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Multivariate optimization of ulvan extraction applying Response Surface Methodology (RSM): the case of Ulva lactuca
Beatrice Zonfrillo1, Maria Bellumori1, Irene Digiglio1
1Department of Neuroscience, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, via Ugo Schiff 6, Sesto Fiorentino, Italy.
Abstract:
The polysaccharide ulvan has great potential for various industrial applications due to its unique composition and biochemical properties. The study aimed to optimize the extraction conditions (pH, extraction time, and Extractant/Solid (E/S) ratio) of ulvan employing Ulva lactuca samples collected in the Orbetello lagoon, Tuscany (Italy), using a Design of Experiments (DoE) approach. The extraction process was optimized through a screening phase followed by Response Surface Methodology (RSM) to maximize ulvan yield and selectivity of the extraction. The purified extracts were characterized by quantitative NMR for rhamnose (Rha) content, turbidimetric assay for sulfate content, and HPAEC-PAD for monosaccharide composition. The results indicated that a low pH value of 2.0, an extraction time of 105 min, and a high E/S ratio (60:1 mL/g) favored higher purity and yield of ulvan. Ulvan extracted under optimized conditions (9.27 % yield, 27.8 % Rha, and 20 % sulfate content) was further characterized by 2D NMR experiments and size exclusion chromatography. This optimized extraction method provides a basis for further exploration of ulvan's potential in food, pharmaceutical, and biotechnological applications.
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