Quantum machine learning driven optimization of nutrient-hormone interactions for enhanced in vitro regeneration of common bean.

ABSTRACT: Common bean (Phaseoulus vulgarsis) is an important edible legume crop, but its improvement through modern biotechnological tools has been limited due to the lack of efficient and reproducible in vitro regeneration protocols. This bottleneck restricts the application of biotechnological applications like genetic transformation, genome editing, and crop improvement. To address the challenges, an experiment was designed to investigate the combined effect of KNO₃ with Indole Butyric acid (IBA) and naphthalene acetic acid (NAA) on shoot proliferation using two different explants, followed by optimizing the results with quantum machine learning (QML) analysis. Results demonstrated enhanced shoot proliferation with increased KNO₃ levels (5700 mg/L), with a shoot count of 6.4

SUBMITTER: Katırcı R 

PROVIDER: S-EPMC12619191 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature