In the spirit of Agri 3.0, Matogen Applied Insights (MAI) created a sophisticated weather and plant disease risk alert system, using data and technology to mitigate the potentially dire repercussions of crop failure
Weather-related crop disease
Throughout the centuries, crop diseases often obliterated entire harvests, the Irish Potato Famine of the 1840s being a famous example of Potato Late Blight which led to mass starvation and emigration. The disease in question, Potato Blight (Phytophthora infestans), is a fungal infection caused by spores transported by wind and develops on susceptible plants when weather conditions are favourable, i.e. warm and humid.
To this day, crop losses due to Potato Blight amount to billions of US dollars worldwide, despite the scientific advances in chemical crop protection. This could be attributed to ever-increasing temperature and humidity levels effectively expanding the areas at risk, as well the existence of a wider variety of strains of fungal infections — most likely due to mutation.
Smith and Hutton Periods
Agricultural scientists have defined a formal description of the weather conditions conducive to Potato Blight. Initially, a “Smith Period” referred to a 48 hour period during which the minimum temperature measures 10°C or greater, in addition to the relative humidity exceeding 90% for at least 11 hours during the first 24 hour period, and then again for at least 11 hours during the final 24 hour period. A more recent, and simpler, definition is the “Hutton Period”, which denotes two consecutive days with minimum air temperatures of 10°C and relative humidity of more than 90% for at least 6 hours.
Plant disease risk prediction
Increasingly, using agricultural data to predict plant disease has become an essential tool in crop management. This type of forecasting is necessary to justify each instance of fungicide application and optimise the timing, targeting, and dosage. Several factors influence the risk for plant disease, including the crop flowering stage, petal or airborne spore inoculum levels and weather conditions. A Risk Score is calculated based on these variables.
Weather risk alert system
MAI was contracted to automate and improve the client’s system. Our automated system applies cloud-based algorithms to weather data to calculate indices for disease risk for several diseases. When specified risk thresholds are reached, email and text messages are sent out automatically to users to alert them of heightened disease risk. The system also provides a high-resolution risk map and various relevant weather metrics. Crucially, the system also includes recommendations relating to risk mitigation, for example, which protection products would be required and when spraying conditions would be ideal.
In addition, MAI provides service support to that the risk alert system functions optimally. The risk alert data generated by the system is used to analyse trends in crop risks so that the models can be improved. User behaviour is also tracked for product improvement and business intelligence purposes. The tailor-made product can easily be adapted to include a greater variety of crops and diseases.and dosage. Several factors influence the risk for plant disease, including the crop flowering stage, petal or airborne spore inoculum levels and weather conditions. A Risk Score is calculated based on these variables.