Simulation and prediction of the thuringiensin abiotic degradation processes in aqueous solution by a radius basis function neural network model

Abstract

The thuringiensin abiotic degradation processes in aqueous solution under different conditions, with a pH range of 5.0–9.0 and a temperature range of 10–40°C, were systematically investigated by an exponential decay model and a radius basis function (RBF) neural network model, respectively. The half-lives of thuringiensin calculated by the exponential decay model ranged from 2.72d to 16.19d under the different conditions mentioned above. Furthermore, an RBF model with accuracy of 0.1 and SPREAD value 5 was employed to model the degradation processes. The results showed that the model could simulate and predict the degradation processes well. Both the half-lives and the prediction data showed that thuringiensin was an easily degradable antibiotic, which could be an important factor in the evaluation of its safety.