Hyperspectral 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)
Progress made on the detection of stress in heterogeneous crop canopies with hyperspectral remote se...
Remote sensing technologies are widely used to monitor quantity and quality of plants in agriculture...
The increasing need to develop a rapid understanding of plant functional dynamics has led to the emp...
This hyperspectral imagery (HSI) dataset contains scans of Arabidopsis leaf samples under three trea...
Hyperspectral imaging sensors are promising tools for monitoring crop plants or vegetation in differ...
Close-range hyperspectral imaging (HSI) of plants is now a potential tool for non-destructive extrac...
Hyperspectral imaging can generate spatial chemical information in plants. The imaging acquisition s...
Close-range hyperspectral imaging (HSI) of plants is now a potential tool for non-destructive extrac...
Hyperspectral imaging is a technique with an increasing range of applications in plant science. Here...
High spectral resolution in hyperspectral images and their ability of imaging in narrow bands, make ...
The potential of close-range hyperspectral imaging (HSI) as a tool for detecting early drought stres...
Abstract Background Remote monitoring of plants using hyperspectral imaging has become an important ...
Ornamental heather (Calluna vulgaris) production is characterized by high risks such as occurrence o...
With the implementation of novel automated, high throughput methods and facilities in the last years...
High-throughput phenotyping is becoming a critical method for many plant science researchers. Compar...
Progress made on the detection of stress in heterogeneous crop canopies with hyperspectral remote se...
Remote sensing technologies are widely used to monitor quantity and quality of plants in agriculture...
The increasing need to develop a rapid understanding of plant functional dynamics has led to the emp...
This hyperspectral imagery (HSI) dataset contains scans of Arabidopsis leaf samples under three trea...
Hyperspectral imaging sensors are promising tools for monitoring crop plants or vegetation in differ...
Close-range hyperspectral imaging (HSI) of plants is now a potential tool for non-destructive extrac...
Hyperspectral imaging can generate spatial chemical information in plants. The imaging acquisition s...
Close-range hyperspectral imaging (HSI) of plants is now a potential tool for non-destructive extrac...
Hyperspectral imaging is a technique with an increasing range of applications in plant science. Here...
High spectral resolution in hyperspectral images and their ability of imaging in narrow bands, make ...
The potential of close-range hyperspectral imaging (HSI) as a tool for detecting early drought stres...
Abstract Background Remote monitoring of plants using hyperspectral imaging has become an important ...
Ornamental heather (Calluna vulgaris) production is characterized by high risks such as occurrence o...
With the implementation of novel automated, high throughput methods and facilities in the last years...
High-throughput phenotyping is becoming a critical method for many plant science researchers. Compar...
Progress made on the detection of stress in heterogeneous crop canopies with hyperspectral remote se...
Remote sensing technologies are widely used to monitor quantity and quality of plants in agriculture...
The increasing need to develop a rapid understanding of plant functional dynamics has led to the emp...