Progress 06/15/10 to 06/14/12
Outputs
OUTPUTS: Outputs in each of the five objectives of the proposal were achieved: 1. Expand the DSS to tomatoes: Epidemics of tomato late blight in Florida are being analyzed for the impact of weather on disease development using historical data (unpublished, P.D. Roberts). The relative resistances of many tomato cultivars were identified and incorporated into the DSS. 2. Expand the DSS to include additional fungicides: Fungicides were applied to small plots of potatoes and the efficacy of the fungicides over time and under different environmental conditions was monitored. These data are being used to construct algorithms to enable these fungicides to be included in the DSS system of models. The most effective avenue was to modify the late blight forecast, Simcast. The 2012 version of the DSS has several of the most popular fungicides. 3. Identify a conceptual model for the first tomato late blight spray in Florida: The date of first detection in south Florida has been recorded yearly since 1998 by co-PD Roberts and historical weather data including temperature, rainfall, windspeed, relative humidity, dewpoint, and other parameters for these years will be obtained from the Florida Automated Weather Network (FAWN http://fawn.ifas.ufl.edu/). Additionally, Blitecast is being be evaluated to determine if this disease forecast can be applied usefully to the tomato production system. As result of this analysis it appears that an alert for high risk conditions (see below) seems most appropriate. 4. Develop an "alert" for "high risk conditions". There are three types of "high risk conditions". The first is triggered by observed weather that identifies the first spray of the season (18 severity values in Blitecast). The second will be a prediction of the first spray of the season using weather criteria, but driven by the weather forecast in conjunction with observed weather. The third active alert will be triggered by weather known to favor sporulation, dispersal and infection, so that if a source of the pathogen is in the region, an "inoculation alert" will be posted. 5. Evaluate the expanded DSS: Two types of evaluations have been conducted in each of the agro-ecosystems in research plots -- in south Florida on tomatoes, and in upstate NY on potatoes. Disease suppression and fungicide use are compared to these in untreated plots and to these in plots treated according to standard grower practice. In the first year, use of the DSS on potatoes enabled a savings of 25-33% of fungicide used in a typical grower fungicide schedule. There was equivalent disease suppression in all treatments receiving fungicide. In the second year of evaluation there was a similar reduction in the amount of fungicide used. The second type of evaluation occurs on growers' farms. We compare grower results (disease suppression, amount of fungicide used, and environmental impact of fungicide) using the DSS, with that of their standard practice (or with that of their non-DSS user neighbors). The DSS is theoretically applicable any place in the USA, but it will need to be adjusted to enable the acquisition of historical weather data, and also to obtain weather forecasts. PARTICIPANTS: In Florida, Pam Roberts, R. S. Donahoo, and R. E. Sytsma were the primary participants. This projected provided training to R. S. Donahoo. In New York, William Fry, Laura Joseph, and Ian Small (graduate student) were the main participants. This project provided a training opportunity to Ian Small. Collaborators in New York include Extension Educator Carol McNeil, and grower, Kevin Datthyn. This work has been supported by the NY IPM program and by the Empire State Potato Growers. This work also provided a basis for the successful ($9 million, 5 years) Oomycete AFRI grant titled: "Reducing losses to potato and tomato late blight by monitoring pathogen populations, improved resistant plants, education, and extension" TARGET AUDIENCES: The target audiences for this research are potato and tomato growers, extension educators dealing with potato and tomato growers, field men and agri-business consultants, investigators working with potato and tomato late blight. The goal is to enable a more efficient use of fungicide to suppress late blight. We predict that on average, use of this system will achieve a savings in fungicide use of 10-20%, while maintaining excellent disease suppression -- at least equivalent to current standards. PROJECT MODIFICATIONS: There are no major modifications at this point.
