## 3 Results
### Evaluation of Near-Infrared Spectroscopy (NIRS) Data  
Table 2 shows the statistical indicators for the various calibration and validation models used. Four regression models were developed: raw spectra, SNV, 1 st derivative and SNV + 1 st derivative. After observing the statistical indicators, it was decided to choose the raw spectra for presenting the best indicators: NDF (R\({}^{2}\) of 0.73; RMSE of 3.302 for calibration model and R\({}^{2}\) of 0.69; RMSE of 3.628; Bias of 0.056 and RPD of 1.75 for internal validation model) and CP parameters (R\({}^{2}\) of 0.51; RMSE of 2.073 for calibration model and R\({}^{2}\) of 0.36; RMSE of 2.368; Bias of 0 and RPD of 1.26 for internal validation model).  
Figure 4 represents an example of pasture spectra measured directly with the micro-NIR sensor. These spectra are the starting point for the prediction of pasture NDF and CP content. As can be seen in Figure 4, the wavelength varies between 1093 nm and 1657 nm.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Date** & **Field Code** & **N** & \multicolumn{2}{c}{**FDN \%**} & \multicolumn{2}{c}{**CP \%**} \\ \hline  & & & **Mean \(\pm\) SD** & **Range** & **Mean \(\pm\) SD** & **Range** \\ \hline
30/03/2021 & Mitra A & 12 & 40.7 \(\pm\) 2.0 & 38.8–45.5 & 16.9 \(\pm\) 2.6 & 14.2–20.9 \\ \hline
30/03/2021 & Mitra B & 12 & 41.0 \(\pm\) 2.7 & 37.6–46.8 & 11.6 \(\pm\) 1.6 & 11.0–15.1 \\ \hline
01/04/2021 & Mitra C & 24 & 43.2 \(\pm\) 4.8 & 33.0–51.5 & 11.9 \(\pm\) 2.1 & 8.2–17.2 \\ \hline
08/04/2021 & Azinhal & 8 & 56.5 \(\pm\) 1.4 & 53.7–57.1 & 8.5 \(\pm\) 0.3 & 8.2–8.9 \\ \hline
08/04/2021 & Grous & 8 & 46.8 \(\pm\) 2.9 & 42.4–49.8 & 11.4 \(\pm\) 0.8 & 10.6–12.9 \\ \hline
09/04/2021 & Murteiras & 8 & 49.4 \(\pm\) 2.7 & 46.4–54.5 & 13.3 \(\pm\) 1.6 & 10.4–15.0 \\ \hline
09/04/2021 & Padres & 8 & 52.8 \(\pm\) 2.9 & 46.9–54.5 & 13.7 \(\pm\) 1.2 & 12.4–14.9 \\ \hline
13/04/2021 & Tapada dos Números & 8 & 56.9 \(\pm\) 2.0 & 52.7–58.6 & 12.1 \(\pm\) 2.2 & 11.2–16.3 \\ \hline \end{tabular}
\end{table}
Table 1: Date collection, field code, mean, standard deviation (SD) and range of the pasture NDF and CP reference values.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Pre\_Processing** & \multicolumn{2}{c}{**Calibration Model**} & \multicolumn{4}{c}{**Internal Validation Model**} \\ \hline
**NDF** & **LV** & **R\({}^{2}\)** & **RMSE** & **LV** & **R\({}^{2}\)** & **RMSE** & **Bias** & **RPD** \\ \hline raw spectra & 5 & 0.730 & 3.302 & 5 & 0.690 & 3.628 & 0.056 & 1.75 \\ \hline SNV & 5 & 0.639 & 3.996 & 5 & 0.473 & 4.962 & \(-\)0.279 & 1.35 \\ \hline
1 st derivative & 5 & 0.745 & 3.142 & 5 & 0.649 & 3.834 & \(-\)0.024 & 1.64 \\ \hline SNV + 1 st derivative & 6 & 0.693 & 3.371 & 6 & 0.496 & 4.26 & 0.098 & 1.44 \\ \hline
**CP** & & & & & & & \\ \hline raw spectra & 5 & 0.510 & 2.073 & 5 & 0.360 & 2.368 & 0.000 & 1.26 \\ \hline SNV & 4 & 0.405 & 2.450 & 4 & 0.299 & 2.690 & 0.008 & 1.36 \\ \hline
1 st derivative & 3 & 0.309 & 2.378 & 3 & 0.200 & 2.584 & 0.001 & 1.36 \\ \hline SNV + 1 st derivative & 2 & 0.325 & 2.506 & 2 & 0.263 & 2.722 & 0.079 & 1.13 \\ \hline \end{tabular}
\end{table}
Table 2: Statistical indicators of the internal calibration and validation models for the NDF and the CP through the use of the micro NIR sensor in the pasture and partial least squares regression (PLSR).  
Figure 5 shows the reference and predicted values of NDF (a) and CP (b) resulting from the calibration and validation models. The calibration and validation points for the NDF are relatively close to each other, which means that the models can be considered good (R\({}^{2}\) of 0.71 for calibration and 0.69 for validation). As for the CP, the calibration and validation points do not fit so well, which is a reflection of the R\({}^{2}\) values of the calibration and validation models (0.51 and 0.36, respectively).  
Figure 4: Example of pasture spectra measured with the micro-NIR sensor to predict pasture neutral detergent fibre (NDF) and crude protein (CP).  
Figure 5: _Cont._