BP-ANN for fitting the temperature-germination model and its application in predicting sowing time and region for bermudagrass

Temperature is one of the most significant environmental factors that affects germination of grass seeds. Reliable prediction of the optimal temperature for seed germination is crucial for determining the suitable regions and favorable sowing timing for turf grass cultivation. In this study, a back-propagation-artificial-neural-netwo?rk-aideddual quintic equation (BP-ANN-QE) model was developed to improve the prediction of the optimal temperature for seed germination. (cont.)