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“A disease forecast system for timing fungicide applications to control strawberry fruit rots” Natalia Peres and Steve Mackenzie, Natalia Peres and Steve.

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Presentation on theme: "“A disease forecast system for timing fungicide applications to control strawberry fruit rots” Natalia Peres and Steve Mackenzie, Natalia Peres and Steve."— Presentation transcript:

1 “A disease forecast system for timing fungicide applications to control strawberry fruit rots” Natalia Peres and Steve Mackenzie, Natalia Peres and Steve Mackenzie, UF – Gulf Coast REC Clyde Fraisse and Willingthon Pavan UF – Agriculture & Eng. Dept.

2 FL strawberry industry overview FL ~ 8,500 ac FL ~ 8,500 ac 2 nd biggest producer in U.S. 2 nd biggest producer in U.S. 15% total strawberry production 15% total strawberry production $300 million industry $300 million industry Plant City – “Winter strawberry Plant City – “Winter strawberry capital of the world” capital of the world” 25 8000 220

3 Strawberry Production Cycle in West Central Florida Peak bloom periods Land prep / planting Peak harvest periods

4 Major Strawberry Fruit Rot Diseases in Florida Botrytis fruit rot or Gray Mold (caused by Botrytis cinerea) Anthracnose fruit rot (caused by Colletotrichum acutatum)

5 Planting 1 st Bloom 1 st Harvest 2 nd Bloom 2 nd Harvest Spray program for control of BFR and AFR in FL Botrytis Protective sprays (captan) Bloom sprays X X X Late season sprays Anthracnose Legard, D.E., MacKenzie, S.J. Mertely, J.C., Chandler, C.K., Peres, N.A. 2005. Development of a reduced use fungicide program for control of Botrytis fruit rot on annual winter strawberry. Plant Dis. 89:1353-1358

6 Disease management currently relies on calendar-based protective applications of fungicides Disease management currently relies on calendar-based protective applications of fungicides Disease management with a forecast system, application of fungicides are made only when necessary (requires a good understanding of the conditions suitable for disease development, i.e., host, pathogen, environment) Disease management with a forecast system, application of fungicides are made only when necessary (requires a good understanding of the conditions suitable for disease development, i.e., host, pathogen, environment) Calendar system vs. Forecast system

7 Disease models published by others to predict the incidence of Botrytis and anthracnose fruit rots were evaluated for their effectiveness to time fungicide applications in replicated field trials during the 3 consecutive strawberry seasons Disease models published by others to predict the incidence of Botrytis and anthracnose fruit rots were evaluated for their effectiveness to time fungicide applications in replicated field trials during the 3 consecutive strawberry seasons Fungicides applied at variable intervals according to models and compared to a standard calendar program and an untreated control Fungicides applied at variable intervals according to models and compared to a standard calendar program and an untreated control Development of a forecast system

8 Botrytis Bulger - Madden model and Broome model Length of most recent wetness period Length of most recent wetness period Average temperature during wetness event Average temperature during wetness event Bulger, M. A., Ellis, M. A. and L. V. Madden. Influence of Temperature and Wetness Duration on Infection of Strawberry Flowers by Botrytis cinerea and Disease Incidence of Fruit Originating from Infected Flowers. Phytopathology 77: 1225- 1230, 1987. Broome, J. C., English, J. T., Marois, J. J., Latorre, B. A. and Aviles, J. C. Development of an Infection Model for Botrytis Bunch Rot of Grapes Based on Wetness Duration and Temperature. Phytopathology 85: 97-102, 1995.

9 Botrytis Xu model Average day time relative humidity (%) Average day time relative humidity (%) (8:00 am to 7:45 pm) Average day time temperature Average day time temperature (8:00 am to 7:45 pm) Average night time temperature Average night time temperature (8:00 pm to 7:45 am) Duration of leaf wetness (hr) previous night Duration of leaf wetness (hr) previous night X. Xu, D.C. Harris, A.M. Berrie. Modeling infection of strawberry flowers by Botrytis cinerea using field data. Phytopathology, 90:13671373, 2000.