Impacts
An older version of the DSS has been used in evaluation experiments. We used Simcast (one of the late blight disease forecasts in the DSS) to guide fungicide applications in research plots. There were experiments in the summer of 2010 and the summer of 2011. In 2010 the experiment involved Katahdin as the susceptible variety and Kennebec as the moderately resistant variety. Late blight was known to be present about 0.5 miles away. Chlorothalonil was the fungicide. Treatments consisted of i) weekly applications, ii) applications according to the DSS, or iii) no fungicide. At the end of the season there was essentially no late blight in any plot receiving fungicide, but different treatments had received different amounts of fungicide. Plots sprayed weekly had received 8 applications. Katahdin plots sprayed according to the DSS had received 6 applications, and Kennebec plots sprayed according to the DSS had received 5 applications. Late blight was certainly a threat because by the end of the season the untreated Kathahdin plots were severely affected by late blight (60% defoliated), and the untreated Kennebec plots were about 10% defoliated. Use of Simcast in the DSS enabled the savings of three fungicide applications for Kennebec and two fungicide applications for Katahdin. These savings were made possible by taking into account the effect of weather and host resistance. In 2011, the experiment involved Kennebec as the resistant cultivar and Yukon Gold as the susceptible cultivar. The plots were inoculated from an unknown source with a mixture of isolates of P. infestans. Again the DSS permitted effective disease suppression with less fungicide needed on the resistant cultivar than on the susceptible cultivar. The utility of the DSS has been described to diverse audiences. These include: a meeting of extension personnel associated with a large late blight project at their annual meeting in December 2011; meetings in winter and spring 2012, grower "twilight" meetings, and local extension personnel. Some growers are evaluating the system - using diverse components. Their comments are useful to make further improvements. One extension specialist has 10 weather stations that she is monitoring and growers in other states are evaluating the system.
Publications
- Small, I., Joseph, L. E., and Fry, W. E. 2012. A decision support system for the integrated management of potato and tomato late blight. National IPM Conference.
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Progress 06/15/10 to 06/14/11
Outputs
OUTPUTS: The goal of this project is: to enable fungicides to be used more efficiently in late blight management. Late blight is a major constraint in both potato production and in tomato production, so experiments will occur in both agro-ecosystems. The delivery mechanism for information is a web-based interactive Decision Support System (DSS) that provides information to growers in real-time. Outputs in each of the five objectives of the proposal were achieved: 1. Expand the DSS to tomatoes: Epidemics of tomato late blight in Florida are being analyzed for the impact of weather on disease development using historical data (unpublished, P.D. Roberts) and also via experiments to be conducted during the 2009-2010 and 2010-2011 production seasons. 2. Expand the DSS to include additional fungicides: Fungicides are applied to small plots of potatoes and the efficacy of the fungicides over time and under different environmental conditions is being monitored. These data are being used to construct algorithms to enable these fungicides to be included in the DSS system of models. 3. Identify a conceptual model for the first tomato late blight spray in Florida: The date of first detection in south Florida has been recorded yearly since 1998 by co-PD Roberts and historical weather data including temperature, rainfall, windspeed, relative humidity, dewpoint, and other parameters for these years will be obtained from the Florida Automated Weather Network (FAWN http://fawn.ifas.ufl.edu/). Additionally, Blitecast is being be evaluated to determine if this disease forecast can be applied usefully to the tomato production system. 4. Develop an "alert" for "high risk conditions". There are three types of "high risk conditions". The first is triggered by observed weather that identifies the first spray of the season (18 severity values in Blitecast). The second will be a prediction of the first spray of the season using weather criteria, but driven by the weather forecast in conjunction with observed weather. The third active alert will be triggered by weather known to favor sporulation, dispersal and infection, so that if a source of the pathogen is in the region, an "inoculation alert" will be posted. 