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Funded Project |
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Funding Program:
Regional IPM Competitive Grants - Northeastern |
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Project Title:
Area-wide Decision Support System for Potato Late Blight (Phytophthora infestans) |
Project Directors (PDs):
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Lead State: NY Lead Organization: Cornell University |
| Research Funding: $48,012 |
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Start Date: Sep-01-1998 End Date: Sep-30-2000 |
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Site/Commodity: potatoes |
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Area of Emphasis: modeling, forecasting |
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Summary:
Potato production in the northeast United States has been compromised by late blight, a disease caused by the oomycete Phytophthora infestans. This is the same disease responsible for the Irish Potato Famine during the mid-nineteenth century (3,12). The disease is devastating and total crop loss is not unusual if proper control measures are not taken. Recently, late blight epidemics in the United States and Canada have become worse as a result of migrations of more aggressive strains of P. infestans into and throughout North America (21). The immigrant (=new) strains of the pathogen are more aggressive than the ones previously found (8,35,37) and are usually resistant to metalaxyl (26), the most effective systemic fungicide for the control of late blight.
Growers are aware of the explosive nature of the disease and to minimize the risk of late blight infection they rely on frequent fungicide applications, usually on a weekly basis, but depending on the weather and proximity of diseased fields, even two or three times a week. This strategy not only results in higher production costs but also may bring detrimental consequences to the environment. These intensive fungicide application schedules could be modified if reliable risk assessment techniques were available such that the user could be warned with probabilistic estimates of risks. Additionally, since there might be situations in which more than one course of action could be taken, it would be helpful to simulate the outcomes of alternative scenarios related to both management strategies and environmental conditions. Our long range goal is to develop more sustainable (based on economic and environmental concerns) management strategies for late blight. The objective of the present proposal is to develop a computer-based decision support system (DSS) for the management of potato late blight caused by P. infestans on an area-wide basis. The DSS will be based on a complex computer simulation model that integrates the three components of the plant disease triangle, the environment (weather variables as well as fungicide), the pathogen (population present and probability of influx and establishment), and the host. The DSS will be used as a tool for risk analysis in which the outcome of a management strategy can be analyzed under different scenarios to assist in decision-making. The unique aspect of the approach proposed here is that the risk of late blight will be probabilistically estimated as a function of inoculum availability for disease development, environmental conditions (past, current and future weather, fungicide applications, redistribution and weathering), and host resistance all integrated via the simulation model. Objectives: Our overall objective is to develop a decision support system (DSS) for area wide management of potato late blight, caused by Phytophthora infestans, in the NE-USA. Area wide is defined as a region of radius up to 10km. This computer-based DSS will be based on a complex disease simulation model and will integrate management of potato late blight by accounting for endogenous inoculum, exogenous or incoming inoculum, host resistance level, effect of fungicide application, and past and future weather. Because it can estimate outcomes of different courses of action, it will be possible to associate risks with different management actions. This system constitutes a major part of our ultimate goal of area wide management of potato late blight. To achieve our overall goal several sub-objectives need to be accomplished. The two sub-objectives of the current proposal are: Development of the DSS. The development phase consists of four stages: i. adjustment of the simulation model to the epidemics caused by new immigrant strains of P. infestans ; ii. integration of the inoculum transport model with the disease development model; iii. incorporation into the existing simulation model of an algorithm to use weather forecast information; and iv. development of an interface to predict probabilities associated with specific courses of action at any point in the season. Validation. We will initiate validation of different parts of the DSS. These include: i. the disease model (re-parameterization to new clonal lineages); ii. initial validation of the transport model; and iii. evaluation of recommendations derived from the estimates of future risks. Outcomes and Impacts Summary from 2001 IPM Center report William Fry is working to develop a computer-based decision support system (DSS) for the management of late blight caused by P. infestans. The DSS would warn growers about blight risk in their area based on weather factors, disease characteristics, and the susceptibility of the potato variety. Potato and tomato farmers throughout the Northeast will be able to use this system to identify the most appropriate strategy for controlling late blight in their fields. The DSS may allow some producers to eliminate as many as seven sprays per season, which will lower farming costs and reduce pesticide use. It should also provide significant peace of mind to farmers, who have felt extremely vulnerable to potential late-blight damage and will now be better able to understand the real risks in their area. Many disease-forecasting models rely primarily on temperature and wetness as weather-related indicators of conditions that are conducive to outbreaks. Fry's work has revealed that another factor -- solar radiation -- can also have an impact on late blight. The spores survive only a short time when exposed to direct sunlight but live much longer when radiation is filtered through a heavy cloud cover. Thus, cloudy conditions can allow the disease to spread further when spores are transported from field to field on the wind. The addition of solar radiation data will improve the accuracy of the lateblight forecasting model used in the DSS. The system should help growers improve their strategies for timing sprays and minimize unnecessary fungicide use. A related project was funded in 1996. |
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