# Fluorescence Hyperspectral Imaging for Early Diagnosis of Heat-Stressed Ginseng Plants
## 1 Introduction
Thermal imaging, which provides temperature information related to plant status [15; 22] through long-wave infrared spectra coupled with stereo visible light imaging, was applied to detect diseased tomato plants [23]. Additionally, the early diagnosis of plants based on morphological features has been widely used in color imaging in combination with machine learning and deep learning analysis. For example, digital images were used for early water stress detection in maize plants [24], automated high throughput systems were developed for the evaluation of salt tolerance in soybean plants [25], and a convolution neural network (CNN) was used for the real-time detection of apple leaf disease and identification of _Arabica_ and _Robusta_ coffee plants [26]. Moreover, several spectroscopic and imaging techniques have been used to assess plants' biotic and abiotic stress detection. Among the non-destructive technologies, HSI combined with chemometrics has been widely used to inspect the phenotypic status of plants. The main advantage of HSI technology is that it provides spatial and chemical information about a scene/subject beyond the range of human-eye visualization (700 nm). For example, HSI has been used for water stress detection in apple trees [27], early-stage detection of drought stress in _Arabidopsis Thaliana_ plants [28], and the early detection of tomato-spotted wilt virus [29]. In addition, fluorescence HSI is used widely for monitoring plant states and in phenotypic response analysis. FL-HSI was used for drought stress inspection of soybean plants over different treatments [30] and for detecting and quantifying the _Pseudomonas Cichorii_ pathogen in tomato plants [31]. Additionally, hyperspectral chlorophyll fluorescence imaging was used for the early detection of diseases in wheat plants [32], the visualization of infected grapevine leaves associated with leafroll virus and its effects on the photosynthetic of plants [33], the detection of heavy metal effects on plants' productivity, and the photosynthetic reactions of plants exposed to heavy thallium [34]. Furthermore, advances in hyperspectral imaging technologies are employed to assess solar-induced fluorescence (SIF) for the prediction of the photosynthesis properties of plants. Hyperspectral imaging systems allow for simultaneous and accurate assessment of the SIF emission in plant leaves, which provides a visual representation of physiological changes caused by the photosynthetic activities of the plants in the early stage. For instance, water stress in sugar beet was detected based on the S.I.F. using hyperspectral imaging [35], irrigation deficiency in orange (_Citrus sinensis_ L. cv. [PERSON]) field was monitored [36], and another study assessing forest plants' health in early stages used hyperspectral imaging for the extraction of SIF [37], and apple tree volume mapping [38]. Since crops' photosynthetic activities directly influence the physiological changes in plants, further research needs to investigate the involved mechanisms. In this study, we explored the potential of line-scan fluorescence HSI to detect heat-stressed ginseng plants in the early stages. In a fluorescence illumination system, the photoreactive components of materials must absorb light energy in a particular wavelength to emit the absorbed light. Different objects exhibit different reactions upon exposure to light (absorbing, scattering, or emitting light or any other combination). According to previous studies, fluorescence has been widely applied in agriculture for different purposes, indicating that plants' compounds are susceptible to releasing absorbed energy from fluorescence. The emission wavelength and intensity are influenced by excitation states, power, and exposure.