Ricardo Pérez-Correa

Modelling Gibberella fujikuroi growth and GA3 production in solid-state fermentation

A simple differential equation model was developed to represent the growth and production of a secondary metabolite in solid-state cultivation (SSC) under conditions of limited nitrogen. The model was used to interpret data obtained from SSCs of the fungus Gibberella fujikuroi, under different temperatures (25 and 31 °C) and water activity conditions (0.985, 0.992, 0.999). The model was calibrated in two steps. An innovative procedure to achieve good initial guesses for key parameters, such as maintenance coefficients and death rates was first applied. These initial guesses were then used in a non-linear optimisation routine to get a minimum least squares fit for the model. The mathematical model was able to reproduce the measured variables: biomass, urea, starch, CO2 ,O 2 and GA3 satisfactorily. Moreover, the model indicated that the fungus does not assimilate the nitrogen source, urea, directly. The model will be useful in developing optimal feeding policies and on-line biomass estimators.

Solid substrate cultivation of Gibberella fujikuroi on an inert support

Growth of Gibberella fujikuroi on Amberlite, an inert support, and gibberellic acid (GA3) production was studied in glass columns under different conditions of temperature and water activity (aw). Maximum biomass concentration and GA3 production were respectively 40 (mg:g inert support) and 0.73 (mg:g inert support). While high specific growth rates were obtained, low initial nitrogen resulted in low biomass concentrations. Maximum GA3 (31°C, aw 0.985) was not produced by the maximum concentration of biomass (25°C, aw0.992). Peaks in the rate curves of either outlet gas, CO2 or O2, occurred on exhaustion of urea indicating, for future works, just when to feed the culture additional nitrogen.

Reassessment of the estimation of dissolved oxygen concentration profile and KLa in solid-state fermentation

Abstract Oxygen mass transfer in aerobic microbial growth systems is often a limiting factor for optimal growth and productivity. Oxygen mass transfer has been widely studied in submerged fermentations but has attracted as yet little attention for solid state fermentations. The parallel to submerged fermentation has led to the incorrect interpretation and use of the overall oxygen mass transfer coefficient ( K L a ) to assess the ability of a particular fermentation system to supply the oxygen to microorganisms. The use of K L a , as traditionally defined, should be used with caution in solid substrate fermentation systems because there is no convection on the liquid side of the medium, and oxygen is consumed in the biofilm. Hence, K L a must be redefined for solid state fermentation. In this paper, the use of oxygen mass transfer coefficients in solid state fermentations is clarified. Published literature data were analysed with a simple pseudo-steady-state model and used to discuss the influence of the biofilm thickness, the dissolved oxygen diffusion coefficient, the convective gas mass transfer coefficient, and the gas flow rate on the oxygen mass transfer coefficient in solid state fermentations.

Solid substrate fermentation of Monascus purpureus: growth, carbon balance, and consistency analysis.

Solid Substrate fermentation (SSF) of Monascus purpureus on rice is a promising new technology for obtaining natural pigments. However, before attempts can be made at maximizing pigment yield, all significant macroscopic compounds should be assayed. Here, Monascus purpureus has been grown on rice in batch mode, and the evolution of the main components, biomass, residual rice, O2, CO2, ethanol, acetic acid, and pigments, have been followed. This set of data, never previously studied for Monascus SSF, allowed both the performance of a macroscopic elemental balance, which accounted for 83–94% of the initial substrate carbon, and a check of data consistency. Standard consistency analysis showed a significant underestimation of the nitrogen fraction of biomass, but it was unable to discriminate the errors in the carbon balance as a result of the simultaneous presence of two gross errors in the system. A simple stoichiometric model in tandem with consistency analysis explained unaccounted carbon as an underestimation of CO2 and ethanol. Using the simplified method to estimate ethanol, the macroscopic balance accounted for 87–99% of the initial carbon.

A neural network estimator for total biomass of filamentous fungi growing on two dimensional solid substrate

A neural network dynamic model is proposed for the on-line estimation of total biomass during filamentous fungi cultures on two dimensional solid substrate. The neural network provides an accurate and robust estimation of biomass from macroscopic measurements of the colony radius evolution. Experiments were performed on Gibberella fujikuroi growing on Petri dishes under different conditions of temperature and water activity.

Fungal biomass estimation in batch solid substrate cultivation using asymptotic observation

The lack of on-line measurements of key variables is the main obstacle that hinders the development of proper control and optimisation systems for fermentation processes. This is especially true for solid substrate cultivation (SSC) that lags behind submerged cultivation. To partially overcome this limitation of SSC processes, on-line observers of relevant variables, such as biomass, secondary metabolites and nutrients concentration, can be developed. In fact, the high cost and scarcity of reliable sensors adapted to SSC systems forces the development of softsensors (software + sensors) [1].

An aseptic pilot bioreactor for solid substrate cultivation processes

Solid Substrate Cultivation processes (SSC) are characterised by the growth of microorganisms within a porous support without free water. This condition favors the development of filamentous fungi, given their unique capacity to colonise the interparticular spaces of solid matrices. In addition, the risk of bacterial contamination is reduced due to the low water activity (lower than 0 98) of the solid medium. Some interesting advantages of SSC processes compared with submerged cultivation are: higher productivities, lower operation costs and higher products concentration [1].

Multivariable model predictive control of a solid substrate pilot bioreactor: A simulation study

Modelling and control in solid substrate cultivation systems (SSC) are critical aspects that must be solved before scaling up the process to industrial level. SSC systems are difficult to understand due to the strong interaction among solid, liquid, gaseous and biotic phases. In addition, the lack of adequate sensors limits the identification of the process states.

Steric Approach for Growth Kinetics of Gibberella fujikuroi on 3D Solid Substrate

Abstract A 3D model for growth of filamentous fungi on solid substrate, based on microscopic obsērvations was developed and tested on macroscopic experimental data. Comparisons with previous models were performed. The specificity of solid substrate growth was taken into account in the model equations, and the adaptation of the model to the geometry of experiments led to interesting geometric considerations

On-line estimation of bed water content and temperature in a SSC bioreactor using a modular neural network model

Abstract A modular neural network model is developed in order to give on line estimations of bed water content and temperature in a SSC bioreactor. This grey box, predictive model gives accurate results for previous experiments carried out in the case of Gibberella fujikuroi SSC, and could be used for bioreactors on line monitoring.