Prediction of the Growth Rates of Pseudomonas sp. in Seafood Based on Artificial Neural Network (ANN) Model

ABSTRACT

The aim of this study is to predict the growth rate (µmax) of Pseudomonas sp. in seafood under different temperature -2 - 25°C and modified atmosphere packaging (MAP) conditions. At total 52 µmax were compiled from the literature to develop and 68 different µmax values to validate the ANN model. For the development of ANN model different transfer functions were applied and based on the bias (Bf) (0.91) and accuracy factors (Af) (1.60) 3 layers 10 neurons with purelin transfer function was assumed to be best topology to predict the µmax of Pseudomonas sp. in seafood.

KEYWORDS:

• Predictive microbiology
• mathematical modeling
• seafood
• ANN

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author [Genç, I.Y.] upon reasonable request.