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ARS Home » Pacific West Area » Corvallis, Oregon » Forage Seed and Cereal Research Unit » Research » Publications at this Location » Publication #411225

Research Project: Optimizing and Stabilizing Economic and Ecological Sustainability of Pacific Northwest Seed Cropping Systems Under Current and Future Climate Conditions

Location: Forage Seed and Cereal Research Unit

Title: Comparison of molecular and morphological identification methods for Anguina seed gall nematodes in Oregon grasses grown for seed

Author
item Rivedal, Hannah
item Temple, Todd
item STARCHVICK, ROBERT - Oregon State University
item BRAITHWAITE, EMILY - Oregon State University
item LOWDER, SARAH - University Of Georgia
item Dorman, Seth
item NUNEZ RODRIGUEZ, LESTER - Oregon State University
item Peetz, Amy
item Zasada, Inga

Submitted to: PhytoFrontiers
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/7/2024
Publication Date: 5/6/2024
Citation: Rivedal, H.M., Temple, T.N., Starchvick, R.J., Braithwaite, E.T., Lowder, S.R., Dorman, S.J., Nunez Rodriguez, L.A., Peetz, A.B., Zasada, I.A. 2024. Comparison of molecular and morphological identification methods for Anguina seed gall nematodes in Oregon grasses grown for seed. PhytoFrontiers. https://doi.org/10.1094/PHYTOFR-01-24-0001-R.
DOI: https://doi.org/10.1094/PHYTOFR-01-24-0001-R

Interpretive Summary: Oregon’s grass seed industry specializes in production of forage grasses, like annual ryegrass (Lolium multiflorum) and orchardgrass (Dactylis glomerata). These species can be infected with seed gall nematodes (SGN): Anguina funesta and Anguina sp. Trade partners have strict phytosanitary regulations leading to rejection of seed lots infested with SGN. Current best practices for SGN detection focus on post-harvest seed evaluation. Methods to evaluate fields before harvest could improve risk management decisions. In this study, we evaluated timing, collection, and detection methods, to generate new recommendations for SGN detection throughout the growing season. Traditional nematology methods resulted in detection of SGN from plant material in 11-40% of fields as opposed to 33-44% of fields when using molecular methods. This study indicates the utility of incorporating molecular methods for risk evaluations of SGN and provides recommendations for the accurate detection of SGN throughout the growing season.

Technical Abstract: Oregon’s grass seed industry specializes in production of forage grasses, including annual ryegrass (Lolium multiflorum) and orchardgrass (Dactylis glomerata). These species are hosts of seed gall nematodes (SGN): Anguina funesta and Anguina sp. SGN cause yield-limiting seed galls and can also vector toxic Rathayibacter bacteria. Trade partners have strict phytosanitary regulations leading to rejection of seed lots infested with SGN. Current best practices for SGN detection focus on post-harvest seed evaluation. Methods to evaluate fields before harvest could improve risk management decisions. In this study, we evaluated timing, collection, and detection methods, to generate new recommendations for SGN detection throughout the growing season. Fields of annual ryegrass (21) and orchardgrass (7) were sampled in the 2022 and 2023 growing seasons at tillering (March), flowering (May), harvest (July), and germination (November). At each time point, tillers, seed heads or soil samples were collected. Nematodes were extracted from soil, tiller, and seed head samples using traditional nematology methods. Alternatively, SGN-specific real-time and conventional PCR protocols were evaluated on DNA extracted from tillers or seed heads. Direct enumeration of SGN from tillers with traditional nematology methods resulted in positive detections in 11-19% of fields depending on sample time and year as opposed to 33-44% of fields when using molecular methods. SGN were detected in 40% of fields using both methods when evaluating seed head samples. This study indicates the utility of incorporating molecular methods for risk evaluations of SGN and provides recommendations for the accurate detection of SGN throughout the growing season.