In this work, the analysis of the growth of Pleurotus pulmonarius in corn cob, using artificial neural networks and a logistic model was carried out. Biomass is quantified through the concentrations of protein (Kjeldahl method) and ergosterol (High performance liquid chromatography). The data obtained were analyzed with the Matlab and R programs. The best adjusted r2 of the logistic model was 0.9937 in the concentration for test by test protein analysis. For the artificial neural network model the root mean square error was 0.017 for the concentrations of protein and 11.394 for ergosterol. The results show that the logistic model and the artificial neural network model are useful tools for modeling solid fermentation. The best results were found for the concentration of protein.
|Título traducido de la contribución
|Analysis of biomass measurement in solid-state fermentation using neural networks and a logistic model
|Número de páginas
|Publicada - 2014
- Logistic model
- Pleurotus pulmonarius