Plant pathogens and environmental stress can have a detrimental impact on forest health, biomass and growth. Early detection and identification of biotic and abiotic stresses, ideally before visible symptoms are present, are important for effective forest management practice and early control of pathogen, and to minimize damage. However, reliably detecting and identifying plant diseases and stress in the field are usually constrained by time and the large size of the area of interest. In this issue, Fallon et al. (2020) demonstrates how hyperspectral reflectance measurements can be used to detect fungal diseases and drought stress in two North American Oak species. The work of Fallon and co-authors exemplifies that fast and non-destructive high-throughput field phenotyping is not limited to crops and agricultural settings (Singh et al. 2016, Lowe et al. 2017), but is also promising to detect and classify the early onset of diseases and stress in forest tree species. Much focus has been on reflectance measurements in the visible, near-infrared (NIR) and short-wave infrared (SWIR), because changes in these wavelength areas are associated with several physiological and biochemical traits (Ge et al. 2019). Hyperspectral measurements are non-destructive, so repeated measurements can be taken of the same plant, and it takes only a few seconds to obtain multiple scans of a single leaf (Ge et al. 2019). In addition, multiple traits or properties can be modelled and estimated from a single leaf scan. All this greatly advances detection and monitoring of biological processes and stress responses at scales from single leaves to ecosystems, to assess for example, the relationship between water shortage and photosynthetic properties of crops (El-Hendawy et al. 2017), to identify species richness and biodiversity in prairie ecosystems (Wang et al. 2018), or for pre-visual detection of symptoms of pathogen infection (Zarco-Tejada et al. 2018).

中文翻译：

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快速诊断：高光谱反射将疾病与树木的干旱胁迫区分开来。

植物病原体和环境胁迫会对森林健康，生物量和生长产生不利影响。最好在出现可见症状之前尽早发现和识别生物和非生物胁迫，对于有效的森林管理实践和病原体的早期控制以及使损害最小化非常重要。然而，可靠地检测和识别野外植物病害和胁迫通常受到时间和关注区域的大尺寸的限制。在这个问题上，法伦等。（2020）证明了高光谱反射率测量可用于检测两种北美橡树种的真菌病和干旱胁迫。Fallon及其合作者的研究表明，快速且无损的高通量田间表型分析不仅限于农作物和农业环境（Singh等人，2016年，劳等。2017），但也有望对林木物种的疾病和压力的早期发作进行检测和分类。由于可见光，近红外（NIR）和短波红外（SWIR）的反射率测量与多种生理和生化特性有关（Ge等人，2019），因此很多注意力都集中在反射率的测量上。高光谱测量是非破坏性的，因此可以对同一棵植物进行重复测量，并且仅需几秒钟即可获得对单片叶子的多次扫描（Ge et al.2019）。另外，可以从单片叶子扫描中建模和估计多个特征或特性。所有这些都极大地促进了从单叶到生态系统的尺度上的生物过程和胁迫响应的检测和监测，以评估例如