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Table 4 Optimizing PGRs according to optimization process via SVR-NSGAII for embryo number and embryogenesis rate in chrysanthemum

From: Development of support vector machine-based model and comparative analysis with artificial neural network for modeling the plant tissue culture procedures: effect of plant growth regulators on somatic embryogenesis of chrysanthemum, as a case study

input variable (μM) Predicted embryogenesis rate Predicted embryo number
2,4-D KIN SNP
9.10 4.70 18.73 99.09 56.23