Evaluation of forage quality in a pea breeding program using a hyperspectral sensing system

The dataset includes the leaf reflectance spectra collected using a spectroradiometer and the associated biomass quality traits from laboratory-based near-infrared reflectance spectroscopy (NIRS) analysis from pea breeding trials. The data is used for analysis in the publication "Evaluation of Forage Quality in a Pea Breeding Program Using a Hyperspectral Sensing System".

This study was funded by Washington State University's Center for Sustaining Agriculture and Natural Resources BIOAg Program (project ID 184) and the US Department of Agriculture-National Institute of Food and Agriculture (USDA-NIFA) Hatch and Multi-State Hatch projects (accession number 1014919, NC1212).

Related Organizations

Washington State University
United States

Keywords

machine learning; feature importance; first derivative reflectance; vegetation index; normalized difference spectral index; ratio spectral index; random forest regression

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