One of the principal opportunity areas in the development of the microalgal biodiesel industry is the energy recovery from the solid microalgal biomass residues to optimise the fuel production. This work reports the cumulative methane yields reached from the anaerobic digestion of the solid microalgal biomass residues using different types of inocula, reporting also the improvement of biogas production using the co-digestion of microalgal biomass with glycerol. Results demonstrate that the solid microalgal biomass residues showed better biogas production using a mesophilic inoculum, reaching almost two-fold higher methane production than under thermophilic conditions. Furthermore, the solid microalgal biomass residues methane production rate showed an increase from 173.78 ± 9.57 to 438.46 ± 40.50 mL of methane per gram of volatile solids, when the co-digestion with glycerol was performed. These results are crucial to improve the energy balance of the biodiesel production from Tetraselmis suecica, as well as proposing an alternative way to treat the wastes derived from the microalgae biodiesel production.

The production of photosynthetic biofuels using microalgae is a promising strategy to combat the use of non-renewable energy sources. The microalgae residual biomass is a waste by-product of biofuel production; however, it could prove to have utility in the development of sustainable nutraceuticals and functional foods. In this study, a comprehensive characterisation of the under-utilised Phaeodactylum tricornutum microalgae residual biomass is presented. Proximal composition, antioxidant capacity (using three different antioxidant assays; oxygen radical absorbance capacity; radical cation activity, ABTS; and radical scavenging activity, DPPH), and total phenolic content of free and bound polyphenols were determined. Additionally, the physicochemical properties of water activity, pH, water absorption index, water solubility index, and dispersibility were evaluated. Results revealed that P. tricornutum microalgae residual biomass exhibits a relatively high protein and carbohydrate content, with values of 36.67% and 46.78%, respectively; and most carbohydrates were found as total dietary fibre (45.57%), of which insoluble dietary fibre was the most predominant (43.54%). Antioxidant capacity values for total phytochemicals of 106.22, 67.93, 9.54 µM TE g⁻¹ dw were determined by oxygen radical absorbance capacity, ABTS, and DPPH assays, respectively. Total phenolic content was found to be 2.90 mg GAE g⁻¹ dw. Interestingly, antioxidant capacity and total phenolic content were higher in bound than in free phytochemical extracts. The physicochemical analysis showed P. tricornutum microalgae residual biomass to have suitable properties for the generation of a beverage with Aw, pH, water absorption index, water solubility index, and dispersibility values of 0.45, 7.12, 3.40 g gel g⁻¹ dw, 2.5 g solids 100 g⁻¹ dw, and 90%, respectively. Hence, P. tricornutum microalgae residual biomass could be considered a potential source of bioactive compounds suitable for the production of functional food exhibiting antioxidant capacity and high dietary fibre content.

The development of microalgae culture technology has been an integral part to produce biomass feedstock to biofuel production. Due to this, numerous attempts have been made to improve some operational parameters of microalgae production. Despite this, specialized research in cell growth monitoring, considered as a fundamental parameter to achieve profitable applications of microalgae for biofuels production, presents some opportunity areas mainly related to the development of specific and accurate methodologies for growth monitoring. In this work, predictive models were developed through statistical tools that correlate a specific micro-algal absorbance with cell density measured by cell count (cells∙per ml), for three species of interest for biofuels production. The results allow the precise prediction of cell density through a logistic model based on spectrophotometry, valid for all the kinetics analysed. The adjusted determination coefficients () for the developed models were 0·993, 0·995 and 0·994 for Dunaliella tertiolecta, Nannochloropsis oculata and Chaetoceros muelleri respectively. The results showed that the equations obtained here can be used with an extremely low error (≤2%) for all the cell growth ranges analysed, with low operational cost and high potential of automation. Finally, a user-friendly software was designed to give practical use to the developed predictive models.