The science of real-time disease detection has arrived and it could be helping growers to manage key yield-robbing diseases, such as sclerotinia, in just five years.
The technology has been developed to detect diseases, to allow growers to accurately time their applications and show due diligence on the necessity to spray, says Gary Jobling, Syngenta’s oilseed rape product manager. He sees automated data gathering as more accurate for risk assessment than current methods based on field monitoring.
At the forefront of this advance is SYield (Sensors for protecting Yield – pronounced shield), a collaborative project between industry and public sector organisations with sponsorship from the government’s Technology Strategy Board. Initiated in 2010, it has already yielded a prototype sensor and risk prediction model.
SYield’s first application will be in warning growers of the risk of sclerotinia in oilseed rape. In future, it may be calibrated to detect any disease with an airborne phase in any crop, suggests Mr Jobling.
“It would be useful to have a sensor system in place for a range of diseases throughout the season, particularly where preventative use of fungicides is the only option. With further research and development, the SYield system could be adapted for other diseases such as rusts and fusarium.”
The prototype data recording box with a network of sensors and an automated spore sampler has been developed for sclerotinia because it is such a damaging disease. Furthermore, current detection and prediction methods are time consuming and unreliable, and there are no fungicides with curative activity against sclerotinia. That means growers must spray protectants or face potential yield losses of up to 50%, he says.
“Rainfall and relative humidity around flowering and the number of airborne spores within the crop are broadly what determine the sclerotinia risk. No one can be out there all the time measuring conditions conducive to infection – an automated unit can save a lot of legwork.”
But how reliable is the system and will it be cost-effective?
Syngenta’s Shradha Singh, SYield project leader, explains: “The sensor for sclerotinia works by detecting the presence of an acid produced when spores germinate, using enzyme reactions and electrochemistry. This data, along with in-crop weather and canopy conditions plus local disease history, are integrated into a computerised, real-time disease prediction model.
“Low risk is forecast if the sensor records viable spores, but there is no rain or high relative humidity. High-risk predictions include advice about how and when to treat crops, in time for preventative fungicides. This should allow for precision management and ultimately save money on unnecessary prophylactic sprays.”
Reliability shouldn’t be an issue, with early teething problems now ironed out, says Dr Singh. Farm-scale costings have yet to be established. Ten prototype units are being tested in the field this season. If all goes according to plan, the technology will be ready for market within five years.
“We’ve yet to ascertain how wide an area one sensor could cover. We will develop the product either as a local service or an individual farm kit, depending on need and economics.”
View from the field
Growers now recognise there are benefits from applying a fungicide to oilseed rape that do not relate to sclerotinia control – be it maintaining leaf greenness, growth regulation or controlling pod diseases. The average yield response in the absence of sclerotinia is 0.1t/ha, according to Peter Gladders, ADAS disease expert. However, severe sclerotinia can take 2t/ha off yield.
“If it is wet around mid-flowering, and the sclerotial germination monitoring supported by ADAS petal tests indicates sclerotinia spores are likely to be present, crops can be considered at risk,” says Dr Gladders. The actual level of infection depends on suitable weather for petals to stick to the leaves and for spores to infect the plant.
“The SYield system should rapidly quantify the local risk based on spore numbers and identify high-risk areas that may require a second spray to control sclerotinia. Its inoculum data would add significantly to prediction models, bringing an extra level of comfort to risk assessment.”
Dr Gladders points out there are still many unknowns, notably the range of a sensor system and its positioning in relation to the crop. Sclerotinia is often field specific and it is still difficult to forecast the type of rain that causes petal sticking and the relative humidity required for infection.
However, he acknowledges that it would be another tool in the box. “I see SYield as an early flowering warning system rather than a last-minute test. The emphasis must be on getting results in good time to maximise spray days. If it can identify epidemic years such as 2007 and 2008, we should be able to minimise yield losses in future.”
|ADAS’s stand on biosensing for sclerotinia|
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