SPRAYING TECHNOLOGY ▶▶▶
treatment, as appropriate for weed type and population density.
Kuhn-Blanchard is adopting Carbon Bee AgTech’s AQiT-Sensor hyperspectral imagery technol- ogy for weed location and identification.
fundamental research in the 1990s at Wagen- ingen University in the Netherlands does the same. Trimble’s WeedSeeker sensors can be mounted up to 30 at a time on broadacre spray booms up to 45m (150ft) wide, with settings for up to 16km/h (10mph) or 32km/h (20mph) working speeds, operating day or night. Rometron’s WEEDit Ag system uses sensors scanning a 1m band of soil 40,000 times per second while emitting red light. This is ab- sorbed by chlorophyll in the foliage of plants, resulting in near infrared (NIR) light being re- flected back to the sensors. When a weed shows up, the system recognises an increase in the ratio of near-infrared to red light and
activates a solenoid valve to deliver a pre- mixed herbicide spray. It can be fitted to new sprayers, or as a retro-fit installation on booms up to 36m (118ft) wide. In Europe, the Rometron technology has been adopted by Amazone as the AmaSpot system. It is availa- ble on 4,200- and 5,200-litre UX trailed spray- ers equipped with a purpose-made 24m (78ft) boom and Agrotop nozzles with pulse width frequency modulation (PWFM) output control. This approach enables each nozzle to deliver from 100% to 30% of the application rate – or to be switched off altogether. This suits a combined approach of weed-specific on-off spraying and variable rate blanket
Weed species identification An alternative optical weed location system developed by US company Blue River Technol- ogy, now a John Deere company, was inspired by advances in facial recognition. Ben Chost- ner of Blue River explains: “We saw an oppor- tunity to take cameras, computers and artificial intelligence to allow ag machines to see every plant in a field and give farmers the ultimate flexible tool to spray very precisely, whether it be herbicide only to the weeds or fertiliser or fungicide directly on each crop plant.” The system employs deep learning algorithms to enable recognition of not only the presence but also the identity of different weeds within crops. It does not rely on spacing or colour to identify them. Instead it recognises differences between plant shapes and structures. A sec- ond set of cameras automatically checks the machine’s work as it operates. Pigweed (Ama- ranthus species) is among the first targets. This is a summer annual resistant to most common herbicides that growers aim to control in cot- ton and other row crops. “The first time our system saw a pigweed it didn’t know what kind of plant it was. But we taught it by show- ing it tens of thousands of images of pigweed – and now it’s an expert,” says Ben Chostner. “Spraying apart, there are opportunities to in- form growers about how many weeds the sys- tem has seen and even what kind of weeds ex- ist in the field, so they can tailor their herbicide programme towards those weeds.”
Tillett & Hague video image analysis locates weeds for a precisely targeted shot of herbicide on the Garford Robocrop Spot Sprayer.
16 ▶ FUTURE FARMING | 24 May 2019
Deadly effect - trials with the Garford Robocrop Spot Sprayer saw her- bicide use slashed by up to 90% with acceptable levels of crop damage.
PHOTO: GARFORD
PHOTO: KUHN
PHOTO: GARFORD
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