Fourier-transform infrared imaging and multivariate analysis for direct identification of principal polysaccharides...

The current hydrocolloid industry requires new techniques for biomass characterization, which can quickly and ecologically characterize contained sugars. This work proposes the use of Fourier Transform Infrared microspectroscopy in combination with multivariate methods, to localize and identify the main carbohydrates and other components present in fresh brown seaweeds, avoiding time-consuming samples pre-treatments. Infrared images of Macrocystis pyrifera samples were analyzed by Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis (PCA) as chemometrics techniques to identify the compounds. MCR-ALS was the best strategy, delivering pure spectra of chemical compound that PCA did not. The carbohydrates identified by this method were 1-3-β-glucans divided into endofibers and laminarin; two types of fucoidans (rich in fucose or mannuronic acid), alginate and mannitol, besides other compounds such as proteins. This technique represents an opportunity for the hydrocolloid industry for a modern, rapid and environmentally-friendly characterization of macroalgal biomass to enhance its use.