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Fig. 2 | BMC Biotechnology

Fig. 2

From: Prediction and optimization of indirect shoot regeneration of Passiflora caerulea using machine learning and optimization algorithms

Fig. 2

The schematic representation of the step-by-step methodology of the current study including (a) dataset consists of inputs (i.e., callus type, 6-benzylaminopurine (BAP), indole-3-butyric acid (IBA), kinetin (KIN), putrescine (PUT), and thidiazuron (TDZ)) and outputs (i.e., regeneration rate, shoot number, and shoot length), (b, c), data modeling through generalized regression neural network (GRNN) and random forest (RF), respectively, and (d) optimization process through a genetic algorithm (GA).

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BMC Biotechnology

ISSN: 1472-6750

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