# Application of Hyperspectral Imaging for Assessment of Tomato Leaf Water Status in Plant Factories
## 3 Results and Discussion
### Application of NDVI and TBI to Wavelength and Water Status
#### 3.5.3 Characteristic Wavelength Bands  
Numerous studies have demonstrated that the wavelengths that are the most sensitive to leaf water status are in the 900-2500 nm range, which includes four water absorption bands for all angiosperm leaves around 970 nm, 1200 nm, 1400 nm, and 1900 nm [2; 8]. Nevertheless, owing to equipment limitations in the present experiment, wavelengths ranging from 1700 nm to 2500 nm were not addressed. Only several different characteristic wavelength bands in the 900-1700 nm range were employed to establish models based on spectral preprocessing for different water statuses (Table 2). For WC assessment, one of the two characteristic wavelengths for NDVI or TBI was concentrated at 1390 nm, very close to 1400 nm, which is well known as the main water absorption band of the leaf [9]. Another characteristic wavelength was concentrated at 1600 nm, which is a wavelength band that is also often chosen by researchers. By using the wavelengths of 1600 nm and 819 nm, [PERSON] et al. [19] and [PERSON] [17] developed a normalized difference infrared index (NDII) model and moisture stress index (MSI) model for detecting variations in the leaf WC with different respective expressions. All of the above proved that the wavelengths around 1400 nm and 1600 nm have a strong correlation with leaf WC. However, on account of the different characteristics of the leaf itself, the measuring equipment, and other factors, the characteristic wavelength selection may be slightly offset in the actual application. The best model for WC assessment was obtained in this experiment using TBI with DIFF and the 1410 nm and 1520 nm wavelengths. Similar results were demonstrated by [PERSON] et al. [35]. To identify the best indices for relative water content (RWC) and equivalent water thickness (EWT) based on the first-derivative reflectance, they chose the wavelengths of 1415 nm and 1530 nm for RWC by using the same NDVI expression, and 1530 nm and 1895 nm for EWT by using a simple ratio expression. For MC assessment, several characteristic wavelengths exist for NDVI or TBI models with high performances in this experiment. They are concentrated around 950 nm, 1300 nm, 1350 nm, and 1400 nm. The wavelength bands of 950 nm and 1400 nm are very close to or equal the central wavelengths of \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Regression Models**} & \multirow{2}{*}{**Data Sets**} & \multicolumn{3}{c}{**WC (\%)**} & \multicolumn{3}{c}{**MC (g/dm\({}^{2}\))**} \\  & & **Wavelength** & \(R^{2}\) & \(r^{2}\) & **RMSE** &
\begin{tabular}{c} **Wavelength** \\ **Bands (nm)** \\ \end{tabular} & \(R^{2}\) & \(r^{2}\) & **RMSE** \\ \hline \multirow{3}{*}{NDVI} & RAW & 1390, 1600 & 0.6060 & 0.3672 & 1.44 & 1300, 1310 & 0.8042 & 0.6467 & 0.2689 \\  & LOG & 1390, 1600 & 0.6080 & 0.3696 & 1.44 & 950, 1350 & 0.7550 & 0.5699 & 0.2967 \\  & DIFF & 1370, 1610 & 0.5643 & 0.3185 & 1.49 & 1310, 1410 & 0.7733 & 0.5980 & 0.2869 \\  & RAW & 1400, 1570 & 0.5950 & 0.3540 & 1.45 & 1300, 1310 & 0.7886 & 0.6389 & 0.2720 \\  & LOG & 1390, 1620 & 0.5851 & 0.3430 & 1.47 & 950, 1350 & 0.7500 & 0.5707 & 0.2971 \\  & DIFF & 1410, 1520 & 0.6369 & 0.4057 & 1.39 & 1310, 1400 & 0.7716 & 0.5972 & 0.2878 \\ \hline \multicolumn{10}{l}{\(R^{2}\): coefficient of determination for calibration, \(r^{2}\): coefficient of determination for validation, RMSE: root-mean-square error.} \\ \end{tabular}
\end{table} 
Table 2: Model performance by using NDVI and TBI according to wavelength and water status. the water absorption bands of 970 nm and 1400 nm [2; 8]. It is well explained why these two bands are chosen as characteristic wavelengths for high performance modeling. Regarding the wavelength of 1350 nm, in 2007, [PERSON] et al. developed a simple ratio vegetation index using wavelengths of 1070 and 1340 nm, and a moisture stress index using wavelengths of 870 and 1350 nm, to detect the MC for grape leaves, and both quantities exhibited excellent correlations with MC, with R \(>\) 0.90 [36].