Prediction of organogenesis of using artificial neural networks and regression models.

This study was conducted to determine if artificial neural networks (ANN) can be used to accurately predict organogenesis of compared with statistical regression. Prediction models were developed for shoot and root organogenesis (outputs) on two culture media (Murashige and Skoog and Gamborg B5) affected by two explant types (leaf and node) and two cytokinins (6-Benzylaminopurine and Thidiazuron at 1.0, 5.