Enhancement of Xylitol Production by Fed-batch Policy Designed Through Stochastic Search

Abstract

In the design of a process to produce xylitol in a stirred tank bioreactor, this work addresses the problem of determining the better feeding policy of sugars by following a stochastic search. Xylitol is a high-value sweetener that can be produced by both chemical and biochemical ways; in the last decades, the second one has been gaining more interest because of the eco-friendly and likely economical advantages of green processes. On the basis of a model that describes a fermentation process of xylose to xylitol by Candida mogii, an optimization problem is stated aiming to obtain the highest amount of xylitol with the minimum remaining xylose. The process considers the addition of glucose to drive more amount of xylose to the metabolic pathway xylose-to-xylitol instead of the xylose-to-cell growth one; then the problem implies the determination of two feed flows and the initial load of cells, and sugars. A Genetic Algorithm was implemented, firstly considering the most likely practical case of constant feed flows, and later partitioning the process time in several intervals, along which the feed flows are allowed to change. In both cases, the xylitol concentration obtained is even higher than the one reported in previous works.