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Funded Project

Funding Program: Regional IPM Competitive Grants - Northeastern

Project Title: Validation and Implementation of a Weather-based Spray Advisory Model for White Rust of Spinach

Project Director (PD): Kathryne Everts [1]

Lead State: MD Lead Organization: University of Maryland

Extension Funding: $6,824

Research Funding: $48,085

Start Date: May-01-2004 End Date: Apr-30-2006

No-Cost Extension Date: Apr-30-2007

Pests Involved: fungus, fungi, rusts, white rust

Site/Commodity: spinach

Area of Emphasis: weather, modeling, models, crop rotation

Summary: Spinach (Spinacia oleracea L.) was grown on more than 35,000 acres in the U.S. in 2002. It is an important crop grown for the fresh and processing markets in Maryland and Delaware where acreage has increased in the past ten years. Together Delaware and Maryland constitute the fourth leading spinach producing area in the U.S., with 2700 acres produced in Maryland alone; New Jersey and Virginia also have large acreages. A spinach stakeholders meeting was held in Milford, Delaware on December 13, 2002. Growers, processors, and University of Delaware and University of Maryland Cooperative Extension personnel attended the meeting. White rust (Albugo occidentalis G. W. Wils.) was cited as the most prevalent, and difficult to control, disease. There was near unanimous interest in adaptation of a weather-based fungicide application model for management of spinach white rust. Despite widespread crop rotation and some, limited, use of host resistance, fungicide usage is very high on spinach in order to control white rust. Azoxystrobin, copper, mefenoxam, fosetyl-Al, and acibenzolar-Smethyl are used to control foliar diseases on U.S. acreage. Despite high fungicide usage, losses due to white rust persist due to poor timing of fungicides. In addition, fungicides are applied on a calendar schedule and are not always necessary, especially when the environment does not favor disease development. A fungicide-application model based on the relationship between the environment and white rust on spinach was developed in Oklahoma. Our preliminary trials examining the model have clearly demonstrated that, although the model may result in better fungicide timing, delaying initial applications until disease is observed often results in unacceptable losses due to initial infections. The overall objective of this project is to assist growers in adopting a weather-based fungicide application model for spinach through an improved understanding of i) presence and extent of over-wintering oospore inoculum, ii) identification of the optimum time to initiate fungicide applications, and iii) identification of fungicides or bio-fungicides that can be successfully used with a weather-based fungicide application model. Problem, Justification, and Background Spinach (Spinacia oleracea L.) was grown on more than 35,000 acres in the U.S. in 2002. It is an important crop grown for the fresh and processing markets in Maryland and Delaware where acreage has increased in the past ten years. Together Delaware and Maryland constitute the fourth leading spinach producing area in the U.S., with 2700 acres produced in Maryland alone; New Jersey and Virginia have large acreages, also. A spinach stakeholders meeting was held in Milford, Delaware on December 13, 2002. It was attended by growers, processors, and University of Delaware and University of Maryland Cooperative Extension. White rust (Albugo occidentalis G. W. Wils.) was cited as the most prevalent, and difficult to control, disease. There was near unanimous interest in adaptation of a weather-based fungicide application model for management of spinach white rust. White rust is consistently identified as a priority concern of growers in the mid-Atlantic region. Spinach was identified as a priority crop in Delaware's 1996 IPM needs assessment survey. During that needs assessment, improved foliar disease management and the development of a white rust prediction system were identified as priority research and extension needs. A Pest Management Strategic Plan (PMSP) Workshop for Spinach in Delaware, Maryland, and New Jersey will be held on January 5 and 6, 2004 in Harrington, DE (http://www.pestmanagement.rutgers.edu/NJinPAS/PMSP.htm). Again spinach white rust is expected to be the identified as the most important disease, in terms of economic loss. Crop rotation is used on most of the spinach acreage in the U.S.; however, rotation alone is not adequate to control white rust (NAPIAP, 1994, Garrison, 2003). Host resistance has been successful in minimizing the impact of downy mildew (Brandenberger et. al., 1994, Dainello et al., 1990; Heineman et al., 1990). Recently cultivars that have moderate levels of resistance to white rust, and with fair agronomic characteristics, have been developed (Heineman and Dainello, 1990). A cultivar with moderate resistance to white rust (Vancouver) is now grown on limited acreage in Maryland and Delaware, and other moderately resistant cultivars are currently in University trials. Vancouver has "semi-savoy" leaf type, which limits how much can be used for the