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

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 2.72 d to 16.19 d 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.

► Thuringiensin was highly unstable in aqueous phase.
► The degradation parameters of thuringiensin was firstly characterized.
► The degradation process was simulated by an RBF ANN model.
► An optimized RBF model could well predict the thuringiensin degradation process.