A new early warning device for Septoria, yellow rust and brown rust that gives farmers a three week window for deciding whether to spray or not is one of the demonstrations in the Technology Exhibition new for REAP this year.
Bayer CropScience will be exhibiting its automated spore trap. It can detect disease at the point of infection, up to three weeks before the symptoms are seen. This early notice will enable farmers to optimise their disease control programmes, increasing yields and profitability. Better targeting of fungicides may also help to reduce the risk of resistance.
“We have seen that even a big spike in spores only translates into disease if the conditions are favourable for infection. Also there is a latent period between detection of spores and the observation of visible symptoms,” says Will Charlton, Fungicide Product Manager at Bayer CropScience.
“This new information means that farmers will know when their crops have been infected up to three weeks before they can see the disease, allowing much more time to tackle the pathogen. “If however, the weather conditions were unsuitable for infection then they can do a risk assessment and may decide not to spray for that pathogen at all.”
The pathogen detection device is fully automated. Air is sucked through the device bringing fungal spores, which are trapped and identified using LAMP (loop mediated isothermal amplification) DNA amplification. This allows the farmer to see the number and type of spores; at present it identifies Septoria, yellow rust and brown rust in wheat.
Other demonstrations at REAP include:
A “lab on a smartphone” – PA Consulting
This year the wheat harvest had one of the highest protein content on record and some of that is the result of strategic spraying of nitrogen fertiliser at key growth stages. Too much and the expensive fertiliser is wasted, at the wrong time and the benefit is missed. To assess the levels of nitrogen the plant is able to access from the soil, it is useful to make regular samples of the plant’s leaves and roots, but this is time-consuming and the samples need to be processed in a lab. PA Consulting has developed a ‘lab on a smartphone’, which allows the analysis to be done in the field on a mobile device, fast access to results allows decisions to be made about spraying, allowing farmers to optimise the timing and volume of the application.
At REAP, PA Consulting’s innovation experts, scientists and engineers will be on hand for free 30 minute consultations. They can bring their experience of answering these challenges from around the world, and they hope to start exploring what you could individually benefit from on a case-by-case basis. Provide them with a brief summary of what you’d like to talk about, they’ll book you a time and make sure they have the right people there to talk to you. To book a slot for your free consultation, please send a short headline summary for discussion to firstname.lastname@example.org.
New Thorvald robot – University of Lincoln
Telling the difference between a crop and a weed is not a trivial problem, however machine vision technology being developed by University of Lincoln is able to do this. The robot is trained to identify the emerging crop at key stages allowing weeds to removed either mechanically or other physical measure instead of through the use of chemicals. The new Thorvald robot has also been designed to carry soil sensors. Recent research by the AHDB Cereals has shown that soils can vary every few metres so accurate soil mapping can help to determine more precision application of water or fertiliser, reducing waste.
Taking to the air – AgriVue
The health of a crop can be determined by rate of growth and the colour of the leaf canopy. These indicators can be monitored from the air allowing key information to be gained about stress on the crop – for example areas of soil compaction, poor drainage or competition from blackgrass. AgriVue will be demonstrating how drones equipped with a range of sensors can provide farmers and their advisors with a ‘bird’s-eye’ view of the crop.