Statistical Diagnosis Test of the Growth Kinetics Model for the Algae Dunaliella tertiolecta (Asian Journal of Plant Biology, 2014)
Mathematical modeling of physical, chemical or biological data could help the investigator toexplain a phenomenon observed based on physical, chemical or biological mechanisms. Themodel could also be used to predict or forecast future behavior, simulate a hypothetical event orinput and design better experiments. Previously, we demonstrated that the Baranyi-Robertsgrowth kinetics is the best model using the ordinary least squares method for the growth of thealgae Dunaliella tertiolecta compared to other models such as modified logistic, modifiedGompertz, modified Richards, modified Schnute, Baranyi-Roberts, Von Bertalanffy, Huangand the Buchanan three-phase linear model. The ordinary least squares method relies heavily onseveral important assumptions such as residuals conformation to normal distribution, does nothave outliers, is truly random, of equal variance (homoscedastic) and does not showautocorrelation. If all of these assumptions are satisfied, the test is said to be robust. In thiswork we perform statistical diagnosis test for the adequacy of the model to satisfy theserequirements.
Keywords: Baranyi-Roberts, ordinary least squares method, normal distribution, homoscedastic, autocorrelation