Leaf and canopy spectra, symptom progression, and physiological data from experimental detection of oak wilt in oak seedlings

These data were collected as part of an experimental effort to accurately detect oak wilt infections in oak seedlings using remote sensing tools and to differentiate that disease stress from other mechanisms of tree decline. Oak wilt disease causes rapid mortality in oaks in the central and eastern United States. Management of the disease requires early diagnosis and tree removal to prevent fungal spread. Hyperspectral tools provide a potential method of early remote diagnosis, but accurately differentiating oak wilt from other agents of oak decline is integral to effective management. We conducted experiments (2017 and 2018) on two year old seedlings of Quercus ellipsoidalis and Q. macrocarpa in which treatments were 1) maintained as healthy individuals, 2) subjected to chronic drought, or inoculated 3) stems with oak wilt fungus (Bretziella fagacearum, a fungal vascular wilt) or 4) leaves with bur oak blight fungus (Tubakia iowensis, a fungal leaf pathogen). We measured leaf and whole plant hyperspectral reflectance (350 to 2400nm, Spectra Vista HR 1024i spectroradiometer (Spectra Vista Corporation, New York, USA)), gas exchange (LI-6440XT with a leaf chamber fluorometer attachment (LI-COR Environmental, Nebraska, USA)), and tracked symptom development in repeated measures of seedlings over the course of each experiment. In 2018, we explicitly measured spectral reflectance and gas exchange on both symptomatic and green leaves, as available and we also measured collected thermal images of leaves twice during the experiment (2018 only).University of Minnesota Grand Challenges Research Grant, Minnesota Invasive Terrestrial Plants and Pests Center (Legislative-Citizen Commission on Minnesota Resources) GrantTes