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Tailoring disease control to risk – CPM – David Howard

Understanding risk based on early cropping decisions, like variety or drilling date, and in-season monitoring of crops are key to using Integrated Crop Management (ICM) successfully ...

Many farmers may already be taking these steps without fully realising it, says Dave Howard, head of ICM at Hutchinsons.

“ICM doesn’t require a drastic change from the norm, in fact many ICM principles have already been taken up over the years due to the positive effect they can have on disease management. It’s simply a more strategic approach when planning which crops and varieties to grow, assessing where risks lie and then adapting management and inputs in response to changing weather patterns and disease levels – or visualizing risk,” he says.

“This can be more complicated than it sounds. Over the past two years growers have juggled with a spectrum of drilling dates and varieties across their farm, which makes assessing which crops are at higher risk more complicated. And that’s without the extremes of weather to consider throughout the season.”

So to make this process much simpler Hutchinsons has developed a Wheat Disease Risk Forecasting model within Omnia. The model automatically calculates which crops are at the highest risk from disease, taking into account all of the factors affecting disease developing in the crop and allowing the user to tailor a fungicide approach accordingly.

“It’s about being better informed to plan a strategy. The job of the model is not to tell us that disease is present, but rather to plan for what disease will be more likely to develop in a particular variety/field etc. This allows the user to temper that risk as much as possible, not eliminate it, by tailoring a planned fungicide approach accordingly.”

The model takes into account the data already entered into Omnia, like variety and drilling date, alongside the climatological data provided by the Omnia Climate module. The output is a visual risk map across the farm, illustrating which fields pose higher risks and where that risk is coming from, he explains.

“Users can allocate specific fields and are presented with a sliding scale to access visual representations of crop growth and certain growth stages. Likely spray days are then predicted and as the weather patterns change, the calculated risk constantly evolves, allowing fungicide programmes to be planned more effectively.”

The risk is recorded though the season to provide a record for justification purposes which is something that is becoming increasingly important, he adds.

The Omnia team are developing a similar model for barley and a lodging risk model for wheat, which are both being trialled this spring at Hutchinsons’ Helix farms.


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