processing market. In addition, fungicide applications are necessary on moderately resistant cultivars to limit the incidence of white rust lesions that reduce leaf quality. Despite widespread crop rotation and limited use of host resistance, fungicide usage is very high on spinach in order to control white rust (NAPIAP, 1994). Azoxystrobin, copper, mefenoxam and fosetyl-Al are used to control foliar diseases on U.S. acreage. Acibenzolar-S-methyl is registered for use in some counties in Texas and California and is available through a Special Local Needs label (24c) in New Jersey and Virginia. Despite high fungicide usage, losses due to white rust persist due to poor timing of fungicide applications. In addition, copper fungicides and acibenzolar-S-methyl have caused phytotoxicity in some environments. Fungicide applications may be reduced without incurring yield or quality loss in some environments and on some cultivars (Black et. al., 1992; Everts, 1998a & b). As the acreage of cultivars with moderate resistance increases, fungicide usage may be further reduced. The ability to schedule fungicide applications to coincide with periods of environmental conditions conducive to disease, would reduce application frequency and/or increase the efficacy of each application (Dainello and Jones, 1984; Jones and Dainello, 1983; Raabe and Pound, 1952 Sullivan, 1999; Sullivan et.al. 2002). A fungicide-application model based on the relationship between the environment and white rust on spinach was developed in Oklahoma (Sullivan, 1999). Temperature during periods of leaf wetness were used to time fungicide applications. This model was adapted and preliminary tests were conducted in the mid-Atlantic (Diagne et al., 2003). Several experiments were conducted in Maryland in 2002 to evaluate the ability of the weather-based fungicide application model to schedule sprays under mid-Atlantic weather conditions. Preliminary results indicate that the model may improve timing of fungicides. Preliminary results also indicate that the model would improve economic return for Maryland, Delaware, New Jersey and Virginia growers through reductions in disease incidence and therefore quality loss. Despite preliminary success with the model, we concluded that initiation of the model through scouting was not adequate to effectively manage white rust. Control of white rust is also impeded because little information exits on the importance of oospores as initial inoculum, and the optimum time to initiate fungicide applications. Our preliminary trials examining the model have clearly demonstrated that, although the model may result in better fungicide timing, delaying initial applications until disease is observed often results in unacceptable losses due to presumed oospore infections. Identical experiments were conducted at the UM Wye Research and Education Center in Queenstown in adjacent fields. One field had been cropped to spinach in the spring of 2002; one had not. Both experiments were planted, treated and harvested on the same days. The experiment was scouted weekly and fungicide applications were initiated at the first sign of disease. White rust incidence was unacceptably high in the double-cropped field. The initial infections, presumably from oospores, resulted in spinach that would have been rejected for processors, despite whether it was sprayed weekly or according to the model. However, where initial inoculum was not high, plots sprayed weekly or according to the model significantly reduced white rust incidence. These studies illustrate the importance of initial infections in losses due to white rust. Improved information on spray initiation in white rust control is critical. Objectives: The overall objective of this project is to assist growers in adopting a weather-based fungicide application model for spinach through an improved understanding of i) presence and extent of over-wintering oospore inoculum, ii) identification of the optimum to initiate fungicide applications, and iii) identification of fungicides that can be successfully used with a weather-based fungicide application model. Objective 1) Survey fields for the presence of oospores and determine their role as initial inoculum in epidemics. Oospores are not commonly observed in the mid-Atlantic region. Understanding when oopspores occur would assist in development of biologically based disease management strategies for white rust throughout the region. Objective 2) Determine optimum time to initiate weather-based fungicide application model for management of white rust of spinach. Preliminary trials of the weather-based fungicide application model initiated at first sign of disease did not adequately manage white rust. Here we will test the initiation of the model prior to disease onset. Objective 3) Evaluate reduced risk fungicides and biofungicides for management of white rust on spinach when scheduled according to the weather-based fungicide application model. Several products have recently been registered or are undergoing research or registration through the IR-4 program. USDA CRIS data Progress Report Final Report

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