+ = A decision support system for late blight of tomato. Ian Small, L. Joseph, G. Danies, S. McKay, K. Myers and W. Fry

Transcription

1 A decision support system for late blight of tomato + = Ian Small, L. Joseph, G. Danies, S. McKay, K. Myers and W. Fry 26 th Annual Tomato Disease Workshop (TDW), Ithaca, October th, 2011

2 Presentation outline Late blight crop protection strategy: decisions, decisions Decision Support System (DSS) for late blight Preliminary field evaluation Work in progress Summary 2

3 Considerations for late blight crop protection strategy Influence of prevailing weather? Pathogen characteristics? Aggressiveness Host specificity Mefenoxam resistance Cultivar resistance? Lineage specificity Pesticide use? Efficacy Economic efficiency Environmental impact Late blight strategy 3

4 Introduction Decision support system (DSS) - software dedicated to the calculation of disease predictions that support decision making activities Cornell DSS for late blight Web-based Real-time (in season) use Tool for disease management, research and extension 4

5 Decision Support System components Location-specific weather data Disease forecasting tools Late blight disease simulator Alert system 5

6 6 Decision Support System screenshot

7 Weather data Observed and forecast data 7

8 Screenshot: Input page for disease forecasters Variety Defiant PHR F1 Matt's Wild Cherry Mountain magic F1 Plum regal F1 Aunt Ginny's Purple Aunt Ruby's German Green Black Krim Black Plum Brandywine Prudens Purple Red Currant Yellow Currant Yellow Pear BHN 589 BHN 961 Big Beef Celebrity Mountain Fresh Plus F1 Mountain Supreme West VA 63 Glamour Gold Nugget Jetstar F1 Market Pride New girl F1 New Yorker Pik Rite Pilgrim Primo red F1 Scarlet red Sunbrite VFF Sunrise Supersonic F1 Ultra Sweet Susceptibility to LB Resistant (Ph2 & Ph3) Resistant Resistant (Ph2 & Ph3) Resistant (Ph3) 8

9 Disease forecast systems Blitecast Simcast 9

10 Preliminary field evaluation (potatoes) Three treatments: DSS scheduled fungicide applications Weekly fungicide applications Unsprayed control chlorothalonil (Bravo WS) Two cultivars: Katadhin (moderately susceptible) Kennebec (moderately resistant) Trial design: Randomised complete block design (four blocks) 10

11 Evaluation of fungicide scheduling methods for the prevention of late blight A P B C C C C Standard grower practice (seven-day interval) 8 applications DSS schedule Katahdin (moderately susceptible) 6 applications 11 DSS schedule Kennebec (moderately resistant cultivar) 5 applications

12 Late blight simulator: LATEBLIGHT (LB2004 version) Core of DSS is a mechanistic model of late blight disease Uses of LATEBLIGHT simulator Evaluation of disease management scenarios Host resistance Pathogen characteristics Education 12 Andrade-Piedra, et al. 2005, Phytopathology 95:

13 13 Screenshot: Simulator

14 Late blight simulator: management scenarios cultivar cultivar 14

15 Late blight simulator: management scenarios cultivar cultivar Mod. resistant cultivar Mod. resistant cultivar 15

16 16 Late blight simulator: Host characteristics

17 17 Late blight simulator: Host characteristics

18 18 Late blight simulator: Pathogen characteristics

19 Future work: Expand cultivar resistance database 19 Variety Susceptibility to LB Defiant PHR F1 Resistant (Ph2 & Ph3) Matt's Wild Cherry Resistant Mountain magic F1 Resistant (Ph2 & Ph3) Plum regal F1 Resistant (Ph3) Aunt Ginny's Purple Aunt Ruby's German Green Black Krim Black Plum Brandywine Prudens Purple Red Currant Yellow Currant Yellow Pear BHN 589 BHN 961 Big Beef Celebrity Mountain Fresh Plus F1 Mountain Supreme West VA 63 Glamour Gold Nugget Jetstar F1 Market Pride New girl F1 New Yorker Pik Rite Pilgrim Primo red F1 Scarlet red Sunbrite VFF Sunrise Supersonic F1 Ultra Sweet

20 Future work: Incorporate pathogen lineage information Pathogen lineage crop Sensitivity to mefenoxam Unknown (default) Potato Tomato? US-1 Potato Tomato Sensitive US-2 Potato Tomato? US-3 Potato Tomato? US-4 Potato Tomato? US-5 Potato Tomato Sensitive US-6 Potato Tomato Resistant US-7 Potato Tomato Resistant US-8 Potato Intermediate/Resistant US-9 Potato Tomato Resistant US-10 Potato Tomato Sensitive US-11 Potato Tomato Resistant US-12 Potato Tomato Resistant US-13 Potato Tomato Resistant US-14 Potato Tomato Resistant US-15 Potato Tomato Resistant US-16 Potato Tomato Resistant US-17 Tomato Resistant US-18 Potato Tomato Sensitive (Intermediate) US-19 Potato Tomato Sensitive (Intermediate) US-20 Potato Tomato Intermediate/Resistant US-21 Potato Tomato Sensitive//Intermediate/Resistant US-22 Potato Tomato Sensitive (Intermediate) US-23 Potato Tomato Sensitive (Intermediate) US-24 Potato Sensitive (Intermediate) 20 Photo courtesy K. Myers

21 21 Development of an aerial-dispersal risk component

22 Development of a dispersal-risk algorithm Stages of a dispersal event Sporulation Dispersal / survival Germination Temp ( C) RH (%) 0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 24:00 Time of day 22

23 Late Blight Decision Support System Blight alert Sporulation x dispersal x survival x wind risk x germination = Risk index RH = 23

24 24 Application of algorithm preliminary field evaluation

25 Enhancing late blight management using the DSS Alert (US-22) Fungicide selection and scheduling Pathogen characteristics: crops Mefenoxam sensitivity Location-specific weather Maximize benefit from resistant cultivars Minimize environmental impact Infection risk Inoculum? Tomato crop Cultivar resistance Fungicide selection & scheduling Simcast + blitecast Late blight simulator Alert system

26 Acknowledgments Homer C. Thompson Vegetable Research Farm staff This research was supported by: US Department of Agriculture s National Institute of Food and Agriculture program on global food security grant Department of Plant Pathology and Plant-Microbe Biology

27 A decision support system for late blight of tomato 42 Ian Small L. Joseph, G. Danies, S. McKay, K. Myers and W. Fry