Modelling fungal growth using radial basis function neural networks: the case of the ascomycetous fungus Monascus ruber van Tieghem.

@article{Panagou2007ModellingFG,
  title={Modelling fungal growth using radial basis function neural networks: the case of the ascomycetous fungus Monascus ruber van Tieghem.},
  author={Efstathios Z Panagou and V. S. Kodogiannis and George-John E Nychas},
  journal={International journal of food microbiology},
  year={2007},
  volume={117 3},
  pages={276-86}
}
A radial basis function (RBF) neural network was developed and evaluated against a quadratic response surface model to predict the maximum specific growth rate of the ascomycetous fungus Monascus ruber in relation to temperature (20-40 degrees C), water activity (0.937-0.970) and pH (3.5-5.0), based on the data of Panagou et al. [Panagou, E.Z., Skandamis, P.N., Nychas, G.-J.E., 2003. Modelling the combined effect of temperature, pH and aw on the growth rate of M. ruber, a heat-resistant fungus… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 15 extracted citations

Modelling the effect of environmental factors on the hyphal growth of the basidiomycete Physisporinus vitreus

M. J. Fuhra, C. Stührka, M. Schuberta, F. W. M. R. Schwarzeb, H. J. Herrmanna
2011
View 1 Excerpt

Similar Papers

Loading similar papers…