Monitoring Drought Stress in Raspberry Plants (Rubus idaeus L.) Using Hyperspectral Thermal Infrared Remote Sensing

摘要

Herbicide application efficiencies over conifer plantations for suppressing wild raspberry may be related to drought conditions. In our study, we investigated the potential of hyperspectral reflectances and surface radiative temperature to detect drought stress among raspberry plants under laboratory conditions. Spectral measurements acquired in the 400-2500 nm at a fine spectral resolution showed that control plants have a significantly lower reflectance than stressed plants, mainly in the near-infrared and shortwave infrared regions. At the leaf level, we were able to define two hyperspectral indices (ρ_(548)/ρ_(720) andρ_( 1335)/ρ_(588)) that were correlated to leaf water potentials. The first index worked the best for plants growing on promix, whereas the second works the best for plants growing over sandy soils. In. contrast to the optical hyperspectral bands, surface radiative temperatures worked better at the plant level than at the leaf level. Small sample size, however, may have limited any significant results obtained from the surface temperature measurements.