Microalgae are considered a promising resource of proteins, lipids, carbohydrates, and other functional biomolecules for food and feed markets. Competitive drying solutions are required to meet future demands for high-quality algal biomass while ensuring proper preservation at reduced costs. Since often used drying methods, such as freeze or spray drying, are energy and time consuming, more sustainable processes remain to be developed. This study tested an indirect and hybrid solar dryer as an alternative to conventional freeze drying of industrially produced Tetraselmis chui and Nannochloropsis oceanica wet paste. The effects of the drying method on biomass quality parameters, including biochemical profiles, functional properties, and microbial safety, were assessed. No significant differences were found between the applied drying technologies for total proteins, carbohydrates, lipids, and fatty acid profiles. On the other hand, some pigments showed significant differences, displaying up to 44.5% higher contents in freeze-dried samples. Minor differences were also registered in the mineral profiles (<10%). Analyses of microbial safety and functional properties of the solar-dried biomass appear adequate for food and feed products. In conclusion, industrial solar drying is a sustainable technology with a high potential to preserve high-quality microalgal biomass for various markets at expected lower costs.

Drying is a necessary step in the microalgae production chain to reduce microbial load and oxidative degradation of the end product. Depending on the differences in applied temperature and treatment time, the process of drying can have a substantial impact on protein quality and aroma, important characteristics determining the incorporation potential in food products. In this study, we compared the drying of heterotrophic Chorella vulgaris with both innovative (agitated thin film drying (ATFD), pulse combustion drying (PCD) and solar drying (SolD)) and commonly used drying techniques (spray drying (SprD) and freeze drying (FD)). To evaluate the impact on protein quality, we evaluated techno-functional properties, in vitro digestibility (INFOGEST) as well as protein denaturation using differential scanning calorimetry (DSC). A sensory analysis was performed by a trained expert panel, combined with headspace solid-phase microextraction (HS-SPME) - gas chromatography-mass spectrometry (GC-MS) to determine volatile organic compounds (VOCs). ATFD was found to increase techno-functional properties such as gelling, water holding and solubility as well as in vitro protein digestibility. These observations could be related to induced cell disruption and protein denaturation by ATFD. Sensory analysis indicated an increased earthy off-flavor after ATFD. Interestingly, the high-temperature PCD led to an increase in cacao odor while low-temperature FD resulted in lower flavor, odors and VOCs. These results demonstrate that protein quality and sensorial properties of C. vulgaris can be steered through the type of drying, which could help in the selection of application-specific drying methods. Overall, this work could promote the incorporation of microalgal single cell proteins in different innovative food products.

Mammals are not able to restore lost appendages, while many amphibians are. One important question about epimorphic regeneration is related to the origin of the new tissues and whether they come from mature cells via dedifferentiation and/or from stem cells. Several studies in urodele amphibians (salamanders) indicate that, after limb or tail amputation, the multinucleated muscle fibres do dedifferentiate by fragmentation and proliferation, thereby contributing to the regenerate. In Xenopus laevis tadpoles, however, it was shown that muscle fibres do not contribute directly to the tail regenerate. We set out to study whether dedifferentiation was present during muscle regeneration of the tadpole limb and zebrafish larval tail, mainly by cell tracing and histological observations.

High expectations are placed on microalgae as a sustainable source of valuable biomolecules. Robust methods to control microalgae cultivation processes are needed to enhance their efficiency and, thereafter, increase the profitability of microalgae-based products. To meet this need, a non-invasive monitoring method based on a hyperspectral imager was developed for laboratory scale and afterwards tested on industrial scale cultivations. In the laboratory experiments, reference data for microalgal biomass concentration was gathered to construct 1) a vegetation index-based linear regression model and 2) a one-dimensional convolutional neural network model to resolve microalgae biomass concentration from the spectral images. The two modelling approaches were compared. The mean absolute percentage error (MAPE) for the index-based model was 15–24%, with the standard deviation (SD) of 13-18 for the different species. MAPE for the convolutional neural network was 11–26% (SD = 10–22). Both models predicted the biomass well. The convolutional neural network could also classify the monocultures of green algae by species (accuracy of 97–99%). The index-based model was fast to construct and easy to interpret. The index-based monitoring was also tested in an industrial setup demonstrating a promising ability to retrieve microalgae-biomass-based signals in different cultivation systems.