BeetControl
In-app purchases
100+
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USK: All ages
info
About this app
Determine sugar beet diseases with a smartphone and predict disease development! BeetControl replace the leaf plucking method. BeetControl makes this possible!
What is BeetControl?
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 diseas for the next 14 days will be available. 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. Alert messages will be sent.
What you have to do?
100 leaves should be taken from the field. Pictures from these leaves should be taken frontally and a whole leaf should fit a picture.
What happens then?
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. In addition to infection frequency, severity of the sugar beet diesease is also estimated. 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.
This result is taken as a guideline for the prediction of the next 14 days and estimation for disease development the upcoming days. 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.
Result
The result is an assessment of the incidence and severity of infection and a prediction of disease development in the selected time point.
Based on a threshold model, which is applied for the respective country, the infection frequency (incidence) is determined in a specific time point. The farmer receives an alert once the threshold has exceeded or not. The threshold model is country-specific and tackles different time points.
Alert Messages
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.
This app monitors its location in the background at runtime. This is needed to determine the geodistribution of the sample during an investigation. For this reason, the app requires permission to always use the location service. You will receive a notification when this functionality is active.
What is BeetControl?
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 diseas for the next 14 days will be available. 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. Alert messages will be sent.
What you have to do?
100 leaves should be taken from the field. Pictures from these leaves should be taken frontally and a whole leaf should fit a picture.
What happens then?
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. In addition to infection frequency, severity of the sugar beet diesease is also estimated. 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.
This result is taken as a guideline for the prediction of the next 14 days and estimation for disease development the upcoming days. 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.
Result
The result is an assessment of the incidence and severity of infection and a prediction of disease development in the selected time point.
Based on a threshold model, which is applied for the respective country, the infection frequency (incidence) is determined in a specific time point. The farmer receives an alert once the threshold has exceeded or not. The threshold model is country-specific and tackles different time points.
Alert Messages
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.
This app monitors its location in the background at runtime. This is needed to determine the geodistribution of the sample during an investigation. For this reason, the app requires permission to always use the location service. You will receive a notification when this functionality is active.
Updated on
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Data is encrypted in transit
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What's new
Some Bugs fixed.