Using drones to detect coffee rust
A team of UK scientists are researching how to apply drone technology to prevent the spread of the coffee rust fungus and has begun testing in Thailand.
“Coffee rust can be utterly devastating to farmers who rely on the income for their livelihoods,” said project lead Dr Oliver Windram, of Imperial College London. “The benefit of using drones is that they are non-invasive and do not damage the product, but also they are able to get a much more comprehensive view from the air than any farmer can from the ground, so we hope the drones will be able to spot the disease early enough before it wipes out the crop entirely.”
The research project has been funded by the STFC Food Network+, which brings together researchers from STFC and different disciplines in the agri-food sector with the aim of solving some of the world’s greatest food sustainability challenges.
Dr Windram has been working with Professor Katherine Denby, a plant scientist from the University of York, and astrophysicist Dr Anthony Brown, of Durham University, to adapt a technique commonly used in astronomy called multispectral imaging to spot the coffee rust.
Multispectral imaging is used to collect image data at different frequencies in the electromagnetic spectrum, including frequencies beyond visible sight such as infrared.
In the first phase of the project, the team began surveying coffee fields in the Chaing Rai province of Thailand and collecting image data of various crops. This data will be used to train machine learning algorithms, with the aim of having an instrument able to recognise and map coffee plants, as the coffee plants are often surrounded by other different crops.
Dr Windram said: “Having located coffee in the field we would then like to track the spread of coffee leaf rust in coffee plants and as part of this investigate how different intercropping plant community structures influence the spread of this pathogen.
“In terms of milestones we have shown that we can use multi-spectral sensing to differentiate between coffee plants infected with rust and those that are not. We can also distinguish between different types of coffee cultivars using this technology. We have been working in the Chaing Rai coffee-growing region, but if this technology is successful it could potentially be rolled out anywhere the plant is grown.”
The project has now received additional funding from the STFC Food Network+ and will be looking to develop a custom built multi-spectrum camera that will be optimised for differentiating coffee cultivars and coffee leaf rust infections. This will allow Dr Windram’s team to gather more data and make the method more robust, before it can be deployed in other countries.
He added: “If this all goes to plan I can see real impact being made on the ground on coffee farms within the next five years.”