Our Group’s Postdoctoral researcher, Anthi Panara was awarded the Best Poster Award at the 13th International Conference on Instrumental Methods of Analysis: Modern Trends and Applications, IMA Conference 2023, which successfully took place between 17-20 of September in Chania, Greece.

Dr. Panara, participated in the conference with the poster entitled: Longitudinal plant health monitoring via HRMS screening workflows (A. Panara, E. Gikas, A. Koupa, and N.S. Thomaidis) and acquired the Best Poster Award by the Microchimica Acta Journal (Springer Nature Group).

During the poster session, Dr. Panara presented our work regarding the investigation of an onion-based fertilizer on the growth of a tomato plant using time series metabolomics analysis. The plants were irrigated at 5 time points, and the changes in the metabolome were investigated utilizing high-resolution mass spectrometry (HRMS). The statistical analysis employed multivariate and time trend computation in order to highlight the time course variation of metabolites that were deemed to exhibit the highest level of bioactivity.

In more detail, the poster presentation elaborated the differentiation between the control and the onion-irrigated plants via the investigation of a five-time-point experiment based on the tomato cycle life. The identified compounds, belonging to various categories such as steroidal alkaloids and their glucosides, organic acids, fatty acids, flavonoids, and other metabolites thereof, act beneficially for plant growth. These metabolites were highlighted by applying a newly developed workflow combining multivariate chemometrics (O2PLS-DA) and time trend analysis of the most important variables. In order to facilitate the adoption of the proposed workflow from the scientific community, open-source software was employed for peak picking (MS-DIAL), annotation (SIRIUS), and time-series monitoring (MetaboClust). The results indicate that the presence of the identified compounds could ameliorate plant health, paving the way for the holistic monitoring of plant growth.