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, from among other mechanisms of decline. We subjected greenhouse-grown oak seedlings (Quercus ellipsoidalis and Q. macrocarpa) to chronic drought or inoculation with the oak wilt fungus or bur oak blight fungus (Tubakia iowensis). We measured leaf and canopy spectroscopic reflectance (400-2,400 nm) and instantaneous photosynthetic and stomatal conductance rates, then used Partial Least Squares Discriminant Analysis (PLS-DA) 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 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.

中文翻译：

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从叶真菌病和干旱引起的橡树枯萎病的光谱分化与生理变化相关。

高光谱反射工具已被用于检测农业环境中的多种病原体以及单一感染源或林分广泛下降。但是，将任何一种疾病与其他树木压力源区分开来，对于混合物种系统中的林分和景观水平应用都是必不可少的。我们测试了光谱模型与其他衰退机理之间的区别，该模型能够区分橡木枯萎（一种由致命小白菜（Bretziella fagacearum）引起的致命性疾病）。我们对温室种植的橡树幼苗（椭圆栎和Q. macrocarpa）进行了长期干旱或接种了橡树枯萎真菌或伯橡树枯萎真菌（Tubakia iowensis）。我们测量了叶和冠层的光谱反射率（400-2,400 nm）以及瞬时光合和气孔电导率，然后使用偏最小二乘判别分析（PLS-DA）从高光谱数据预测治疗。我们在症状出现之前检测到橡树枯萎，并在有症状的叶子中以高准确度将疾病分类。橡木分类接种的植物中，光谱的分类准确度随光合功能下降而增加。橡树枯萎病的波长诊断仅在不可见光谱区域发现，并且与水状态，非结构性碳水化合物和光合作用机制有关。我们表明，高光谱模型可以将枯萎与其他引起树木枯萎的原因区分开，并且检测与枯萎感染和疾病进展的生物学机制相关。我们还表明，在树冠症状内异质性可以减少检测，但是有症状的叶子和树冠适合于高度准确的诊断。高光谱工具的远程应用可用于跨多种物种森林表现出多种压力症状的疾病的特异性检测。