5. Evaluate the expanded DSS: Two types of evaluations have been conducted in each of the agro-ecosystems in research plots -- in south Florida on tomatoes, and in upstate NY on potatoes. Disease suppression and fungicide use are compared to these in untreated plots and to these in plots treated according to standard grower practice. The second type of evaluation occurs on growers' farms. We compare grower results (disease suppression, amount of fungicide used, and environmental impact of fungicide) using the DSS, with that of their standard practice (or with that of their non-DSS user neighbors). The DSS is theoretically applicable any place in the USA, but it will need to be adjusted to enable the acquisition of historical weather data, and also to obtain weather forecasts. PARTICIPANTS: In addition to the Project directors, the following individuals worked on this project: Laura Joseph, a programmer who implemented many of the improvements of the DSS. Ian Small, visiting scientist who conducted many of the experiments and did most of the analyses. Steve McKay, farm manager at the Vegetable Research Farm near Ithaca NY, and who is one of the early evaluators of the DSS. Giovanna Danies, a graduate student at Cornell who worked on many of the experiments which provided data for improving the DSS. Carol MacNeil, extension educator who introduced the DSS to growers and fieldmen central and western NY. Abby Seaman, IPM professional who aided growers and extension educators understand and use the DSS. Ryan Donahoo, a plant pathologist from the University of Florida is working on the system in Florida. TARGET AUDIENCES: The target audiences for the DSS include extension educators, field men, and growers. The growers are of diverse characteristics: commercial and conventional, organic growers, CSA operators. The DSS has been presented to these persons at a series of workshops, conferences and twilight meetings. PROJECT MODIFICATIONS: Not relevant to this project.
Impacts
Improvements to the DSS were achieved during the first year and have been made available to users at the beginning of the season in 2011. The major impact of the project is to enhance the visibility of IPM in potato and tomato production. The DSS is a great educational tool for growers, fieldmen and extension staff. It highlights the importance of late blight management and epidemiology. The highly specific weather forecasts are important in making decisions about fungicide spraying, and these decisions are now being made much more knowledgeably. We expect that knowledge will begin to replace fungicide as insurance in the management of late blight. Field trials of fungicides were conducted in the first growing season of the project in NY (summer 2010) and FL (winter 2010/2011). In the summer 2011, we are gathering data necessary to include additional fungicides into the DSS. Develop the "first fungicide application" model for Florida tomatoes. These experiments are in process. We are comparing historical weather data with the first report of late blight to determine weather factors most strongly associated with the first late blight occurrence. These experiments and comparisons are in process. We have incorporated "active alerts" into the DSS. We have developed an algorithm that reflects the factors contributing to a successful inoculation and have added the result to the DSS as an "infection alert". This alert takes into account the following crucial variables: a) whether or not late blight has been reported within 50 miles of the user; b) the degree to which weather at the source of the late blight has had weather favorable to sporulation; c) whether or not weather at the source of late blight favors dispersal of sporangia; d) whether or not wind direction will transport sporangia to the user's location; e) survival of sporangia during transit; f) the probability that sporangia will initiate infection at the users location (using weather at that location). This algorithm is currently being evaluated. Growers can opt for this alert and receive text or email messages when such conditions are met. 5. We evaluated the DSS under "stress test" conditions. Two cultivars (susceptible and moderately resistant) and three fungicide treatments (i. normal grower practice of weekly sprays, ii. fungicides applied according to the DSS and iii. no fungicide) were used for a total of six treatments. The stress test occurred within 0.5 mile of a known source of late blight. When no fungicide was used, late blight destroyed 60% of the foliage of the susceptible cultivar and 10% of the foliage of the moderately resistant cultivar. The grower practice resulted in 8 fungicide sprays on both cultivars and there was no late blight in these crops. The DSS resulted in 6 sprays in the susceptible cultivar and 5 sprays in the moderately susceptible cultivar; there was no late blight in any of these crops. Thus, the experiment illustrated the benefits of using the DSS - there was no reduction in disease control, but the system resulted in a savings of fungicide use by 25-40%.
Publications
- Small, Ian, McKay, Steve, Fry, Bill. 2010., Fungicides for the prevention of foliar and tuber blight. Evaluation of the Cornell Decision Support System. http://www.plantpath.cornell.edu/Fry/2010FieldResearchResults.pdf
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