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ARS Home » Pacific West Area » Salinas, California » Crop Improvement and Protection Research » Research » Research Project #426096

Research Project: Detection and Management of Pathogens in Strawberry and Vegetable Production Systems

Location: Crop Improvement and Protection Research

Project Number: 2038-22000-015-00-D
Project Type: In-House Appropriated

Start Date: Dec 17, 2013
End Date: Mar 29, 2017

The overall objective of this project is to develop diagnostic tools for detection, quantification, and identification of soilborne plant pathogens currently controlled by chemicals including methyl bromide and to develop technically and economically feasible alternatives to chemical control for high value crops, such as strawberries and vegetables. Objective 1: Optimize delivery and evaluate performance of cultural and biological control, management practices, and genetic alternatives for management of pathogens currently mediated by soil fumigation. Sub-objective 1.a. Evaluate alternatives to replace current fumigation strategies for management of soilborne pathogens. Sub-objective 1.b. Identify genes associated with pathogenicity of Verticillium dahliae to support the development of alternative control procedures. Sub-objective 1.b.1. Identify genes associated with pathogenicity of Verticillium dahliae based on a previous insertional mutagenesis study. Sub-objective 1.b.2. Evaluate expression of candidate pathogenicity-related genes in resistant and susceptible lettuce-Verticillium dahliae interactions. Sub-objective 1.c. Identify emerging diseases and their etiology, and evaluate germplasm for resistance to diseases of strawberry, lettuce, and vegetables. Sub-objective 1.c.1. Evaluate spinach germplasm for new sources of Verticillium dahliae resistance using an enhanced screening technique. Sub-objective 1.c.2. Evaluate primary inoculum sources of Peronospora effusa, the cause of downy mildew of spinach. Sub-objective 1.c.3. Identify pathogens of emerging and established bacterial diseases of strawberry and vegetables. Sub-objective 1.c.4. Identify and characterize lettuce and crucifer germplasm resistant to bacterial pathogens. Sub-objective 1.d. Identify factors associated with production, maintenance, and the degradation of inoculum to elucidate potential alternatives for pathogen control. Sub-objective 1.d.1. Identify and evaluate microbial predators of fungal and bacterial pathogens for disease control. Sub-objective 1.d.2. Functionally analyze candidate genes identified as up-regulated in microsclerotia development in Verticillium dahliae. Objective 2: Develop rapid and accurate molecular diagnostic tools for identifying emerging diseases of vegetables and strawberries, and use these tools in the development of management strategies as alternatives to methyl bromide. Sub-objective 2.a. Develop molecular markers for detecting and quantifying bacterial plant pathogens. Sub-objective 2.b. Develop molecular diagnostic tools for detection, quantification, and characterization of isolates of Peronospora effusa. Sub-objective 2.c. Develop molecular tools for identification and detection of Pythium and Phytophthora species. Sub-objective 2.c.1. Molecular diagnostics. Sub-objective 2.c.2. Improved identification of Phytophthora species. Sub-objective 2.c.3. Mitochondrial genomics project. Objective 3: Develop disease management strategies for the soil-borne fungal pathogens Macrophomina and Fusarium on strawberry (strawberry collapse disorder) and integrate these strategies into sustainable crop production systems.

Develop integrated management approaches including crop rotation, biological control, selection of disease resistant varieties, organic production, other biological practices, and combinations of biological practices to control diseases. Evaluate responses of the root biome to these practices through metagenomics analyses. Identifying useful biological agents through traditional microbiological methods or soil metagenomics, as well as new agents, that will help to improve disease management. Molecular tools will be developed for plant pathogen identification, evaluation of the efficacy of pathogen management and modeling population dynamics of plant pathogens and beneficial microbes.