Predictive growth model of microalgae in agricultural wastewater / Nur I'ffah Abdul Hanan...[et al.]

Agricultural wastewater is a dark brown viscous liquid with a high concentration of degradable organic matter and mineral constituents. The incorporation of microalgae in agricultural wastewater to utilizes organic substances creates a potentially unprecedented valuation. However, provided that the descriptive growth model of microalgae in agricultural wastewater is rarely addressed. In this study, an assessment was performed on four mathematical models (Logistic, Modified Logistic, Modified Gompertz, and Baranyi-Roberts) on the growth of Coellastrela sp. UKM4, Chlamydomonas sp. UKM6 and Scenedesmus sp. UKM9 based on the available published works in the literature. Statistical analyses, including R2, adjusted R2, rootmean-square error (RMSE), bias factor (BF), accuracy factor (AF), and percent of standard error prediction (%SEP) were applied to verify the accuracy of each model. The findings showed, based on the visual analysis and residual plots, modified logistic model and Baranyi- Robets model had produced good fitting curve between experimental data and model predictive data. For statistical analysis, both models produced R2 (>95%), adjusted R2 (>93%), RMSE (0.048-0.08), BF (0.9-1.01), AF (<1.1) and %SEP (7.7%-15%). The findings therefore revealed that the most appropriate model for predicting the growth of Coellastrela sp. UKM4, Chlamydomonas sp. UKM6 and Scenedesmus sp. UKM9 in agricultural wastewater were modified logistic and Baranyi-Roberts models.