PHOTO: RONALD HISSINK


PHOTO: ODD.BOT


PHOTO: JOHN DEERE PHOTO: INTERNATIONAL GREEN WEEK


EDITOR’S PICKS ▶▶▶


Space tech to reduce ammonia emissions


EUROPE Due to intensified production with increasing reliance on chemical fertilisers, more ammo- nia is being released. A team of UK scientists are applying technology developed for space research to help tackle this amount, and try to make farming more efficient. The research team from RAL Space facility and environ- mental consultancy firm ADAS is working to create a reliable way of monitoring and ana- lysing the emissions, so that mitigation proce- dures can then be introduced. This will not only help the environment, it will also sup- port farmers by lowering production costs by reducing expensive fertiliser use. The CAMAG (Continuous Ammonia Monitoring for Agri- culture) instrument concept uses a gas sens- ing method that was originally developed for radio astronomy research and satellite-based Earth observation to detect the microwave signals given off by the ammonia. Atmos- pheric ammonia pollution is of concern – when it combines with other pollutants in the atmosphere it can form dangerous particles which, when inhaled, may pose a threat to human health.


Odd.Bot Weed Whacker


EUROPE The ESMERA project (European Small and Me- dium Enterprise Robotics Applications) trig- gered Martijn Lukaart and Alex Brussee to initi- ate Odd.Bot. Esmera offers funding to SME


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companies to develop robotic solutions for ap- plications that cannot be served by existing ro- botics solutions. Just two months later Odd. Bot showed its first early prototype, designed to eliminate weeds in row crops like carrots, cabbage and leek. The Weed Whacker is a three wheeled robot – front wheels 1.0 m apart, the back wheel in between. This tripod configuration offers stability, efficiency for the robotic delta arm to move around, and allows quick turns on headlands. It navigates using advanced GPS and video. In future the robot eliminates the weeds in the row, between the row crop plants, by image recognition and AI / machine learning technology. A retractable “blender” mills weeds down to their roots. First real trials are planned for early 2019. In May the first prototypes should be in the fields of interested farmers.


uptake over time. Non-uniform uptake rates and delays in plant growth can also be identi- fied, and the farmer is able to see how much nitrogen is still available to the crop at any time, or if the plants aren’t getting enough. This helps avoid excess fertiliser being applied. At harvest, the HarvestLab 3000 sensor meas- ures the nitrogen content in the crop for the season’s N balance and the total of nitrogen applied and removed is summarised ready for regulatory use.


Taranis launches platform in Brazil


Airbus and John Deere observe nitrogen


NORTH AMERICA / EUROPE Satellite imagery provider Airbus Defence and Space and John Deere have teamed up to continuously observe nitrogen uptake by the crop in each part of the field during the grow- ing season. The Live NBalance tool allows farmers to enter the available nitrogen con- tent at the start of the growing season. The ni- trogen and NH4-N content of organic fertil- isers can be measured precisely by the John Deere HarvestLab 3000 NIR system on a slurry tanker. During the growing season, satellite images provide details of the total nitrogen


▶ FUTURE FARMING | 22 February 2019


SOUTH AMERICA Technology could be one of the main allies of the Brazilian rural producer. The Israeli start- up Taranis has an intelligent agricultural man- agement platform that assists in the early identification of major diseases and crop pests. Its next launch in Brazil will incorporate its latest proprietary technology, which deliv- ers ultra-high resolution (0.5 mm / pixel) sub-millimetre images, high resolution satel- lite imagery, weather forecasting, field moni- toring and models that already make up the solution in precision agriculture. This innova- tion consists of the coupling of a lightweight camera into aircraft for aerial application or drones, capable of automatically identifying and quantifying, within a few hours, damage caused by diseases, pests, weeds and nutri- tional deficiencies in large-scale regions that are difficult to access for satellite or face-to- face monitoring. The Israeli start-up offers the first scalable and predictive analytic solution to predict crop threats and prevent them in any climate zone.


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