beetcontrol-Enterprise for Pc

1. By using artificial intelligence and pictures from 100 leaves that are taken at a determine time point, sugar beet diseases especially Cercospora among others, will be identified and a forecast for disease development of this specific sugar beet diseases for the next 14 days will be available.

2. BeetControl replace the leaf plucking method considering the respective threshold of the sugar beet disease for your specific country at a current valid time point.

3. Determine sugar beet diseases with a smartphone and predict disease development! BeetControl replace the leaf plucking method.

4. These leaves are then evaluated individually, and infestation of the sugar beet disease will be determined based on how many leaves are infected with Cercospora – provided information will be given in percent.

5. Based on a threshold model, which is applied for the respective country, the infection frequency (incidence) is determined in a specific time point.

6. The result is an assessment of the incidence and severity of infection and a prediction of disease development in the selected time point.

7. This is possible for BeetControl, because it takes into consideration weather date for the specific site, information on the resistance level for sugarbeet disease of a given variety, and a classification on how high the risk for this disease is in this area.

8. This result is taken as a guideline for the prediction of the next 14 days and estimation for disease development the upcoming days.

9. Alert messages will be sent, if a farmer in the vicinity has exceeded the threshold and/or if the forecast of a farmer in the vicinity indicates that the threshold was exceed.

10. Again, each individual leaf should be evaluated with score classes ranging from 1 to 9, then the mean over all 100 leaves will be given as a result.

11. In addition to infection frequency, severity of the sugar beet diesease is also estimated.

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