In silico analysis of decomposed reflectances of C3 and C4 plants aiming at the effective assessment of crop needs

By separating the surface and subsurface components of foliar hyperspectral signatures using polarization optics, it is possible to enhance the remote discrimination of different plant species and optimize the assessment of different factors associated with their health status. These initiatives, in turn, can lead to higher crop yield and lower environmental impact. It is important to consider, however, that the main varieties of crops, represented by C3 (e.g., soy) and C4 (e.g., maize) plants, have markedly distinct morphological characteristics. Accordingly, the influence of these characteristics on their interactions with impinging light may affect the selection of optimal probe wavelengths for specific applications making use of combined hyperspectral and polarization measurements. In this paper, we compare the sensitivity of the total (including surface and subsurface components) and subsurface reflectance responses of C3 and C4 plants to different spectral and geometrical light incidence conditions. This investigation is supported by measured biophysical data and predictive light transport simulations. The results of our comparisons indicate that the total and subsurface reflectance responses of C3 and C4 plants depict well-defined patterns of sensitivity for varying illumination conditions. We believe that these patterns should be considered in the design of high-fidelity crop discrimination and monitoring procedures. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.