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ARS Home » Pacific West Area » Corvallis, Oregon » Forage Seed and Cereal Research Unit » Research » Research Project #449133

Research Project: New Solutions for Nematode Management on Cool-Season Putting Greens: Improved Diagnostics and Decision Models

Location: Forage Seed and Cereal Research Unit

Project Number: 2072-21600-001-024-T
Project Type: Trust Fund Cooperative Agreement

Start Date: Jan 1, 2026
End Date: Dec 31, 2028

Objective:
1. Establish a pot-in-pot study on an annual bluegrass research putting green to evaluate the damage caused by 1, 10, 100, 500, 1000, 5,000, and 10,000 individual Root-Knot (RKN) nematodes in a randomized complete block design. 2. Develop a Pacific Northwest (PNW) action threshold based on the Seinhorst equation the pot-in-pot results. 3. Validate nanopore sequencing for the detection and quantification of key Public Participation Network (PPN) community members at proposed thresholds for PNW turfgrass systems.

Approach:
Objective 1. Utilizing the OSU Lewis Brown Turfgrass Research farm, ARS will establish a pot-in-pot study site on an annual bluegrass green. The trial will be designed as a randomized complete block, with four replications and eight treatments. The trial area will be sprayed with an industry-standard nematicide to reduce the native PPN population, then 4x4 ft “plots” to a depth of 6 inches will be removed. The area from which the plot was pulled will be lined with plastic, and a layer of copper screen placed at the base and sides to deter roots from growing out of the plots and limit escaping nematodes. The grass/soil plots will be placed back into their location with plastic edging on each side. This will allow for quick removal of the edging for mowing purposes. To each plot, varying initial densities of RKN will be applied: 1, 10, 100, 500, 1,000, 5,000, or 10,000 individuals along with untreated control plots. There will be a 12-inch border between each plot. These border areas around the plots will receive regular nematicide treatment throughout the life of the study. PPN populations will be monitored monthly; a sample will consist of five ¾ inch soil cores to a depth of 3 inches per plot and the holes will be filled with sterilized sand. Counts of RKN populations will be conducted on an inverted microscope after a 72 hr. Baermann funnel extraction. The plots will be visually evaluated weekly for damage using qualitative ratings, along with a handheld NDVI calculator for plot green color. Any damage will be documented with photographs and detailed descriptions. After 12 months, root density will be compared across plots by cutting one cup-cutter sized plug and calculating it’s displacement in water. The trial will then continue for an additional 12 months, taking all the same measurements. Objective 2. Using the previously established Seinhorst model (Seinhorst 1965), we will calculate the relationship between turfgrass NDVI readings, RKN densities, and damage. Using Baysian methods, we will optimize and simulate inputs for the model (Wheeler et al 2019). A study set using samples from objective 1 prior to and during damage periods, along with data from previous surveys where damage was seen within 6 months, will also be included and used as simulation data. Results of developed Seinhorst curves will be compared with those generated by the SeinFit program, and results will be published in a manuscript. Objective 3. Over the 24 months of study, each plot will be sampled every six months for PPN identification and quantification with molecular methods (n = 32 plots x 4 sample times = 128 samples). Using the same sample as will be collected monthly in objective 1, nanopore sequencing of the 18S and COX1 gene regions will be conducted and results compared to morphological counts with generalized linear mixed models. Objective 4. Information generated from this work will be shared throughout the life of the project at industry events and field days. In addition, the results will be summarized in at least 2 manuscripts for journals like Plant Disease and Journal of Nematology.