Light Stress Detection in <i>Ficus elastica</i> with Hyperspectral Indices

Abstract

The development of methods to detect plant stress is not only a scientific challenge, but is also of great importance for agriculture and forestry. However, at present, stress diagnostics based on plant spectral characteristics has several limitations: (1) the high dependence of stress assessment on plant species identity; (2) the poor differentiation of different types of stress; and (3) the difficulty of detecting stress before visible symptoms appear. In this regard, the development of plant spectral metrics represents a significant area of research. Ficus elastica plants were exposed under the photosynthetic photon flux density (PPFD) from 0 to 1200 μmol photons m−2s−1. Exposure of F. elastica leaves to excess light (EL) (≥400 μmol photons m−2s−1) resulted in an increase in reflectance in the yellow-green region (522–594 nm) and a decrease in reflectance in the red region (666–682 nm) of the spectrum, accompanied by a shift of the red edge point toward the longer wavelength. These changes were revealed using the previously proposed light stress index (LSI = mean(R666:682)/mean(R522:594)). Based on the results obtained, two new vegetation indices (VIs) were proposed: LSIRed = R674/R654 and LSINorm = (R674 − R654)/(R674 + R654), indicating light stress by changes in the red region of the spectrum. The results of the study showed that LSI, LSIRed, and LSINorm have a high degree of coupling strength with maximal quantum yields of photosystem II values. The plant response to EL exposure, as assessed by the values of these three VIs, was well expressed regardless of the PPFD levels. The effect of EL at non-stressful PPFDs (50–200 μmol photons m−2s−1) was found to disappear within one hour after cessation of exposure. In contrast, the effect of the stressful PPFD (800 μmol photons m−2s−1) was found to persist for at least 80 h after cessation of exposure. The results of the study indicate the need to consider light history in spectral monitoring of vegetation.

Keywords

• hyperspectral imaging
• photoinhibition
• quantum yield of photosystem II
• light stress index
• excessive light
• light starvation