# Quantifying Nutrient Content in the Leaves of Cowpea Using Remote Sensing
## 3 Results and Discussion
### Model Calibration
#### 3.3.3 Partial Least Squares Regression (PLSR)  
Using reflectance data from the cowpea, models were tested that aimed to estimate the leaf nutrient content at stages V4, R6 and R9 individually, as well as a single model tested using joint data from all three stages. The bands selected to generate the models for estimating the nutrient content in the leaves of _Vigna unguiculata_ (L.) [PERSON] are shown in Table 4 and the calibration equations in Table 5.  
The models tested for the individual phenological stages (Table 4) did not select any useful bands for predicting the levels of each of the nutrients evaluated in this study. However, when using the data from the three stages together, it was possible to select a considerable number of bands to construct the model for each nutrient. Analysing Table 4, it can be seen that in the PLSR models obtained for predicting P, wavelengths located in both the visible region and the NIR intervals that are influenced by this nutrient were selected. P is an important macronutrient, as it is involved in the metabolic processes of plants [73], being a part of protein and lipid molecules. The spectral regions most affected by these compounds are located between 350 and 1500 nm and from  
Figure 7: Two-dimensional correlogram between spectral reflectance and the leaf phosphorus (**A**), potassium (**B**), calcium (**C**) and zinc (**D**) content. 2350 to 2500 nm [74]. Furthermore, P also participates in the processes of producing energy for photosynthesis [62], as it is strongly influenced by wavelengths in the visible region. In the present study, only one wavelength was selected in the range mentioned by [74]; the remaining wavelengths selected by the PLSR models are mostly in the visible region (Table 4). K is strongly related to carbohydrates and organic acids and can be measured indirectly using these compounds in the near-infrared region [75]. Disagreeing with the results obtained in this study, [PERSON] [74] states that regions of the electromagnetic spectrum most strongly affected by carbohydrates are found roughly between 1000 and 1500 nm and from 1950 to 2300 nm. The PLSR models selected few wavelengths in the near-infrared, while the greatest number of wavelengths for obtaining the Ca estimation model were selected at the V4 stage. As a macronutrient, Ca is strongly related to leaf structure; on the electromagnetic spectrum, this region is located in the near-infrared, between 700 and 1500 nm. Unlike the \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Phenological Stage** & **Nutrient** & **Band** & **n** & **Adjusted R2** \\ \hline \multirow{3}{*}{V4} & Ca & 413, 625, 1301, 1405, 1683, & \multirow{3}{*}{16} & \multirow{3}{*}{0.98} \\  & Zn & 634, 1364, 1981, 1994 & & \\ \hline \multirow{2}{*}{R6} & Zn & 923, 925, 944, 951, 1864, 1890 & 17 & 0.90 \\ \hline \multirow{2}{*}{R9} & K & 630, 1405 & 17 & 0.43 \\  & Ca & 613, 631, 1350 & 17 & 0.59 \\ \hline \multirow{3}{*}{All} & P & 504, 651, 685, 1649, 1715 & 50 & 0.77 \\  & K & 504, 651, 685, 1715, 1735 & 50 & 0.84 \\ (V4, R6, R9) & Ca & 705, 1890, 2377 & 50 & 0.73 \\ \cline{1-1}  & Zn & 751, 1715, 2434 & 50 & 0.57 \\ \hline \hline \end{tabular} n: Number of data used to calibrate the models.  
\end{table} 
Table 4: Spectral bands selected for calibrating the PLSR models.