# Winter Wheat Take-All Disease Index Estimation Model Based on Hyperspectral Data
## 3 Results  
### Selection of Spectral Index Combinations of Winter Wheat Take-All  
The 450-700 nm range (visible light) is the strong absorption band of plant leaves. Due to the strong absorption of plant pigments, especially chlorophyll, green light reflection peaks are formed at 550 nm and red absorption valleys are formed at 660 nm, showing unique vegetation pigments Spectral characteristics [32].  
It can be seen from the spectral reflectance curves of wheat at different disease levels that healthy wheat shows stronger reflection peaks and absorption valleys at 550 nm and 660 nm than the wheat affected by the disease, as depicted in Figure 3. The reason is that the spectral reflectance of winter wheat canopy decreases with the increase of chlorophyll content in leaves. Due to the increase of chlorophyll level, the photosynthesis of corresponding leaves increases, the absorption capacity of red and blue light is enhanced and the corresponding spectral reflectance is reduced. With the aggravation of wheat total erosion disease, the peak valley appearance gradually tends to be flat, the reflection platform in near-infrared band tends to be smooth, the spectral reflectance at 750-950 nm continues to decrease and the change between different disease grades is the most obvious at 750-950 nm (Figure 3).  
The spectral combination range that can effectively estimate the disease index can be roughly observed by the isopotential map of determination coefficient constructed by disease index and spectral index NDSI (Figure 4). The red area shows the highest values of correlation and the blue area shows the lowest value. Figure 3 showed the correlation between wheat take-all disease index and spectral index. Some regions near the red edge at 750 nm showed extremely high correlation and a high correlation at 750-950 nm. The optimal spectral index combination was screened and the autocorrelation between bands was eliminated. The bands were screened by spectral interval.  
Figure 4: Contour maps of \(R^{2}\) between disease index and NDSI.  
Figure 3: Spectral curves of wheat with different disease grades.  
The determination coefficient equipotential map was divided into 16 intervals according to the spectral ranges of 450, 550, 630 and 750 nm. Due to the symmetry of the equipotential map, four regions including the diagonal and six regions that do not repeat in the symmetric region were selected for the selection of spectral combination of a total of 10 regions. According to the determination coefficient \(R^{2}\) of equipotential map, the highest band combination in the region was selected as the inversion parameter of wheat take-all disease indices and its NDSI was calculated. In order to obtain the optimal disease index inversion model, the spectral index NDSI was constructed by extracting the highest spectral combination in each interval from the calculated results of the above equipotential map data. When the wavelength \(\lambda\) was between 450 nm and 550 nm, it was considered to be in the blue interval. If the wavelengths constituting NDSI are not in the same interval, this interval is named as the combination of their respective wavelength intervals.  
The spectral combination information of 10 intervals was summarized in Table 2, among which the near infrared NDSI(R\({}_{810}\),R\({}_{834}\)) had the highest determination coefficient (\(R^{2}\) = 0.828), followed by blue-red NDSI(R\({}_{534}\),R\({}_{742}\)) (\(R^{2}\) = 0.793).