Developed by Abhijith et al. (2025)
ICAR-Indian Agricultural Research Institute, Assam

Contact for reporting bugs, queries, or feedback:

abhijithkpgen@gmail.com

Released under the GPL-3.0 License.

Interactive Field Plot

Hover over the plots to see details. Use the tools in the top-right corner to pan, zoom, and save a static image.

Generated Field Layout Table

This table shows the randomized layout for your experiment. You can sort, search, and copy the data.

Which Won Where

Mean vs Stability

Representativeness vs Discriminativeness

PCA Individual Biplot

Scree Plot

Variable Contributions

PCA Summary Table

About PbAT


Hi,

Thanks for checking out, PbAT.

Statistical analysis lies at the heart of plant breeding, but too often, the complexity of coding stands in the way. We understand that, sometimes researchers end up spending more time wrestling with programming than advancing their science.

Thats why we created PbAT (Plant Breeding Analytical Tools).

PbAT is a free, open-access web application designed to break down those barriers. It unifies the entire analytical pipeline, trial design, data curation, experimental design analyses, stability assessments, multivariate approaches, and mating designs into one seamless, code free workflow.

We hope PbAT makes your analyses simpler, and we would be delighted if you could share your feedback, constraints, suggestions and obviously the bugs at abhijithkpgen@gmail.com to help us further improve the application.

We invite you to explore PbAT, streamline your analysis, and spend more time where it matters most, on discovery and innovation in plant breeding.


Sincerely,

The PbAT Team

Citation Recommendations

If you use PbAT in your research, please cite this application and if you happen to use any of these below analyses please cite the core R packages that perform the analyses.

For the PbAT Application:

Abhijith, K. P., Vinod, K. K., Ellur, R. K., Ravikiran, K. T., Saxena, R. K., Muthusamy, V., & S, Gopalakrishnan. (2025).PbAT: Plant Breeding Analytical Tools (v1.0.5). Zenodo. https://doi.org/10.5281/zenodo.17020132

For Path Analysis:

Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36.

For Stability Analysis (AMMI/GGE):

Olivoto, T., & Gabriel, L. (2019). metan: An R package for multi-environment trial analysis. Methods in Ecology and Evolution, 10(6), 760-768.

For Mixed Model Analysis:

Bates, D., Mchler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48.

For Principal Component Analysis (PCA):

Kassambara, A., & Mundt, F. (2020). factoextra: Extract and Visualize the Results of Multivariate Data Analyses. R package version 1.0.7.

For Graphical Outputs:

Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York.

Help & Guide

Sample Data Downloads

Disclaimer: The example datasets provided in this application are simulated for demonstration purposes only. They do not represent actual experimental results and should not be used for research conclusions.

Troubleshooting Common Issues

Encountering an issue? Most problems with complex model analyses are related to network connection timeouts or temporary rendering glitches. Here are a few simple steps you can take to resolve common errors.

Problem: Results Not Appearing After Running an Analysis or incomplete user interface appear after proceeding to analysis

Cause: This can happen when either the app hasnt loaded full or incases where an analysis takes a while to complete, especially on a slower internet connection, or if there's a temporary glitch while displaying the results. The analysis likely finished successfully on the server, but the results weren't displayed correctly in your browser.

Solutions (Try these in order):

  • 1. Reload and Rerun:
    This is the easiest and most common fix. If the results area or input area is blank, simply reload the entire web page and run the analysis again. This resolves most temporary rendering issues.
  • 2. Ensure a Stable Internet Connection:
    Since these analyses involve sending data and waiting for results, a stable connection is key. If you are on a weak Wi-Fi signal, try moving closer to your router or connect to a more reliable network before rerunning the analysis.
  • 4. Be Patient:
    A complex mixed-model analysis on a large dataset can take some time. After clicking 'Run,' please allow up to a minute for the server to process before assuming there is an error.
  • 5. Use the R Package Locally:
    For very large datasets or complex multi-trait analyses, consider installing the PbAT R package and running it on your own computer for the smoothest and fastest experience.