Abstract
Plant cell, tissue and organ culture (PCTOC) is extensively used to propagate faster and more plants, to produce virus-free plants, and secondary metabolites production as well. This requires the optimization of PCTOC conditions for each plant and final aim. Optimizing the micropropagation is time-consuming and costly, because it is different from the plant and even for each variety. In addition requires the optimization of the concentration and type of hormone and the type of explants for each variety in the stages of callogenesis, embryogenesis, shooting and rooting. Hence, today researchers have used Data Mining with using an artificial neural network (ANN) to predict the best conditions for tissue culture and saved time and money considerably. In this research, radial basis function (RBF) model was used to predict the best conditions for carrot tissue culture and the results showed that the highest and the least sensitivity were related to variety and percentage of Agar in liter, respectively. The results prediction of the RBF model showed that the percentage of embryogenesis was 62.5%, but the percentage of embryogenesis in laboratory obtain 75%. The results showed that the RBF model is a good model to predict the results.
Choosing the best embryogenesis medium in carrot by data mining technology