Abstract

Soybean (Glycine max L. Merr) is a commercially important crop that is sensitive to most abiotic stresses. Successful genetic transformation that has been widely used for yield improvements of many commercial crops needs efficient and reproducible plant regeneration protocols, in which the optimum concentrations of plant growth regulators play crucial roles. Here, response surface methodology was successfully employed to find proper combinations of plant growth regulators that facilitate more callus induction and shoot regeneration of soybean. Five concentrations of 2,4-dichlorophenoxyacetic acid (2,4-D) and kinetin (Kin) were selected as the two independent variables in a central composite design, and quadratic models were generated and evaluated by proper statistical measures. The best combination of plant hormones, which facilitate more callus induction and shoot regeneration, using shoot, root, and leaf explants, was predicted and evaluated. These findings suggest that statistical modeling can be employed to estimate the approximate range of plant growth regulators needed for successful in vitro plant regeneration of various soybean cultivars, with potential applications in plant genetic transformation practices.

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