10 Botrytis - Treatments evaluated Treatment Fungicide spray 1. Xu model DI=0.5 2. Xu model DI=0.8 3. Broome DI=0.5 4. Broome DI=1.4 5. Bulger-Madden DI=0.5 6. Bulger-Madden DI=0.7 7. Bulger-M Captan DI=0.5; Captevate DI=0.7 Captevate DI=0.7 8. Calendar standard 9. Untreated control If %INF>0.5 captan early, Captevate at bloom If %INF>0.8 captan early, Captevate at bloom If DI>0.5 captan early, Captevate at bloom If DI>1.4 captan early, Captevate at bloom If %INF>0.5 captan early, Captevate at bloom If %INF>0.5 captan, if %INF>0.7 Captevate captan early, Captevate at bloom N/A

11 2006-07 season Disease incidence (%) Treatment # Sprays Sweet Charlie Festival Calendar standard 20 3.9 d 0.4 Xu model DI=0.5 15 4.1 d 1.0 Bulger-M Captan DI=0.5; Captevate DI=0.7 Captevate DI=0.7 12 4.1 d 1.1 Bulger-Madden DI=0.5 9 4.6 cd 1.2 Broome DI=0.5 11 5.1 cd 1.5 Xu model DI=0.8 12 6.2 bcd 1.1 Bulger-Madden DI=0.7 8 7.7 bc 1.6 Broome DI=1.4 5 9.1 ab 3.5 Untreated control 0 12.7 a 3.3

12 2007-08 season Disease incidence (%) Treatment # Sprays Sweet Charlie Festival Xu model DI=0.5 14 0.9 a 0.4 Bulger-Madden DI=0.5 8 1.7 ab 0.4 Calendar standard 16 1.8 ab 0.3 Broome DI=0.5 11 1.9 ab 0.4 Bulger-Madden DI=0.7 4 2.4 bc 0.3 Xu model DI=0.8 12 2.6 bc 0.6 Bulger-M Captan DI=0.5; Captevate DI=0.7 Captevate DI=0.7 10 3.2 bc 0.2 Broome DI=1.4 4 3.8 c 0.6 Untreated control 0 3.9 c 0.8

13 2008-09 season

14 Anthracnose Wilson-Madden infection curves Wilson, L. L., Madden, L. V., and Ellis, M. A. 1990. Influence of temperature and wetness duration on infection of immature and mature strawberry fruit by Colletotrichum acutatum. Phytopathology 80:111-116. Infection curve for mature berries (cv. Midway) 42F 50F 59F 68F 77F 86F

15 Anthracnose - Treatments evaluated Treatment Symptoms required Fungicide spray 1. Calendar captan only captan onlyNo captan weekly 2. Calendar captan or pyraclostrobin captan or pyraclostrobinNo captan weekly early season, pyraclostrobin late season 3. Pre-symptom W-M captan only captan onlyNo If INF > 0.15 - captan 4. Pre-symptom W-M captan or pyraclostrobin captan or pyraclostrobinNo If INF > 0.15 - captan, If INF > 0.5 - pyraclostrobin 5. Post-symptom W-M captan only captan onlyYes If INF > 0.15 - captan 6. Post-symptom W-M captan or pyraclostrobin captan or pyraclostrobinYes If INF > 0.15 - captan, If INF > 0.5 or 1 st INF >0.15 - pyraclostrobin 7. Untreated control N/AN/A

16 2006-07 season Disease incidence (%) Treatment # Sprays (captan; Cabrio) CamarosaFestival Pre-symptom W-M captan or pyraclostrobin captan or pyraclostrobin10(6;4) 2.1 a 0.4 ab Calendar captan or pyraclostrobin captan or pyraclostrobin16(12;4) 3.1 ab 0.4 ab Calendar captan only captan only16(16;0) 4.0 ab 0.1 a Post-symptom W-M captan or pyraclostrobin captan or pyraclostrobin6(4;2) 4.8 ab 1.2 bc Pre-symptom W-M captan only captan only9(9;0) 5.5 bc 0.5 ab Post-symptom W-M captan only captan only5(5;0) 9.4 cd 0.9 bc Untreated control 0 14.3 d 2.0 c

