroma and colors. The aim of this work was to develop a novel liquid chromatographic triple quadrupole time-of-flight tandem mass spectrometric (LC-QTOF-MS/MS) method for the investigation of the bioactive fingerprint of petals of different genotypes belonging to Rosa damascena and Rosa centifolia species. Central composite design (CCD) of response surface methodology (RSM) was used for the optimization of the LC-QTOF-MS/MS method. The method was validated and target, suspect, and non-target screening workflows were applied. Statistical analysis and chemometric tools were utilized to explore the metabolic fingerprint of the Rosa species. RSM revealed that the optimal extraction parameters involved mixing 11 mg of sample with 1mL of MeOH:H2 O (70:30, v/v). Target analysis confirmed the presence of 11 analytes, all of which demonstrated low limits of quantification (LOQs; as low as 0.048 ng mg-1 ) and sufficient recoveries (RE: 85%-107%). In total, 28 compounds were tentatively identified through suspect analysis. Non-target analysis enabled the generation of robust OPLS-DA and HCA models that classified the samples according to their species with 100% accuracy. A novel LC-QTOF-MS/MS method was developed and applied in the analysis of 47 R.centifolia and R.damascena flowers belonging to different genotypes.