Abstract
With increasing demand for microalgae, there is a need to reduce operational production costs and develop stable growth prediction methods. In this study, we have developed a low-cost and user-friendly monitoring and biomass auto-recovery system using a microcomputer (Raspberry Pi) and a sensor. The microalgal monitoring sensors (turbidity, light, pH, and temperature) designed for real-time measurements and remote monitoring were validated using standard instruments. The monitoring system was implemented in a culture of the filamentous and spiral microalgae Limnospira fusiformis. The turbidity sensor showed a strong correlation with optical density (R2 = 0.943–0.986) and dry weight (R2 = 0.954–0.975). The sensors for light, pH, and temperature demonstrated average percentage errors of 0.50%, 0.58%, and 2.52%, respectively, indicating their accuracy in measuring the intended parameters (p < 0.05). The developed auto-recovery system effectively maintained biomass within the desired threshold range (OD750 = 0.74–0.67). The threshold value for the operating biomass density was adjustable with data available in real time and logged with time stamping on a Google spreadsheet. This cost-effective system, priced at approximately $330, offers a practical solution for the real-time monitoring and control of biomass density in microalgal cultures.