17 2007-08 season # Sprays Disease incidence (%) Treatment (captan; Cabrio) CamarosaFestival Calendar captan or pyraclostrobin captan or pyraclostrobin16(12;4) 15.5 a 5.2 a Pre-symptom W-M captan or pyraclostrobin captan or pyraclostrobin11(9;2) 17.6 ab 6.3 ab Calendar captan only captan only16(16;0) 20.2 abc 5.9 a Post-symptom W-M captan or pyraclostrobin captan or pyraclostrobin8(6;2) 24.7 bc 7.9 ab Pre-symptom W-M captan only captan only11(11;0) 27.6 c 9.8 bc Post-symptom W-M captan only captan only9(9;0) 38.4 d 13.4 c High threshold post-symptoms captan or pyraclostrobin captan or pyraclostrobin1(0;1) 51.9 e 28.4 d Untreated control 0 58.5 e 35 e

18 2008-09 season Disease incidence (%) Treatment # Sprays CamarosaFestival Calendar captan or pyraclostrobin captan or pyraclostrobin 17 0.8 a 0.2 Calendar captan only captan only 17 1.1 a 0.2 Pre-symptom W-M captan or pyraclostrobin captan or pyraclostrobin 5 1.5 a 0.3 Combined anthracnose and Botrytis fruit rot INF 5 1.8 a 0.8 Post-symptom W-M captan or pyraclostrobin captan or pyraclostrobin 5 2.0 a 0.4 Untreated control 0 8.3 b 0.4

19 Treatments selected to develop the disease forecast system Botrytis: Bulger-Madden %INF>0.5 Botrytis: Bulger-Madden %INF>0.5 Anthracnose: Wilson-Madden INF>0.15; INF>0.5 Anthracnose: Wilson-Madden INF>0.15; INF>0.5 (pre-symptom) (pre-symptom) Length of most recent wetness period Length of most recent wetness period Average temperature during wetness event Average temperature during wetness event

20 Development of the disease forecasting tool in AgroClimate http://agroclimate.org/tools/strawberry/

21 AgroClimate.org Peres, N.A., and Fraisse, C.W. Development of a disease forecasting system for strawberries as a tool on AgClimate. (USDA/RMA)

22 Strawberry Disease System

23 Current risk level

24 Disease simulation

25 Weather data

26 Spray recommendation

27

28 Email and SMS alerts

29 2009-10 Grower trials 2 treatments: Grower standard and model- timed applications 2 treatments: Grower standard and model- timed applications 3 farms – 5 to 13 acres 3 farms – 5 to 13 acres Disease incidence – 60 plants per treatment Disease incidence – 60 plants per treatment ~20 growers signed up to receive disease risk alerts ~20 growers signed up to receive disease risk alerts

30 TreatmentCultivar# SpraysBFR (%)AFR (%) Farm 1 ModelFestival421.32.8 GrowerFestival1430.40.7 Farm 2 ModelAlafia610.21.0 GrowerAlafia139.92.4 ModelSanibel612.40.0 GrowerSanibel1313.86.0 Farm 3 ModelTreasure (1)5 42.1 5.7 GrowerTreasure (1)14 41.6 0.5 ModelTreasure (2)5 37.4 14.3 GrowerTreasure (2)14 32.0 0.9 ModelTreasure (3)5 19.2 60.4 GrowerTreasure (3)14 23.2 23.8 2009-10 Grower trials

31 Future plans USDA-NIFA-SCRI project funded to: USDA-NIFA-SCRI project funded to: Validate and expand the forecast system to North Carolina, South Carolina, Ohio and Iowa Validate and expand the forecast system to North Carolina, South Carolina, Ohio and Iowa Evaluate the use of models to estimate leaf wetness duration Evaluate the use of models to estimate leaf wetness duration Determine baseline sensitivities of B. cinerea and C. acutatum and develop a resistance monitoring system Determine baseline sensitivities of B. cinerea and C. acutatum and develop a resistance monitoring system

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