# Rapid Estimation of Moisture Content in Unpeeled Potato Tubers Using Hyperspectral Imaging
## 3 Results and Discussion  
Before preprocessing the spectrum data, the average spectrum of all the pixels inside the ROI of each unpeeled potato sample was computed. The averaged spectra were subjected to preprocessing techniques, such as standard normal variate (SNV), mean filter with 5 \(\times\) 5 window size (MF5), mean filter with 9 \(\times\) 9 window size (MF9), the first and second derivatives calculated using Savitzky-Golay smoothing (1D-SG and 2D-SG), and multiplicative scatter correction (MSC). The original averaged spectra and their related preprocessed spectra were used to create the PLSR model. A total of seven PLSR models were created based on the preprocessing procedures performed on the HSI dataset before determining the best wavelengths, where 204 spectral bands are recorded by the hyperspectral sensor at wavelengths ranging from 397.32 to 1003.58 nm [60]. Similarly, 79 spectral bands are recorded at wavelengths ranging from 732.53 to 969.63. The key statistical metrics utilized to evaluate the performance of the PLSR model including latent variables (LVs), R\({}^{2}\), RMSE, and RPD, are included in Tables 1 and 2 respectively. The R\({}^{2}\) value between the predicted and measured moisture content was used to assess the prediction models' performance via RMSE and RPD, respectively. The model was considered good if RMSE was low and both R\({}^{2}\) and RPD were high. The PLSR results when considering full HSI wavelengths were compared with results when selecting important wavelength ranges. It was tested to see if choosing significant wavelengths increased the models' ability to predict outcomes more accurately. A total of seven models were developed using the \(\beta\)-coefficient and VIP wavelength selection methods. When full HSI wavelengths were considered, six of the seven models performed poorly (RPD \(<\) 1.4) and only the PLSR \(\beta\)-coefficient (R\({}^{2}\) = 0.53, RMSE = 5.02, and RPD = 1.47) and PLSR no \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{\begin{tabular}{c} **Preprocessing** \\ **Method** \\ \end{tabular} } & \multirow{2}{*}{**LV**} & \multirow{2}{*}{\
\begin{tabular}{c} **Wavelength** \\ **(A/B/C)** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **No Wavelength** \\ **Selection** \\ \end{tabular} } & \multicolumn{2}{c}{**VIP Based Wavelength**} & \multicolumn{2}{c}{\(\beta\)**-Coefficient**} \\  & & & & **Selection** & & & **Selection** & & **Wavelength Selection** \\ \cline{2-11}  & & & **R\({}^{2}\)** & **RPD** & **RMSE** & **R\({}^{2}\)** & **RPD** & **RMSE** & **R\({}^{2}\)** & **RPD** & **RMSE** \\ \hline I & NO & 8 & 204/73/51 & 0.53 & 1.46 & 5.04 & 0.51 & 1.43 & 5.16 & 0.53 & 1.47 & 5.02 \\ \hline II & 1D-SG & 6 & 204/61/61 & 0.48 & 1.39 & 5.29 & 0.46 & 1.36 & 5.40 & 0.48 & 1.38 & 5.32 \\ \hline III & 2D-SG & 2 & 204/75/57 & 0.26 & 1.16 & 6.34 & 0.29 & 1.18 & 6.22 & 0.30 & 1.19 & 6.18 \\ \hline IV & SNV & 7 & 204/65/52 & 0.45 & 1.35 & 5.46 & 0.40 & 1.29 & 5.73 & 0.43 & 1.33 & 5.54 \\ \hline V & MSC & 7 & 204/62/51 & 0.47 & 1.37 & 5.36 & 0.44 & 1.34 & 5.50 & 0.47 & 1.37 & 5.36 \\ \hline VI & MF5 & 8 & 204/66/53 & 0.49 & 1.40 & 5.27 & 0.47 & 1.38 & 5.35 & 0.44 & 1.34 & 5.49 \\ \hline VII & MF9 & 8 & 204/67/56 & 0.47 & 1.38 & 5.35 & 0.45 & 1.35 & 5.44 & 0.41 & 1.30 & 5.66 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The PLSR results when considering the full HSI wavelengths between 397.32 and 1003.58 (a total of 204 spectral bands). wavelength selection (R\({}^{2}\) = 0.53, RMSE = 5.04, and RPD = 1.46) with no preprocessing technique showed acceptable performance (RPD \(>\) 1.4). The performance based on VIP wavelength selection was low (R\({}^{2}\) = 0.51, RMSE = 5.16, and RPD = 1.43) when compared with no wavelength selection and \(\beta\)-coefficient wavelength selection. Figure 4 shows that the optimum model created using \(\beta\)-coefficient wavelength selection with no preprocessing also showed acceptable performance (R\({}^{2}\) = 0.53, RMSE = 5.02, and RPD = 1.47).