%0 Journal Article
%T Predicting grain yield using canopy hyperspectral reflectance in wheat breeding data
%A Abelardo Montesinos-L¨®pez
%A Gregorio Alvarado
%A Gustavo de los Campos
%A Jessica Rutkoski
%A Jos¨¦ Crossa
%A Juan BurgueŁżo
%A Lorena Gonz¨˘lez-P¨¦rez
%A Mondal Suchismita
%A Osval A. Montesinos-L¨®pez
%J Archive of "Plant Methods".
%D 2017
%R 10.1186/s13007-016-0154-2
%X Modern agriculture uses hyperspectral cameras to obtain hundreds of reflectance data measured at discrete narrow bands to cover the whole visible light spectrum and part of the infrared and ultraviolet light spectra, depending on the camera. This information is used to construct vegetation indices (VI) (e.g., green normalized difference vegetation index or GNDVI, simple ratio or SRa, etc.) which are used for the prediction of primary traits (e.g., biomass). However, these indices only use some bands and are cultivar-specific; therefore they lose considerable information and are not robust for all cultivars
%K Spectral data
%K Vegetation indexes
%K Prediction accuracy
%K Genome selection
%K Bayes B
%K Spline regression
%K Fourier regression
%K Wheat
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5209864/