guest ::
| Home > Publications database > Solar Induced Chlorophyll Fluorescence and Vegetation Indices for Heat Stress Assessment in Three Crops at Different Geophysics-Derived Soil Units > print |
| Home > Publications database > Solar Induced Chlorophyll Fluorescence and Vegetation Indices for Heat Stress Assessment in Three Crops at Different Geophysics-Derived Soil Units > print |
| 001 | 888900 | ||
| 005 | 20210130011158.0 | ||
| 024 | 7 | _ | |a 10.1002/essoar.10504968.1 |2 doi |
| 024 | 7 | _ | |a 2128/26564 |2 Handle |
| 037 | _ | _ | |a FZJ-2020-05305 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Quirós, Juan |0 P:(DE-Juel1)178996 |b 0 |e Corresponding author |
| 111 | 2 | _ | |a American Geophysical Union (AGU) Fall Meeting |c Online |d 2020-12-01 - 2020-12-17 |w United States |
| 245 | _ | _ | |a Solar Induced Chlorophyll Fluorescence and Vegetation Indices for Heat Stress Assessment in Three Crops at Different Geophysics-Derived Soil Units |
| 260 | _ | _ | |c 2020 |
| 300 | _ | _ | |a 2 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1608128158_3068 |2 PUB:(DE-HGF) |
| 520 | _ | _ | |a 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 (SIF =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, SIF data showed a clearer differentiation of the stress conditions at a terrace level in potato and sugar beet. However, towards the end of the wave a significant decrease of MTCI and NDVI contrasted with higher SIF in sugar beet and corn. Nonetheless, those crops (sugar beet and corn) did not show significant SIF differences between terraces. A significant spatial match was found 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). This suggests the higher sensitivity of SIF to monitor heat stress compared with common VIs. |
| 536 | _ | _ | |a 89582 - Plant Science (POF2-89582) |0 G:(DE-HGF)POF2-89582 |c POF2-89582 |f POF II T |x 0 |
| 536 | _ | _ | |a TRuStEE - Training on Remote Sensing for Ecosystem modElling (721995) |0 G:(EU-Grant)721995 |c 721995 |f H2020-MSCA-ITN-2016 |x 1 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Brogi, Cosimo |0 P:(DE-Juel1)168418 |b 1 |
| 700 | 1 | _ | |a Krieger, Vera |0 P:(DE-Juel1)172754 |b 2 |u fzj |
| 700 | 1 | _ | |a Siegmann, Bastian |0 P:(DE-Juel1)172711 |b 3 |u fzj |
| 700 | 1 | _ | |a Celesti, Marco |0 0000-0001-7249-7106 |b 4 |
| 700 | 1 | _ | |a Rossini, Micol |0 0000-0002-6052-3140 |b 5 |
| 700 | 1 | _ | |a Cogliati, Sergio |0 0000-0002-7192-2032 |b 6 |
| 700 | 1 | _ | |a Weihermüller, Lutz |0 P:(DE-Juel1)129553 |b 7 |
| 700 | 1 | _ | |a Rascher, Uwe |0 P:(DE-Juel1)129388 |b 8 |
| 773 | _ | _ | |a 10.1002/essoar.10504968.1 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/888900/files/essoar.10504968.1.pdf |y OpenAccess |
| 909 | C | O | |o oai:juser.fz-juelich.de:888900 |p openaire |p open_access |p driver |p VDB |p ec_fundedresources |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)178996 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)168418 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)172754 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)172711 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 7 |6 P:(DE-Juel1)129553 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 8 |6 P:(DE-Juel1)129388 |
| 913 | 1 | _ | |a DE-HGF |0 G:(DE-HGF)POF2-89582 |v Plant Science |x 0 |4 G:(DE-HGF)POF |1 G:(DE-HGF)POF3-890 |3 G:(DE-HGF)POF3 |2 G:(DE-HGF)POF3-800 |b Programmungebundene Forschung |l ohne Programm |
| 914 | 1 | _ | |y 2020 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 920 | 1 | _ | |0 I:(DE-Juel1)IBG-2-20101118 |k IBG-2 |l Pflanzenwissenschaften |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)IBG-3-20101118 |k IBG-3 |l Agrosphäre |x 1 |
| 980 | _ | _ | |a contrib |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)IBG-2-20101118 |
| 980 | _ | _ | |a I:(DE-Juel1)IBG-3-20101118 |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|