Optimizing PGRs for in vitro shoot proliferation of pomegranate with bayesian-tuned ensemble stacking regression and NSGA-II: a comparative evaluation of machine learning models
Saeedeh Zarbakhsh,
Ali Reza Shahsavar,
Mohammad Soltani
Abstract:Background
The process of optimizing in vitro shoot proliferation is a complicated task, as it is influenced by interactions of many factors as well as genotype. This study investigated the role of various concentrations of plant growth regulators (zeatin and gibberellic acid) in the successful in vitro shoot proliferation of three Punica granatum cultivars (‘Faroogh’, ‘Atabaki’ and ‘Shirineshahvar’). Also, the utility of five Machine Learning (ML) algorithms—Support Vector Regression (SVR), Ra… Show more
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