# Classification Models for Nitrogen Concentration in Hop Leaves Using Digital Image Processing
## 3 Results  
The results of the descriptive summary of the DIP data and _t_-test show that the variables G and NB exhibited a significant difference between the means of the two groups (\(p<0.05\)) for both image sources. Additionally, the variables R, NR, GRRI, and MPRI also showed a difference between the groups for the data obtained from the scanner, while the B variable only showed a difference for the data obtained from the mobile phone (Table 3). This suggests that spectral characteristics, particularly those related to colors and vegetation indices, respond differently depending on the image acquisition method, possibly due to variations in light capture and image quality between the mobile phone and the printer. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Variables**} & \multicolumn{3}{c}{**Mobile Phone Images**} & \multicolumn{3}{c}{**Scanner Images**} \\ \cline{2-7}  & **G1** & **G2** & \multirow{2}{*}{\(p\)} & **G1** & **G2** & \multirow{2}{*}{\(p\)} \\  & **(n\({}_{1}\) = 12)** & & **(n\({}_{2}\) = 60)** & & **(n\({}_{1}\) = 78)** & **(n\({}_{2}\) = 72)** & \\ \hline \multirow{4}{*}{**A**} & 66.2 (26.1) & 64.7 (19.0) & _0.81_ * & 67.6 (21.9) & 63.0 (21.1) & _0.19_ * \\  & 70.9 & 60.5 & 63.3 & 61.9 & \\  & (26.4–99.1) & (21.1–107.9) & & (31.1–123.0) & (25.3–104.6) & \\ \hline \multirow{4}{*}{**P**} & 57.1 (14.4) & 59.6 (10.0) & _0.47_ * & 45.7 (9.0) & 43.7 (9.0) & _0.19_ * \\  & 60.8 & 59.7 & 45.7 & 43.8 & \\  & (30.1–75.4) & (31.3–92.0) & & (29.1–65.4) & (19.9–60.2) & \\ \hline \multirow{4}{*}{**Dmin**} & 2.8 (0.6) & 2.6 (0.9) & _0.51_ * & 3.5 (1.2) & 3.2 (1.2) & _0.36_ * \\  & 2.7 & 2.4 & & 2.9 & 3.2 & \\  & (1.9–4.3) & (1.3–6.1) & & (1.7–6.4) & (17–6.4) & \\ \hline \multirow{4}{*}{**Dmax**} & 12.4 (2.7) & 12.3 (1.6) & _0.87_ * & 12.8 (2.1) & 12.4 (2.1) & _0.29_ * \\  & 13.2 & 12.5 & & 13 & 12.2 & \\ \cline{1-1}  & (7.7–15.4) & (7.6–16.5) & & (8.7–17.5) & (7.1–17.1) & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Mean (standard deviation) [first row], median [second row], and minimum–maximum value [third row] of the variables measured in each image type group. It was also found that the nitrogen concentration did not show strong individual correlations with the DIP variables (Table 4). The highest correlation coefficients with nitrogen concentration were found for the following variables: leaf area (r = \(-\)0.37), perimeter (r = \(-\)0.35), mean R and NR (r = \(-\)0.35), as well as MPRI (r = \(-\)0.36). This pattern is consistent with the correlations observed in the image data matrices. By analyzing the Pearson correlation matrices of both databases (Figures 4 and 5), it was observed that some pairs of variables exhibited very high correlation coefficients in both groups, indicating that not all variables are necessary for adjusting the discriminant models. Measures A and P showed a high correlation with each other and with Dmax \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Databases**} & \multicolumn{8}{c}{**DIP Variables**} \\ \cline{2-13}  & **A** & **P** & **Dmin** & **Dmax** & **R** & **G** & **B** & **NR** & **NG** & **NB** & **GRRI** & **MPRI** & **YBA** \\ \hline
**Scanner** & 0.19 & 0.18 & 0.23 & 0.07 & 0.02 & \(-\)0.06 & \(-\)0.18 & 0.09 & 0.07 & \(-\)0.14 & \(-\)0.03 & 0.04 & \(-\)0.03 \\
**Mobile Phone** & \(-\)0.37 & \(-\)0.35 & \(-\)0.2 & \(-\)0.3 & \(-\)0.35 & \(-\)0.29 & 0.17 & \(-\)0.35 & 0.04 & 0.24 & 0.4 & \(-\)0.36 & \(-\)0.03 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Correlations between nitrogen concentration and DIP variables.