The fungal diseases, anthracnose (caused by Colletotrichum spp.) and Botrytis grey mould (caused by Botrytis cinerea), are the major fruit diseases in Ontario strawberries. By integrating a disease prediction model into management, growers can use fungicides more effectively to protect their crops through the season. In 2023, the map below is available for growers to use to help assess the risk of disease epidemics from bloom to harvest.
OMAFRA has partnered with Weather Source to provide OnPoint Weather. The locations on the map are based on agricultural production and use all nearby weather data and geography to provide accurate forecasting data. At the end of the season, OnPoint Weather data will be compared to on-farm weather station data to assess predictive accuracy.
The disease model used is based on the Florida Strawberry Advisory System (FLSAS) developed by W. Pavan et al.. This risk modelling tool is used to identify anthracnose fruit rot and Botrytis fruit rot risk based on leaf wetness and temperature data. For our calculations, leaf wetness is predicted based on relative humidity that is adjusted to account for crop canopy. If the adjusted relative humidity is over 90% for the hour, it is considered as 1 hour of leaf wetness. The average temperature is calculated over the leaf wetness period, and this is used in the equations to calculate the infection risk index, from 0-1.
Feedback from users on these maps is needed. Please use this anonymous survey: https://forms.office.com/r/amLrFa9shq
|B: Botrytis Fruit Rot Lesions remain firm and brown while fruit is green. Lesions expand and soften as fruit ripens. A powdery gray mass of spores may cover infected berries.|
|Risk Level||Recommended Management|
|Low <0.5 (Low)||No need for fungicides against Botrytis|
|Moderate ≥ 0.5 to <0.7 |
|Take into account susceptibility. If several factors contribute to greater susceptibility, apply a fungicide if there has been no application for 7 – 14 days.|
|High ≥ 0.7 (High)||If no fungicides have been applied in the last 7-14 days, apply a highly effective fungicide as soon as possible.|
|A: Anthracnose Fruit Rot Circular, tan or light brown spots usually about 3-7 mm in diameter occur on both green and ripe fruit and become sunken and darker. On ripe fruit, lesions may be sunken and filled with pink slimy spore masses.|
|Risk Level||Recommended Management|
|Low <0.15 (Low)||No need for fungicides against anthracnose|
|Moderate ≥ 0.15 and <0.5|
|Take into account the susceptibility. If several factors contribute to greater susceptibility, if no fungicides have been applied in the last 7-10 days, apply a highly effective fungicide as soon as possible.|
|High ≥ 0.5 (High)||If no fungicides have been applied in the last 7-10 days, apply a highly effective fungicide as soon as possible.|
After applying an effective fungicide and during the fungicide interval (7 days), growers do not need to reapply a fungicide until a moderate or high risk is triggered after the 7 days. If over an inch of rain falls during the spray interval, growers should follow the infection risk levels and spray according to the risk.
- This tool is meant for field-grown strawberries (day-neutral and June-bearing varieties). This tool is not applicable for protected culture as leaf wetness will be significantly different.
- Use either the Botrytis infection risk level or the anthracnose infection risk level to management the disease of greatest concern.
- If predicted risk differs between overlapping locations, err on the side of caution and use the higher risk prediction.
- Fungicide applications are suggested when “Infection Risk Levels” are moderate or high and there has been more than 7-14 days since the last application or more than 1” of rain. High risk indicates that weather conditions are highly conducive to infection and highly efficacious fungicides should be used for either disease
- Disease risk is calculated on a 24-hour clock, from midnight to midnight
Disclaimer: These maps are being providing for free as a decision tool and are not making a recommendation. Weather data is provided by the Weather Source. Data used from on-farm weather stations that have leaf wetness sensors within the crop will provide the most accurate weather data.
Background and more information
Disease prediction models are useful tools to help determine the risk of disease outbreaks through the season. Growers can use these models to time fungicide applications when conditions are favourable for disease development, allowing growers to avoid unnecessary applications and reduce costs without compromising fruit yield or quality.
The severity of disease is weather dependent, and anthracnose is favoured by warm, humid weather and splashing rain. Anthracnose management is challenging as there are limited effective fungicides available for growers. With the presence of group 11 fungicide resistance in Ontario, growers should not rely on group 11 fungicides for anthracnose control, leaving growers with fewer effective options. More information for managing anthracnose can be found here:
A strawberry anthracnose fruit rot model was developed in the US and is now used in multiple areas to help time fungicide applications, including the Strawberry Advisory System (http://agroclimate.org/tools/sas/dashboard/disease) and NEWA (https://newa.cornell.edu/).
FLSAS model details for Colletotrichum acutatum (anthracnose fruit rot):
Low risk: < 0.15 Moderate risk: 0.15- 0.50 High risk: > 0.50
FLSAS model details for Botryis cinerea (Botrytis fruit rot):
In a 2016-2017 project OMAFRA validated the use of this model in Ontario. By spraying according to the model fungicide applications were reduced by 7-33%, while disease control was maintained, and yield and berry quality was not affected. A follow-up demonstration trial in 2018 included on-farm use of the model to give growers experience incorporating the model into their decision making.
Pavan, W., Fraisse, C. W., and Peres N. A. 2012. The Strawberry Advisory System: A Web-Based Decision Support Tool for Timing Fungicide Applications in Strawberry. Department of Agricultural and Biological Engineering, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida publication AE450. https://edis.ifas.ufl.edu/pdffiles/AE/AE45000.pdf