Genotype-specific responses to <i>in vitro</i> drought stress in myrtle (<i>Myrtus communis</i> L.): integrating machine learning techniques.

ABSTRACT:

Background

Myrtle (Myrtus communis L.), native to the Mediterranean region of Türkiye, is a valuable plant with applications in traditional medicine, pharmaceuticals, and culinary practices. Understanding how myrtle responds to water stress is essential for sustainable cultivation as climate change exacerbates drought conditions.

Methods

This study investigated the performance of selected myrtle genotypes under in vitro drought stress by employing tissue culture techniques, rooting trials, and acclimatization processes. Genotypes were tested under varying polyethylene glycol (PEG) concentrations (1%, 2%, 4%, and 6%). Machine learning (ML) algorithms, including Gaussian process (GP), support vector machine (SVM), Random Forest (RF), and Extreme Gradient Boosting

SUBMITTER: Bektas U 

PROVIDER: S-EPMC11466237 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature