B006-0002
Solar Induced Chlorophyll Fluorescence and Vegetation Indices for Heat Stress Assessment in Three Crops at Different Geophysics-Derived Soil Units

Monday, 7 December 2020
Poster
Juan Quiros1, Cosimo Brogi2, Vera Krieger1, Bastian Siegmann1, Marco Celesti3, Micol Rossini3, Sergio Cogliati3, Lutz Weihermueller2 and Uwe Rascher1, (1)Forschungszentrum Jülich, IBG-2: Plant Sciences, Jülich, Germany, (2)Forschungszentrum Jülich, IBG-3: Agrosphere, Jülich, Germany, (3)University of Milano - Bicocca, Department of Earth and Environmental Sciences, Milan, Italy
Abstract:
Remotely-sensed Solar Induced chlorophyll Fluorescence (SIF) is a novel promising tool to retrieve information on plants’ physiological status due to its direct link with the photosynthetic process. At the same time, narrow band Vegetation Indices (VIs) such as the MERIS Terrestrial chlorophyll index (MTCI), and the Photochemical Reflectance Index (PRI), as well as broad band VIs like the Normalized Difference Vegetation Index (NDVI), have been widely used for crop stress assessment. A match between these remote sensing products and the spatial distribution of soil units is expected; nevertheless, an in-depth analysis of such relationship has been rarely performed so that additional studies are required.

In this contribution, we aimed at the comparison in the use of normalized SIF (SIFnorm = SIF/PAR; computed with the Spectral Fitting Method, SFM) and VIs (MTCI, PRI and NDVI) for heat stress assessment in corn, sugar beet and potato at the beginning and towards the end of a heatwave occurring in Selhausen, Germany, 2018. Data were acquired with the HyPlant airborne sensor, which is a high performance imaging spectrometer with around 0.30 nm of spectral resolution in the Oxygen absorption bands. We compared different plots located in the upper (poorer soil characteristics for agriculture such as water holding capacity and content of coarse sediments) or lower landscape terraces; we also evaluated the different remote sensing products in comparison with site specific geophysics-based soil maps.

At the beginning of the heat wave we found that, compared with VIs, SIFnorm data showed a clearer differentiation of the stress conditions of the three crops at a terrace level. However, towards the end of the wave the characteristic leaf yellowing, translated in a significant decrease of MTCI and NDVI, contrasted with higher SIFnorm in sugar beet and corn. At the same time, those crops did not show significant SIFnorm differences between terraces. Based on these results, the observed SIF data well represents the crops physiological status. Furthermore, we observed a significant spatial match between SIF and geophysics-derived soil spatial patterns (p = 0.004-0.030) in fields where NDVI was more homogeneous (p = 0.028-0.499, respectively), suggesting the higher sensitivity of SIF to monitor heat stress compared with common VIs.

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