Online tool to predict wheat leaf photosynthetic traits from hyperspectral leaf reflectance

V Silva-Perez1, A Ivakov2, JR Evans2, RT Furbank1,2 and AG Condon1

  1. CSIRO Agriculture, Canberra, ACT 2601, Australia
  2. Research School of Biology. The Australian National University. Canberra, ACT 2601, Australia

Hyperspectral leaf reflectance and partial least square regression have been used to predict Rubisco (Vcmax) and electron transport (J) capacity, leaf mass per unit area (LMA), chlorophyll and nitrogen content in wheat. To establish the method, data for each trait was collected from a range of wheat varieties grown and measured in both the field and greenhouse. As most wheat leaves are narrower than the optical window in the leaf clip supplied with the portable spectrometer, a mask was developed that restricts the sampling view to 11.5mm width. To facilitate the broader use of hyperspectral data to phenotype individual plants, a friendly internet-based tool was developed. In the website, it is possible to upload reflectance spectra measured with the ASD Field Spec spectrometer (350 to 2500 nm) and obtain model predictions for Vcmax, J, LMA and Narea. This tool enables anyone measuring hyperspectral leaf reflectance in wheat with this instrument to obtain parameter estimates for these traits without requiring them to have any knowledge of the partial least square regression methodology.