Search Results (2)

Microalgae lipids offer numerous advantages over those of plants and animals, enabling the sustainable commercialization of high value-added products in different markets. Although these markets are in a vertiginous annual expansion, technological life cycle modeling is a tool that has been rarely used for microalgae. Life cycle modeling is capable of assisting with decision-making based on data and is considered as a versatile model, usable in multiple software analyzing and diagnostic tasks. Modeling technological trends makes it possible to categorize the development level of the market and predict phase changes, reducing uncertainties and increasing investments. This study aims to fill this gap by performing a global analysis and modeling of microalgal lipid innovations. The Espacenet and Orbit platforms were used by crossing the keywords “microalgae”, “lipid*”, and the IPC code C12 (biochemistry and microbiology). Different sigmoid growth models were used in the present study. A successive repetition of the Chlorella genus category was found in the keyword clusters regarding extraction and separation of lipids. The life cycle S curve indicates a market starting at the maturity phase, where the BiDoseResp model stands out. The main countries and institutions at the technological forefront are shown, as well as potential technological domains for opening new markets. Full article

The large-scale cultivation of microalgae provides a wide spectrum of marketable bioproducts, profitably used in many fields, from the preparation of functional health products and feed supplement in aquaculture and animal husbandry to biofuels and green chemistry agents. The commercially successful algal biomass production requires effective strategies to maintain the process at desired productivity and stability levels. Hence, the development of effective early warning methods to timely indicate remedial actions and to undertake countermeasures is extremely important to avoid culture collapse and consequent economic losses. With the aim to develop an early warning method of algal contamination, the potentiometric E-tongue was applied to record the variations in the culture environments, over the whole growth process, of two unialgal cultures, Phaeodactylum tricornutum and a microalgal contaminant, along with those of their mixed culture. The E-tongue system ability to distinguish the cultures and to predict their growth stage, through the application of multivariate data analysis, was shown. A PLS regression method applied to the E-tongue output data allowed a good prediction of culture growth time, expressed as growth days, with R² values in a range from 0.913 to 0.960 and RMSEP of 1.97–2.38 days. Moreover, the SIMCA and PLS-DA techniques were useful for cultures contamination monitoring. The constructed PLS-DA model properly discriminated 67% of cultures through the analysis of their growth media, i.e., environments, thus proving the potential of the E-tongue system for a real time monitoring of contamination in microalgal intensive cultivation. Full article