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ARS Home » Northeast Area » Frederick, Maryland » Foreign Disease-Weed Science Research » Research » Publications at this Location » Publication #264695
Title: Inoculum density effects on infection of selected Eastern US forest species by Phytophthora ramorum

Author
item Tooley, Paul
item Browning, Marsha

Submitted to: Phytopathology
Publication Type: Abstract Only
Publication Acceptance Date: 3/9/2011
Publication Date: 6/1/2011
Citation: Tooley, P.W., Browning, M.E. 2011. Inoculum density effects on infection of selected Eastern US forest species by Phytophthora ramorum. Phytopathology. 101:S274-275.

Interpretive Summary:

Technical Abstract: Inoculum threshold information can be used to better understand the epidemiology of P. ramorum should it become established in the Eastern US. Detached leaves from Quercus prinus, Q. rubra, Acer rubrum, Kalmia latifolia ‘Hoffman’s K’, and Rhododendron ‘Cunningham’s White’ were exposed to sporangia concentrations ranging from 0 to 3000 sporangia per milliliter. Three leaves per species per experiment were dip-inoculated and positioned between layers of moistened paper towels in sealed plastic containers at 20 degrees Celsius for five days. Experiments were also conducted using stems of 2-3 year old seedlings of Q. prinus, Q. rubra and A. rubrum. Treatments ranging from 0 to 3000 sporangia per milliliter were applied to wounded and unwounded stem tissue. Detached leaf inoculations resulted in disease in all five species at all concentrations tested. Wounding was required for infection of stems to occur. With both stems and detached leaves, disease was observed at the lowest sporangia concentrations utilized; 100 sporangia per milliliter for stems and 10 sporangia per milliliter for detached leaves. The results indicate that P. ramorum is capable of infecting some major Eastern US forest species at very low inoculum levels. This information can be combined with knowledge of understory host distribution and sporulation capacity to predict epidemic potential in new areas, and enhance development of risk assessment models.