Kinetic modelling for prediction of biomass concentration of Chlorella minutissima in open raceway pond cultivation: A pilot-scale study

Abstract

For large-scale microalgae cultivation, modelling can play a significant role in predicting and improving biomass generation. Existing kinetic models for outdoor cultivation have drawbacks of reproducibility due to the involvement of uncontrollable environmental factors such as solar intensity, air temperature, relative humidity, dilution rate, etc., affecting the dependent variables such as culture temperature, dissolved oxygen concentration and pH, regardless of the availability of adequate nutrients in the medium. Thus, a kinetic model was proposed here to predict the biomass concentration accurately for all the given variables in terms of specific growth rates. Chlorella minutissima was cultivated in open raceway ponds to calibrate the proposed model, and biomass concentration was estimated as a function of time along with the cultural and environmental variables. Sensitivity analysis demonstrated that the estimated biomass concentration was highly sensitive to the specific growth rate of solar intensity followed by the air temperature. The model was evaluated using C. minutissima experimental data, which exhibited a prediction efficiency of 99.5% with an R2 value of 0.96. Further, the model validation was performed with experimental data obtained for outdoor cultivation of Scenedesmus accuminatus, Tetradesmus obliquus, Chlorella variabilis, Scenedesmus acutus, and Chlorella pyrenoidosa from the available literature, which showed the mean absolute percentage errors of 0.38, 9.1, 7.38, 9.5, and 1.72%, respectively. It has also been observed that as the availability of input variables increases, the accuracy of biomass concentration prediction increases. Thus, this model is recommended for forecasting microalgal biomass production.