Understanding the infectious diseases outbreak of algae can provide significant knowledge for disease control intervention and/or prevention. We consider here a disease caused by highly pathogenic organisms that can result in the death of algae. Even though a great deal of understanding about diseases of algae has been reached, studies concerning effects of the outbreak at the population level are still rare. For this reason, we computationally model an outbreak in the algae reservoir or container systems consisting of several patches or clusters of algae being infected with a contagious infectious disease. We computationally investigate the systems as well as make some predictions via the deterministic SEIR epidemic model. We consider the factors that could affect the spread of the disease including the number of patches, the size of initial infected population, the distance between patches or spatial range, and the basic reproduction number (R 0 ). The results provide some information that may be beneficial to algae disease control, intervention or prevention.
Algae are fast growing microorganisms and beneficial in many ways, especially concerning food supplement, alternative energy, and wastewater treatment. Naturally, they need a light:dark regime for productive photosynthesis. To have more insight into how light affects their growth, we investigate the effect of light sources (fluorescent and LED) on algae growth both experimentally and computationally via modeling. It was found that growth in the fluorescent light source is relatively better than in other sources. Computational data analyses and detailed discussions are presented. Lastly, a more generalized growth model of microalgae for incorporation of other factors and variables is necessary for more realistic modeling of real-world systems.
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