## Materials and Methods
### Analysis Methods  
#### 2.3.1 Selection of Candidate Spectral Features  
Spectral derivative is a basic hyperspectral analysis technology. The transformation of the first-order derivative reflects the variation range of vegetation reflectance in each band, which can reduce the effects of atmospheric and background noise, and better reflect the essential features of plants [24]. Therefore, the spectral features sensitive to FHB were extracted by using the hyperspectral features of the first-order derivative transformation, including positional, area, ratio, and normalized index features (Table 2). \begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & **Features** & **Definition and Description** \\ \hline \multirow{7}{*}{Spectral position feature} & Db & Blue edge (490–530 nm) maximum \\  & & first-order derivative value \\  & Dy & Yellow edge (550–582 nm) maximum \\  & & first-order derivative value \\  & Dr & Red edge (680–780 nm) maximum \\  & & first-order derivative value \\  & \(\lambda\)b & The wavelength of Db \\  & \(\lambda\)y & The wavelength of Dy \\  & \(\lambda\)r & The wavelength of Dr \\ \hline \multirow{7}{*}{Spectral area feature} & SDb & First-order derivative sum in the \\  & & blue-edge wavelength range \\ \cline{1-1}  & & First-order derivative sum in the \\ \cline{1-1}  & & yellow-edge wavelength range \\ \cline{1-1}  & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & \multicolumn{1}{c}{} \\ \end{tabular}
\end{table} 
Table 2: Hyperspectral features based on first order derivatives. In FHB-infected ear tissues, absorption in the range of the chlorophyll bands rapidly decreased with development of infection as a result of destruction of chloroplasts, and successively, degradation of chlorophylls in cells attacked by fungi [16]. The dry shrinkage of ear tissue and the decrease of chlorophyll and water content causes the change of absorption position and spectral reflectivity of the red band [16; 25]. The main purpose of continuum removal is to eliminate the irrelevant background information and enhance the spectrum absorption characteristic information [25]. The reflectance of the continuum removal in the range of 550-750 nm was calculated, and then the absorption characteristics were obtained. The main absorption characteristics are the absorption wavelength position, depth, width, and area (Table 3). The principle of continuum removal and the specific extraction process are described by [PERSON] et al. [25] and [PERSON] et al. [26]. The main purpose of this step was to find sensitive features of physiological and biochemical changes caused by FHB. The vegetation index method is a basic and commonly used information extraction technology in agricultural remote sensing monitoring research. Changes in plant pigment, moisture content, and internal structure occur when winter wheat is infected with pathogenic bacteria, and these changes can be reflected by spectral reflectance [17]. Based on prior knowledge, with reference to the application of various vegetation indices in the monitoring of plant diseases and insect pests, 16 vegetation indices based on hyperspectral data were selected and their applicability in assessing the severity of FHB was discussed.