PLANT trait data, which once took hours or even days to collect, can now be gathered in seconds, thanks to a world-first machine unveiled in Adelaide a fortnight ago.
The FieldExplorer, built in The Netherlands but designed largely in Australia with CropTraits Pty Ltd and Phenokey in the Netherlands, and the Australian Plant Phenomics Facility's node at the University Adelaide's Waite campus, is a platform that rapidly gathers data on the physical characteristics of plants - the phenotype - using an array of sensors that take measurements non-destructively.
The FieldExplorer has three types of sensors on board, which are located within a cabinet with supplemental illumination in the form of halogen lighting, to provide consistent imaging conditions regardless of cloud cover.
A Light Detection and Ranging sensor creates a 3D reconstruction of a crop canopy and subsequently gives an estimate of crop biomass, while a Red Green Blue camera collects high-resolution colour imagery data, and is used for measuring visual traits of a plant, such as discolouration, which can provide an insight into crop diseases.
Two hyperspectral imaging cameras are also on board, which enable measurement of physiological traits, such as photosynthetic parameters and plant nutrient status.
The FieldExplorer moves at about one metre per second, collecting data which is then time stamped with GPS coordinates, then allowing the "stitching together" of data, according to APPF technology and development lead Darren Plett.
This can allow us come up with new varieties or better understand what is going on much easier, much quicker.
- DARREN PLETT
"LiDAR technology has been around for 15 to 20 years, hyperspectral cameras have been around for a while too, but the fusion of the different sensor data together is a really big stride forward," he said.
"When gathering data previously, it would have involved sorting, drying, weighing and an assay, but now we can just drive over the crop and collect information about a crop in a non-destructive way."
Mr Plett said the ability to collect data on crop disease was extremely beneficial and a major step forward from existing disease scoring systems, which were often subjective.
"Instead of having five distinct categories of disease severity, we can have an infinite number, and so for breeding purposes or genetics, you open up that possibility in the field that you couldn't do before with a one to five disease scoring system," he said.
"The FieldExplorer can speed up what we can measure, and it can measure it more accurately than we have been able to previously.
"This can allow us come up with new varieties or better understand what is going on much easier, much quicker."
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The FieldExplorer is 2.4 metres wide and 5.8m long, with the imaging cabinet able to be moved up and down to cater for different plant heights. Wheel width is also adjustable.
Looking forward, Mr Plett said there were plans to use data from the FieldExplorer to develop sensors that had both high specificity and mobility.
"We're hoping to get several years of data with this machine, and pick the most important wavelengths from the hyperspectral information to give a diagnosis of key traits like frost damage, and then design a multispectral sensor that only measures those wavelengths and can be flown on a drone, as something that growers or breeders can afford to use out in the field," he said.
APPF executive director Susie Robinson said the FieldExplorer's would be of major benefit for design of future phenotyping methods and devices.
"The FieldExplorer serves the dual purpose of answering immediate scientific questions about the plants and how they're functioning, but the platform itself becomes and innovation pipeline itself to simplify and improve future research infrastructure and tools," she said.
FieldExplorer attracts interest early
DESPITE getting to Adelaide just a few weeks ago, the FieldExplorer is already listed to be used in 14 research trials across the state in the coming year.
One trial near Naracoorte is using satellite imagery to determine if forage plants in an area are ready for grazing, with the FieldExplorer being brought in to provide "ground truthing".
Another will have the machine looking at oaten hay, using the Light Detection and Ranging scanner to measure biomass, and hyperspectral imaging to measure feed quality.
Other trials are looking at disease management - ascochyta blight in chickpea and crown rot in wheat - and also frost management, with others using the FieldExplorer to automate the process of pod counts and flower counts in the field.
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