Making waves in Breedbase: An integrated spectral data storage and analysis pipeline for plant breeding programs

Abstract

Abstract Visible and near‐infrared spectroscopy (Vis‐NIRS) is a promising tool for increasing phenotyping throughput in plant‐breeding programs, but existing analysis software packages are not optimized for a breeding context. Additionally, commercial software options are often outside of budget constraints for some breeding and research programs. To that end, we developed an open‐source R package, waves , for the streamlined analysis of spectral data with several cross‐validation schemes to assess prediction accuracy. waves is compatible with a wide range of spectrometer models and performs visualization, filtering, aggregation, cross‐validation set formation, model training, and prediction functions for the association of Vis‐NIR spectra with reference measurements. Furthermore, we have integrated this package into the Breedbase family of open‐source databases, expanding the analysis capabilities of this growing digital ecosystem to a number of crop species. Taken together, the standalone and Breedbase versions of waves enhance the accessibility of tools for the analysis of spectral data during the plant breeding process.