Utilization of statistics and experimental design in data collection and analysis

Abstract

Application of experimental design techniques to Pirt's yield model shows that it is important to collect data at the lowest and highest specific growth rates. In the fed-batch fermentation process, values of specific growth rate can be varied from the maximum value at the start of the process to very low values near the end of the experiment. Candida utilis was cultivated using batch followed by fed-batch culture with glucose as the main source of carbon and energy. Values of substrate concentration, oxygen consumption, carbon dioxide evolution, liquid volume, flow rate cell concentration, and nitrogen concentration, which was an indirect measure of biomass, were measured. Least-squares estimates of the true biomass energetic yield and maintenance coefficient were obtained using a multivariate statistical analysis procedure referred to as the covariate adjustment procedure. Methods of selecting the best estimates using covariate adjustment are illustrated. The results show that useful parameter estimates with relatively short confidence intervals can be obtained using these statistical methods.