Use of a real-time decision support system to give accurate timings for fungicide applications

Abstract

© 2020 The Author(s). This an open access work distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Environmental conditions such as temperature and relative humidity (RH) affect strawberry powdery mildew (Podosphaera aphanis) development and disease severity. To control P. aphanis growers apply fungicides every 7-14 days (insurance spraying). A rule-based prediction system was developed which records the accumulated number of hours (up to 144) of disease conducive conditions (temperature 15.5-30°C, RH>60%), both parameters must be met for the number of hours to accumulate for the development of the pathogen. It identifies high risk periods when sporulation may occur thus allowing growers to spray at the optimal time to prevent primary infection. A new web-based system designed to be more user-friendly was used at farm sites in England and Scotland in 2018. This work aims to give commercially satisfactory disease control of strawberry powdery mildew with fewer fungicide sprays. The growers checked daily to determine whether a fungicide spray would be required; when applied, the growers reset the system to zero, the hours of disease conducive conditions again start accumulating. This was compared to an area of the farm that used the grower’s normal fungicide spray programme. From leaf samples collected, no presence of disease was found throughout the season showing satisfactory control of P. aphanis. The grower in England saved four sprays, compared to their normal spray programme. A cost-benefit analysis based on fungicides used and labour costs, showed that the grower saved £216 per hectare. The grower in Scotland saved three fungicide sprays compared to their grower group’s suggested spray programme thus saving £275 per hectare. The use of the prediction system enables the grower to spray with precision timing, to maximise fungicide effectivity on disease control, whilst making cost savings. The system can be used as a decision support system giving confidence to only spray when necessary instead of insurance spraying.Non peer reviewe

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