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Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application
Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application
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Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application
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Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application
Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application

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Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application
Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application
Journal Article

Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application

2018
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Overview
Late blight is one of the most important potato diseases. To minimize yield losses, various protective measures are used including fungicide application. Active use of fungicides results in a contamination of the environment. Therefore, crop protection strategies optimizing the number of treatments are of great interest. Using information about late blight development in an experimental potato field recorded over 30 seasons, a simulator to forecast yield losses caused by the disease was developed based on the number of 5-d periods favorable for reinfection of plants during a vegetation season. The simulator was successfully verified using independent data on the disease development from nine unprotected potato fields in the Netherlands and Germany. The average difference between the calculated and real yield losses did not exceed 5%. Using the simulator and weather data for a period of 2007–2017, yield losses were calculated for several areas of the Bryansk, Tambov, and Orenburg Regions of Russia. The results revealed differences in disease development between these regions and may be used to develop recommendations for a frequency of fungicide applications according to the regional risk of epidemics, leading to a significant reduction in fungicide use.