Hyperspectral reflectance tools have been used to detect multiple pathogens in agricultural settings and single sources of infection or broad declines in forest stands. However, differentiation of any one disease from other sources of tree stress is integral for stand and landscape-level applications in mixed species systems. We tested the ability of spectral models to differentiate oak wilt, a fatal disease in oaks caused by Bretziella fagacearum ``Bretz'', from among other mechanisms of decline. We subjected greenhouse-grown oak seedlings (Quercus ellipsoidalis ``E.J. Hill'' and Quercus macrocarpa ``Michx.'') to chronic drought or inoculation with the oak wilt fungus or bur oak blight fungus (Tubakia iowensis ``T.C. Harr. & D. McNew''). We measured leaf and canopy spectroscopic reflectance (400–2400 nm) and instantaneous photosynthetic and stomatal conductance rates, then used partial least-squares discriminant analysis to predict treatment from hyperspectral data. We detected oak wilt before symptom appearance, and classified the disease with high accuracy in symptomatic leaves. Classification accuracy from spectra increased with declines in photosynthetic function in oak wilt-inoculated plants. Wavelengths diagnostic of oak wilt were only found in non-visible spectral regions and are associated with water status, non-structural carbohydrates and photosynthetic mechanisms. We show that hyperspectral models can differentiate oak wilt from other causes of tree decline and that detection is correlated with biological mechanisms of oak wilt infection and disease progression. We also show that within the canopy, symptom heterogeneity can reduce detection, but that symptomatic leaves and tree canopies are suitable for highly accurate diagnosis. Remote application of hyperspectral tools can be used for specific detection of disease across a multi-species forest stand exhibiting multiple stress symptoms.
Oak wilt caused by Ceratocystis fagacearum is a significant disease of Quercus spp. in the eastern United States. Early and accurate detection of the pathogen is particularly important when disease control is planned. Nested and real-time polymerase chain reaction (PCR) methods utilizing fungal DNA extracted from sapwood drill shavings of red, bur, and white oak at different stages of disease development were compared with culture-based detection from sapwood. The pathogen was detected in all (n = 3) actively wilting branches of each of nine red oak trees using all three methods. The lowest detection rate (33% of assayed branches; 6 of 8 trees) for actively wilting branches was found for white oak using isolation while nested PCR had a branch detection rate of 100% (8 of 8 trees) and real-time PCR of 87% (8 of 8 trees) for the same samples. For both bur and white oak, the pathogen was not detected by isolation in branches over 1 year after their death but was detected using both PCR methods. Only the PCR assays detected the fungus in sapwood samples underlying remnants of sporulation mats (n = 21; 90%, nested and 62%, real-time) on red oak. These PCR methods offer several significant improvements for laboratory-based detection methods of C. fagacearum.
Oak wilt caused by Bretziella fagacearum is an important disease of Quercus species, but its diagnosis may be confused with damage resulting from other diseases, insects, or abiotic factors. Laboratory diagnosis is important in such situations and when disease control action is desired. Polymerase chain reaction (PCR) tests can provide accurate lab diagnosis within two days. Two variations of a simple DNA extraction protocol using sodium hydroxide (NaOH) were compared to that of the proprietary protocol of a commercially available kit (CK) for nested PCR to detect the pathogen in oak sapwood. High frequencies of pathogen detection (98 to 100% of 48 branch segments assayed) were found for northern pin oak using the two NaOH-based and the CK methods. Detection rates were similar but lower for bur oak (ranged from 58 to 79%) and white oak (ranged from 54 to 71%) regardless of DNA extraction method. Using our alternative DNA extraction protocols may reduce total time and cost of B. fagacearum detection in PCR-based diagnosis and other downstream applications.
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