POSTER Session 2
Tuesday, October 8
11:10–12:50
Poster Session | 1 | 2 | 3 | 4 | Instructions | Schedule at a Glance
ABSTRACT 770 | POSTER T-020
ADVANCING ANALYTICAL METHODS FOR SATELLITE VALIDATION: A UHPLC-BASED APPROACH TO PHYCOCYANIN QUANTIFICATION IN ALGAL BLOOMS
The deployment of hyperspectral satellite missions such as the German EnMAP and the Italian PRISMA and the launch of the NASA PACE mission open to new opportunities for integrated approaches to address the escalating issue of cyanobacterial algal blooms in marine and inland waters. Despite these advancements, the validation of satellite data concerning phycocyanin (C-PC) content demands robust analytical methods. Currently, the available methods, predominantly spectrophotometric or fluorometric, exhibit low reproducibility due the interference of the chlorophyll a (Lauceri et al., 2018). Compounding this challenge, existing techniques perform optimally with liquid water samples, presenting a significant limitation when analyzing concentrated samples on filters (Horwath et al., 2013). This limitation compromises the efficacy of methods designed to identify cyanobacteria in samples collected during ship-based campaigns. In this study, we aim to establish a method for C-PC analysis in water samples on filter pad. This involves the extraction and analysis of C-PC from pure algal cultures and natural samples, employing Ultra High Pressure Liquid Chromatorgraphy (UHPLC) analysis—a recognized gold standard for algal pigment analysis. Based on Design of Experiment (DoE) full factorial design approach, we compared different extraction techniques. Subsequently we developed and validated a rapid, simple and sensitive reverse phase UHPLC method. The optimized chromatographic parameters for C4 phase, were acetonitrile with trifluoroacetic acid (0.1% v/v) in a 5’ linear gradient (from 30% to 100%), flowrate 0.8 mL/min. Our work aims to address the existing gaps in analytical methodologies, providing a more robust and reliable approach to validate satellite-derived C-PC data.
Elisabetta Canuti, University of Urbino, Italy, https://orcid.org/0000-0002-4357-8203
Poster Session | 1 | 2 | 3 | 4 |
Instructions | Schedule at a Glance
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