Field Scanalyzer

AUTOMATED OUTDOOR PHENOTYPING

The FIELD SCANALYZER is a fully automated system designed to capture deep phenotyping data from crops and other plants growing in field environments. A rigid motorised gantry supports a weatherproof measuring platform that incorporates a wide range of cameras, sensors and illumination systems. The FIELD SCANALYZER delivers highly detailed information to monitor growth and physiology continuously, throughout the lifetime of plants.

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Sensor Bay

All sensors are mounted in a separate weather-proof cabinet which is moved over the field by the supporting gantry. The maximum total payload of the sensor bay is 500 kg which allows for additional sensors if required.

The sensor bay contains a range of cameras together with dedicated illumination devices. It also contains equipment for sensing environmental data.

Expemplary sets of sensors: Rothamsted and TERRA-REF configurations.

Sensor functions

Visible light imaging delivers photographs that can be processed for dimensions, morphology, and colour of the samples. They are widely used to monitor growth, development, or environmental responses of plants and canopies.

Infrared imaging delivers images representing the heat emission from the sample surface. Such images can serve to measure canopy temperatures and can be related to transpirational processes.

Hyperspectral imaging, also known as imaging spectrometry, is widely used in remote sensing. The FIELD SCANALYZER is able to image at close range (2.2 m above the canopy) and with high repeatability. Hyperspectral cameras produce a stack of images (hyperspectral data cube), where each image represents a narrow wavelength range of the electromagnetic spectrum.

PS2 Fluorescence analysis addresses status and functions of the chlorophylls that are main components of the light harvesting complexes. The system emits an intense LED flash for 1 second during which 25 images are recorded. From these images variable fluorescence (Fv) can be compared to the saturation level of fluorescence (Fm) and used to assess quantum yield of the PS2 photochemistry.

Laser Scanners are able to scan the plant canopy with very high cubicle resolution using an NIR Laser (840 nm) to ensure high reflectance by plant tissue and minimal physiologic interaction (eg chlorophyll excitation). Below is an example of coarse synthetic point cloud for field data, visualized with white points using shading for a better characterization. A height map can be extracted by encoding the height with colour.

As phenotypes strongly depend on environmental influences, particularly when plants grow in a field, environmental sensors are important to deliver data on factors such as temperature or light. These environmental data are stored together with the camera measurements.

Technical Specifications

Sensor options

RGB Visible
Chlorophyll Fluorescence
Infrared
Hyperspectral
3D Laser Scanner

Environmental sensors

Application examples

Canopy height
Plant geometry
Biomass
Counting features
Vegetation indices
Photosynthetic efficiency

Typical addressable crop area

10 m x 110 m

Control

Dedicated Windows PC plus database server(s)

Software

Process control, Image recording and processing, Data analysis

HYPLASRGBPS2IR
Direct Measures
Size
Morphology
Colour
Surface heat emission

unusual but maybe possible

Applications

Wheat Ears Segmentation

This process may be used to propose the development stage of the wheat by analysing the size of the ears.

Show Application

References

2017

  • Sadeghi-Tehran, Pouria; Sabermanesh, Kasra; Virlet, Nicolas; Hawkesford, Malcolm J. (2017)

    Automated Method to Determine Two Critical Growth Stages of Wheat: Heading and Flowering. In: Front. Plant Sci. (Frontiers in Plant Science), S. 252. DOI: 10.3389/fpls.2017.00252. http://journal.frontiersin.org/article/10.3389/fpls.2017.00252/full

2016

  • Nicolas Virlet, Kasra Sabermanesh, Pouria Sadeghi-Tehran and Malcolm J. Hawkesford (2016)

    Field Scanalyzer: An automated robotic field phenotyping platform for detailed crop monitoring. In: CSIRO Publishing. http://www.publish.csiro.au/fp/FP16163