Detection of changes in leaf water content using Near- and Middle-Infrared reflectances

Abstract

Detection of plant water stress by remote sensing has been proposed using indices of Near-Infrared (NIR, 0.7–1.3 μm) and Middle-Infrared (MIR, 1.3–2.5 μm) wavelengths. The first objective of this study was to test the ability of the Leaf Water Content Index (LWCI) to determine leaf Relative Water content (RWC) of different species with different leaf morphologies. The second objective was to determine how the Moisture Stress Index (MSI; MIR / NIR) varies with RWC and the Equivalent Water Thickness (EWT). Reflectance factors at 0.82 μm and 1.6 μm were measured on leaves of Quercus agrifolia (sclerophyllous leaves), Liquidambar styraciflua (hardwood deciduous tree leaves), Picea rubens and Picea pungens (conifer needles), and Glycine max (herbaceous dicot leaves) as they dried on a laboratory bench. RWC and EWT were measured concurrently with the reflectance measurements. The results showed that LWCI was equal to RWC for the species tested. However, the results of a sensitivity analysis indicated the reflectances at 1.6 μm for two different RWC must be known for accurate prediction of unknown RWC; thus the LWCI is impractical for field applications. MSI was linearly correlated to RWCwith each species having a different regression equation and to log 10 EWT with data of all species falling on the same regression line. Because EWT is correlated with leaf area index, MSI should also be correlated with leaf area index. Assuming that the linear regression equation of MSI to EWT can be applied to canopies, then the minimum significant change of RWC that can be detected is 52%. For most plants, the natural variation in RWC from water stress is only about 20%, so that we conclude that indices derived from NIR and MIR reflectances cannot be used to remotely-sense water stress.