Carbohydrate-based phenotyping of the green macroalga Ulva fasciata using near-infrared spectrometry: Potential implications for marine biorefinery

Abstract

Marine macroalgal biomass is a promising sustainable feedstock for biorefineries. However, the development of macroalgal biomass for industrial cultivation and processing has been slow. In terrestrial plants, high-throughput phenotyping provides rapid imaging methods to select specimens with required properties, rapidly transforming traditional breeding techniques. To foster the development of macroalgal biomass for biorefinery applications, we developed a near-infrared spectrometry-based method for rapid phenotyping of the macroalga Ulva fasciata based on its glucose, rhamnose, xylose and glucuronic acid contents. Spectral slopes were calculated as indicative of major carbohydrate content change. In addition, different spectral indices were generated to distinguish between low and high contents of glucose, rhamnose, xylose and glucuronic acid in wet and dry biomass. Since glucose is a major monosaccharide in Ulva that is fermentable to bioethanol, as an example of future application, we developed a multivariate data analysis based on partial least squares regression to predict its content in dry and wet biomass samples solely from reflectance data. These methods could provide a useful, high-throughput tool to rapidly select thalli with high carbohydrate content for further propagation and to be used for feedstock development for marine biorefineries.