A Low-Cost pH Monitoring and Control System for Algae Cultivation

Algae cultivation requires adaptive control of pH through carbon dioxide (CO2) injection to maximize biomass productivity. Control systems that utilize low-cost platforms and open-source software can reduce capital costs relative to existing industrial devices for pH monitoring and control. Toward this end, this thesis describes the design, programming, and experimental testing of a low-cost control system for regulating the pH of raceway ponds for algae cultivation via CO2 injection. The system utilizes a Raspberry Pi 4B single-board computer with open-source Python code that replicates the pH control functionality of a commercial YSI 5200A aquaculture monitoring and control instrument. Calibration code was developed to both ensure accurate pH readings and determine their drift over time using two pH probes. The volume flow of the gas injected is also recorded, along with the pressure and time. Experiments on monitoring and controlling pH were conducted in 4.2-m2 raceways (820-L) with both the open-source control system and the YSI 5200A instrument. The open-source system was capable of a higher data logging frequency than the YSI instrument due to the open-source systems larger memory and its code design, increasing temporal resolution from 15-minute to 10-second intervals. Decision times for CO2 injection were 30 seconds for both the open-source and YSI systems. The experiments demonstrated that the calibration code improved the accuracy of the open-source system relative to the YSI system in both abiotic and biotic controlling scenarios. When both systems are well-calibrated, they read nearly identical pH values. In summary, the open-source system was found to have significant advantages over the commercial YSI system in terms of data collection frequency, lifespan, pH measurement accuracy, and reduced cost of pH probes and other sensors. Additionally, the open-source system will allow for better control over CO2 injection due to an incorporated diurnal light cycling function.