10.26165/JUELICH-DATA/OM1JKZAcebron, KelvinKelvinAcebron0000-0002-8523-0256IBG-2 Plant Sciences, Forschungszentrum JuelichJülich DATA2022Agricultural SciencesHyperspectral dataphotochemical reflectance indexnormalized difference vegetation indexAcebron, KelvinKelvinAcebronIBG-2 Plant Sciences, Forschungszentrum Juelich2022-03-222022-03-2210.3390/s180204412799316696106954752134927972088961231208065144913928721390950431463475241894149389230141523734146207802514584326195775461613065128001992208896application/octet-streamimage/pngapplication/octet-streamtext/xmlapplication/octet-streamapplication/octet-streamtext/xmlapplication/vnd.openxmlformats-officedocument.spreadsheetml.sheetimage/pngimage/pngtext/x-fixed-fieldapplication/octet-streamimage/pngapplication/vnd.openxmlformats-officedocument.spreadsheetml.sheetapplication/vnd.openxmlformats-officedocument.spreadsheetml.sheetimage/pngimage/pngimage/pngimage/pngimage/pngapplication/octet-streamapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/octet-streamapplication/octet-streamapplication/octet-stream1.0Hyperspectral imaging is a technique used in plant phenotyping which can detect differences in plant traits. Information about the morphology and physiology of plants can be derived by calculating spectral ratios (Vegetation Indices) from hyperspectral datacube. Here we publish the datacube from Arabidopsis plants used as a case study to calculate vegetation indices (NDVI, REIP and PRI) from stressed and non-stressed plants. Files include raw data from IQ camera, analyzed data from ENVI and MatLab software, and visualized in MS Excel. Detailed description of the dataset and methodology used is published in Behmann et al., 2018 (Sensors).