## 3 Results and Discussion
### Comparison of Different Spectral Regions  
The 173 raw spectra and preprocessed spectra from the calibration set are presented in Figure 2. There was a significant baseline shift in the raw spectra, and peaks associated with concentration changes could not be directly observed. After the first derivative and SNV preprocessing, the baseline shift was removed, and the spectral signal-noise-ratio was promoted. The spectral intensity of 100-500 cm\({}^{-1}\) and 3000-3425 cm\({}^{-1}\) changes greatly. There are some small peaks during 500-3000 cm\({}^{-1}\), and the intensity change is relatively small. In fact, the regions with a wavenumber less than 1800 are all Raman fingerprint regions, the regions with a wavenumber of 1800-2800 are Raman-silent regions, and those with a wavenumber of 2800-3100 are C-H stretching regions [52; 53]. It is difficult to choose the spectral regions for modeling directly from the spectra, and the judgment is subjective. Models were constructed using various spectral regions, as outlined in Figure 1. The obtained RMSECV is depicted in Figure 3. The RMSECV obtained by the whole range of spectra (FP20 and CH56 was used for modeling) for Gluc, Lac, VCD, and NH\({}_{4}\)\({}^{+}\) was 0.31 g/L, 0.13 g/L, 0.64 \(\times\) 10\({}^{6}\) cells/mL, and 1.15 mmol/L, respectively. Most of spectral regions selected in this study could effectively improve the prediction accuracy of Raman-based models, and the RMSECV was significantly reduced. However, spectral regions larger than 3200 cm\({}^{-1}\) may contain a large amount of noise, so the RMSECV is obtained using CH55 or CH56 larger. For Gluc, VCD, and NH\({}_{4}\)\({}^{+}\), when modeling with FP6-FP9, the obtained RMSECV is small; when modeling with FP10-FP20, the RMSECV is large, indicating that the regions of wavenumber <200 and 1800-2800 cm\({}^{-1}\) do not contain chemical information about Gluc, VCD, and NH\({}_{4}\)\({}^{+}\). The information involving molecular \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Component (Unit)**} & \multicolumn{3}{c}{**Batches 1–15**} & \multicolumn{3}{c}{**Batch 16**} \\ \cline{2-7}  & **n** & **Range** & **Mean \(\pm\) SD** & **n** & **Range** & **Mean \(\pm\) SD** \\ \hline Gluc (g/L) & 173 & 1.50–4.18 & 2.42 \(\pm\) 0.61 & 13 & 1.61–4.17 & 2.49 \(\pm\) 0.68 \\ Lac (g/L) & 168 & 0.13–1.51 & 0.54 \(\pm\) 0.36 & 13 & 0.18–0.78 & 0.35 \(\pm\) 0.20 \\ VCD (\(\times 10^{6}\) cells/mL) & 173 & 0.60–6.40 & 4.57 \(\pm\) 1.59 & 13 & 0.75–6.06 & 4.65 \(\pm\) 1.61 \\ NH\({}_{4}\)\({}^{+}\) (mmol/L) & 169 & 2.67–15.39 & 9.91 \(\pm\) 3.50 & 13 & 3.28–14.83 & 10.94 \(\pm\) 4.14 \\ \hline \hline \end{tabular} n represents data size, and SD represents standard deviation.  
\end{table} 
Table 2: The number and concentration information of the collected samples for glucose, lactate, viable cell density, and ammonium ion. structure change is mostly contained in the spectral region of 200-1800 cm\({}^{-1}\). On the contrary, for Lac, the addition of regions smaller than 200 cm\({}^{-1}\) and Raman-silent regions (1800-2800 cm\({}^{-1}\)) improved the model performance. For Gluc and NH\({}_{4}\)\({}^{+}\), the addition of the C-H stretching region improved the prediction accuracy of the Raman-based model to a certain extent. However, for VCD, the addition of C-H stretching regions degraded the model's performance. The optimal model for Gluc, Lac, VCD, and NH\({}_{4}\)\({}^{+}\) was obtained when FP8 plus CHSO, FP17 plus CHSO, FP8 plus CHSO, and FP5 plus CHS2 were used for modeling, respectively, and the corresponding RMSECV was 0.18 g/L, 0.075 g/L, 0.39 \(\times\) 10\({}^{6}\) cells/mL, and 0.79 mmol/L. Figure 3: Model cross-validation results using different spectral regions. (**A**) Glucose, (**B**) lactate, (**C**) viable cell density, and (**D**) ammonium ion. The darker blue represents the larger RMSECV. Figure 2: Raw spectra (**A**) and spectra preprocessed by first derivative and SNV (**B**). Color changes from yellow to blue represent the beginning to the end of cell culture.