Unleashing the Full Potential of Haematococcus for Astaxanthin Production using Digital Tools

Haematococcus lacustris is among the industrially most relevant microalgae due to its great potential for the sustainable production of natural astaxanthin. In this thesis, three strategies were adopted to improve and investigate different aspects of growth and astaxanthin production in H. lacustris. First, mixotrophy was studied as a potential strategy to improve biomass productivity. A detailed investigation of mixotrophic growth kinetics as a function of the substrate concentration and light intensity was conducted. Mixotrophic cultivation showed significant differences in respect to applied substrate and achieved maximum specific growth rates of 0.91 ± 0.13, 0.19 ± 0.05, 0.36 ± 0.05, and 0.23 ± 0.05 d^-1, for acetate, methanol, glucose, and glycerol, respectively. Optimal growth at mixotrophic conditions using acetate was 1.8 times higher than the sum of hetero- and photoautotrophic growth. Besides, the optimum light intensity was 1.3 times higher for mixotrophic than for autotrophic growth. These results were used as a foundation for a more detailed mathematical model including growth on light, nitrogen uptake and storage, and prediction of astaxanthin accumulation. Finally, an automated online monitoring system was developed to classify four different cell cycle stages using a scanning microscope. Decision-tree based machine learning and deep learning convolutional neural network algorithms were developed, validated, and evaluated. SHapley Additive exPlanations was used to examine the most important system requirements for accurate image classification. The models achieved accuracies on unseen data of 92.4 and 90.9%, respectively. Furthermore, both models were applied to a photobioreactor culturing H. lacustris, effectively monitoring the transition from a green culture in the exponential growth phase to a stationary red culture. The application of novel cultivation strategies and digital tools to microalgae cultivation is essential to close the gap between traditional biotechnology and microalgae biotechnology, enabling a broader application of microalgae as sustainable production platforms.