PbAT: A user-friendly R/Shiny platform for data-driven decision support in crop improvement

Modern plant breeding requires robust analysis of complex, multi-environment datasets to identify superior genotypes. Although R offers powerful statistical packages, their use often requires programming expertise. Existing graphical user interface (GUI)-based tools are either limited in scope or not openly accessible, leaving breeders without a comprehensive solution.

We introduce PbAT (Plant breeding Analytical Tools), an open-access Shiny application that unifies multiple R packages into a seamless, code-free workflow. PbAT enables trial design, data curation, experimental design analysis, stability testing, multivariate methods, and mating design analysis. Outputs include variance components, best linear unbiased estimators (BLUEs), best linear unbiased predictors (BLUPs), ANOVA tables, and publication-ready plots, accompanied by automated plain-language interpretations and model equations. Its modular architecture supports future integration of additional tools. PbAT is available online as a web application (https://pbat.online) and as an R package (https://github.com/abhijithkpgen/PbAT).

By integrating powerful statistical methods with intuitive interfaces, PbAT streamlines plant breeding analytics, enhances reproducibility, and accelerates data-driven decision-making in crop improvement.