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Early disease detection develops apace

Detecting diseases early to allow better decision making on control was a key focus of research demonstrated at Cereals 2016

 

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New monitoring methods for #blackgrass, #yellowrust, #brownrust, #septoria, #blight

A simple test which can detect the presence of herbicide resistance in black-grass could act as an early warning for farmers to help slow the spread of the grass-weed.


The ‘pregnancy’ test-style prototype detects a protein found in high concentrations in black-grass populations which have evolved resistance to herbicides.


The test takes just 15 minutes to work and a red band appears in a small window on the hand-held device if the protein is present.


The test is sensitive enough to detect the molecule in the early stages of black-grass development. The aim is to help farmers make management decisions early in the crop cycle and prevent costly losses later on.


Funded by the Biotechnology and Biological Sciences Research Council and AHDB, the underpinning science has been developed by scientists at Newcastle University, as part of the Black-Grass Resistance Initiative. This is in partnership with Rothamsted Research, Sheffield and York universities and the Institute of Zoology.


A prototype device demonstrated at Cereals was developed by the Newcastle team, working with Bedfordshire-based diagnostics company Mologic.


Currently, the only way of knowing if black-grass sampled in the field is resistant to herbicides is to send seeds or plants off to the lab for analysis, resulting in delays in making informed decisions about control options.


This autumn, researchers are hoping to work with farmers and agronomists to see how this diagnostic tool could be used in counteracting herbicide resistance using a rapid field-based assay.

 

Smart surveillance


The latest smart surveillance technique for assessing disease risk in cereal crops was on on show at Cereals.


Fera is developing the SMART spore trap for automatic detection of wheat pathogens septoria, yellow rust and brown rust.


The prototype device, developed with funding from Innovate UK, integrates automated spore sampling, in-field pathogen detection and weather monitoring. Results are self-reported to a central hub via the mobile phone network and satellites.


Following the detection of the first presence of disease spores, the device measures spore loads and calculates disease risk, based on local weather and spore load, before communicating this risk to the user.


Ultimately, the system could help provide growers with more flexibility in terms of fungicide spray windows, product choice and rate of application, it is claimed.


Speaking at Cereals, Fera pathologist Dr Judith Turner said the device would be deployed this autumn within the newly-formed Centre for Crop Health and Protection decision support network for further validation and forecast development.


It is hoped a commercial device will be developed for 2017/18.


Further aims are to incorporate detection of other pathogens and extend the spore trap’s use into further crops, said Dr Turner.


The same technology is being used to improve potato blight detection.

 

Potato blight detection

 

More accurate detection of potato blight risk, which could result in better timing of and possibly fewer fungicide applications, is the objective of Innovate UK and AHDB-supported research being carried out on Velcourt farms.


Rothamsted Research plant pathologist Jon West explained how he is developing a prototype auto spore sampler. In the sampler, potato blight spores are broken open and a LAMP assay – a relatively cheap DNA screening technique – is used to detect levels.


He said: “Weather data is used to determine when the right infection conditions are present and alert growers by email or text message.”


Data from last season showed quite a long period when no spores were present, said Dr West.


“When there is low risk, farmers could spray less frequently than they do. This may also allow use of more expensive products when spores are released.”


He estimated the technology could save one or two sprays per season and is likely to cost several thousand pounds.


Detecting septoria, yellow rust and brown rust using drones before the diseases become visible to the human eye, is the objective of a three-year project, involving Velcourt, BASF and Hummingbird.


In its second year, the project involves measuring the amount of disease in plots, mapping the location and intensity of infection in-field and determining whether pre-symptomatic infection can be seen.


It is also looking at identifying and mapping lodging risk early in the season and estimating yield before harvest by measuring ears/sq.metre, ear size and green area index.


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