Monday, April 30, 2007
3-15

Optimization of a propagation procedure of Saccharomyces cerevisiae in batch culture for bioethanol production by means of the Taguchi parameter design

Piedad Curiel-Camino1, Enrique Barrado-Esteban2, Rebeca Díez-Antolinez1, Pablo Gutiérrez-Gómez1, Silvia Pisonero-Torralba1, and Isidro Sangüesa-Dominguez1. (1) Biofuels and Bioproducts Research Group, Agricultural Technological Institute of Castilla y Leon, ITACyL, Carretera de Burgos Km 119, Finca Zamadueñas, 47071, Valladolid, Spain, (2) Dep Analytical Chemistry, Faculty of Chemistry, University of Valladolid, Pº Prado de la Magdalena s/n 47011, Valladolid, Spain

Optimization of Saccharomyces Cerevisiae´s propagation is a crucial step in bioethanol production. Achieving the maximum number of viable cells at the beginning of fermentation avoid long lag phases and therefore, conduct to a more efficient usage of tank fermentation volume in production facilities.

 The aim of these experiences is to find the optimum combination of parameters in the propagation procedure of Saccharomyces cerevisiae. By means of growth plot, glucose plot, specific growth plot rate and relation between optical density and cells counting it is possible to know when the moment of maximum stationary phase is reached. At this time, fermentation starts with the most possible number of viable cells.

 The propagation process was optimized by means of the Taguchi parameter design. Four control factors: 1) percentage of inoculum, 2) percentage of glucose, 3) temperature and 4) stirring, at three levels were explored and assigned to the column of a L9(3)4 saturated orthogonal array. A noise factor (percentage of peptone) was incorporated into the experiment at three levels to simulate the uncontrollable amount of peptone in the process. The experiment was conducted with two replicates of each trial.

 The statistical analysis and the factorial graphs showed that the chosen design parameters and levels lead to an optimum and robust response. This result is independent of uncontrollable variation of percentage of peptone into the sample. Finally, it was performed a confirmatory experiment using two replicates of the optimum combination at each noise level. The resultant response confirms the optimum combination predicted.


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