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

Petros D Mitsikaris; Stefanos Kostas; Ioannis Mourtzinos; Urania Menkissoglu-Spiroudi; Athanasios Papadopoulos; Natasa P Kalogiouri

doi:10.1002/pca.3345

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

Phytochem Anal. 2024 Mar 4. doi: 10.1002/pca.3345. Online ahead of print.

Authors

Petros D Mitsikaris¹, Stefanos Kostas², Ioannis Mourtzinos³, Urania Menkissoglu-Spiroudi⁴, Athanasios Papadopoulos¹, Natasa P Kalogiouri⁵

Affiliations

¹ Department of Nutritional Sciences and Dietetics, Laboratory of Chemical Biology, International Hellenic University, Thessaloniki, Greece.
² School of Agriculture, Laboratory of Floriculture, Aristotle University, Thessaloniki, Greece.
³ School of Agriculture, Laboratory of Food Science and Technology, Aristotle University of Thessaloniki, Thessaloniki, Greece.
⁴ Faculty of Agriculture Forestry and Natural Environment, School of Agriculture, Pesticide Science Laboratory, Aristotle University of Thessaloniki, Thessaloniki, Greece.
⁵ Department of Chemistry, Laboratory of Analytical Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece.

PMID: 38439140
DOI: 10.1002/pca.3345

Abstract

Introduction: Plants of the Rosa genus are renowned for their pronounced and pleasant aroma and colors.

Objective: 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.

Methodology: 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.

Results: RSM revealed that the optimal extraction parameters involved mixing 11 mg of sample with 1 mL 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.

Conclusions: 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.

Keywords: HRMS; Rosa species; chemometrics; non-target; response surface methodology.

Grants and funding

Interdisciplinary Agri-Food Center, Aristotle University of Thessaloniki (KEAGRO-AUTH)