Biochemical and spectral characterization of micro- and macroalgae

Abstract

Algae contain many compounds which are of interest to the pharmaceutical, agricultural and food industries, among others. Despite the potential for many applications, a quick, accurate and inexpensive method for characterising algae is lacking. The objective of this thesis was to investigate the ability to determine protein, carbohydrate and fatty acid contents in algae, using infrared spectroscopy. Algal samples were analysed using some of the most accurate chemical methods, by hydrolysing proteins and polysaccharides and quantifying the resulting amino acid and monosaccharide contents using chromatography techniques. Fatty acid contents were similarly quantified by extraction followed by gas chromatography. This data was subsequently used to calibrate spectral prediction models, using different infrared spectroscopies. The accuracy of protein prediction by diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and near-infrared spectroscopy (NIR) using partial least squares regression (PLSR) was compared to traditional methods like N-protein ratios and colorimetric assays. DRIFTS, attenuated total reflectance (ATR) Fourier transform infrared spectroscopy (ATR) and NIR were also comparatively used to characterise seaweed carbohydrates. Fatty acid contents were studied using DRIFTS in both microalgae and seaweeds. Infrared spectroscopy coupled with PLSR was shown to be highly accurate in characterising algal biomass, provided a sufficiently robust library of calibration samples. These methods require little or no chemicals and are rapid and easy to use, making them both environmentally and economically attractive.