Tech on test to detect early signs of Septoria
by Arable Farming
New technology is coming forward which will allow growers to tailor fungicide programmes to variety, drilling date and real-time disease levels. Alice Dyer reports.
Being able to see what levels of hidden disease are lurking in crops has long been a goal for growers and agronomists.
Now a number of companies are stepping up trials to bring technology capable of detecting latent disease to market.
Swift Detect uses fast-turnaround qPCR testing to search for disease DNA in leaves and alert growers and agronomists of the presence of septoria in the latent period before symptoms become visible.
Developed by Microgenetics, a pharmaceutical company which initially created the rapid analysis to detect salmonella in baby food, the test is available for septoria this season and will soon expand into other wheat diseases including rusts and mildew.
Trials over the last three seasons have seen agronomists send in 10 leaf samples per field every 10 days, enabling them to track disease pressure in the field prior to T1 and T2.
Results are sent back in around one working day and presented as a traffic light system based on the amount of disease present.
Once other wheat diseases are included, it will be possible to track four key wheat diseases septoria, mildew, yellow and brown rust using a single leaf sample.
Chris Steele, crop diagnostics product manager at Microgenetics, says: For more resistant varieties agronomists are generally looking at testing just before the T2 spray and before T1 and T2 for the most susceptible varieties.
Taking a sample every 10 days will cover leaf 1 and 2 and the flag leaf.
Although qPCR testing can give growers a good indication of potential disease threat, there is even more precise technology in the pipeline showing promising results, says precision agriculture expert and consultant Keith Norman.
Results from qPCR testing can be variable depending on how the results are interpreted.
It can give you an indication and no more than that if youve got a disease present, he says.
If youre taking samples from a large number of plants, you have to be specific about the leaf layer you are taking from.
If youve got septoria in leaf 3 but not leaf 2 it doesnt mean you can .
It gives you an indication of timings, when to make interventions and which products to use, whether thats protectant or curative. A number of other technologies which remotely detect pre-symptomatic or early disease are also being worked on behind the scenes.
Using drone or satellite imagery, researchers are recognising the changes to spectral signatures that occur when a plant becomes infected with disease.
This is because when the plant becomes under pressure from disease, the reflection pattern of several wavelengths changes.
The next stage of the study will explore wavelengths for specific diseases to differentiate between septoria or yellow rust infection, for example.
Mr Norman says: There is a general knowledge about which wavelengths indicate plant health.
At the moment it will tell you it has a disease but not which disease.
This is still quite useful for an agronomist to see which crops are starting to show signs of disease so they can then prioritise spray schedules. The University of Manchester, NIAB and Rothamsted Research are, alongside other industry partners, working on a number of possibilities, including an in-field sensor which houses a 3D artificial leaf.
As air naturally filters through, spores are caught on the âleaf surface where biochemicals stimulate germination.
As the spores multiply and penetrate the leaf a signal is sent to a grower portal to alert them of the disease.
Other devices are being developed, whereby spore traps use qPCR testing or LAMP assays to detect the presence of disease DNA in the air.
Although the technologies are some way off landing in a field near you, they show great promise, says Mr Norman.
There is potential for these technologies to work together.
You could have a spore sensor looking for the presence of spores and then use remote sensing to detect when the crop actually started becoming infected.
There is a synergy between these technologies.
The implications mean growers will have a lot more decision-making powers as to when to time fungicides instead of a blanket approach based on a growth stage or calendar date.
Taking care of clean varieties
The next phase of Bayers Rapid Disease Detection trials will determine how the level of disease found in the leaf affects different varieties, particularly those with high resistance ratings.
It is hoped the information from the trials will give growers a new layer of information when it comes to making fungicide choices for certain varieties.
Rapid Disease Detection uses a similar method to Swift Detect, where the quantity of septoria DNA on a leaf sample is assessed using qPCR testing for a rapid turnaround result.
Ben Giles, commercial technical manager at Bayer, says: If you are growing a good will be really useful in terms of whether you should go all in or whether you can trim your rates back or use a different product.