Use this tool to understand sclerotinia infection risk and target control.
Top tip: Click on the page arrows <-> to toggle between page views.
- < 1 of 4 > = Tool home page
- < 2 of 4 > = Look back at how the tool has performed
- < 3 of 4 > = Risk map
- < 4 of 4 > = Spore trap data (five sites)
About the sclerotinia infection risk alerts
Sclerotinia stem rot is usually the main disease to consider during the flowering stages of oilseed rape. Although the infection cycle of Sclerotinia sclerotiorum is complex, a good understanding of the three main risk factors – the presence of sclerotinia inoculum (spores), warm and humid conditions, and crops in flower – will help you target control.
Weather and infection risk
If spores are present, conducive weather is required for infection to occur.
> Based on observed (past 24 hours) and forecast (next 72 hours) weather data, the interactive maps track the period of time that relative humidity (RH) and air temperatures are at or above threshold (80% and 7°C, respectively).
> If these thresholds are exceeded for 23 continuous hours (the time needed in order for sclerotinia to infect the crop), a weather-based infection alert is issued at the corresponding site (red circle). Near misses are also highlighted (amber circles). Where infection risk is low, this is shown (green/white circles).
Click on a circle (any colour) to show an hour-by-hour chart of the sclerotinia infection risk for that site.
Sclerotinia control products are protectants and should be applied prior to infection (before circles turn amber/red).
Forecast forensics (June 2020)
Our weather-based sclerotinia infection risk alerts support decisions. With trends in potential infection risk highlighted, it can focus the all-important monitoring at the field level. Forecasts are never perfect, but our analysis of the 2020 season shows the predictions are relatively good.
This table highlights infection alerts based on forecast and the observed weather data in 2020. There is a high level of consistency between the two sets of data. Occasionally, there are differences and these are more commonly driven by relative humidity, than temperature. Typically, consistency is better when conditions are firmly above or below the weather thresholds. When conditions are at or around threshold, risk alerts are more uncertain.