## 4 Discussion
### PLS and SVM Model Analysis  
The RMSEV wavelength ranges smaller than the average RMSEV value in Figure 4 were used to identify EW regions for FWC in the mixture samples, while wavelengths with RMSEV values less than the average RMSEV value were considered to be unnecessary. Thus, only 50% of the entire spectrum included meaningful FWC spectral features and could be used for FWC prediction in the mixture samples.  
In Figure 3, the lipid component affected the LS-SVM model in the 600- to 700-nm region; this feature is also apparent for the PLS beta coefficients. That is, in Figure 5, all wavelengths except those in the 600- to 700-nm region almost evenly affected the performance of the developed PLS model; therefore, this region would have a relatively large impact on the PLS model performance.  
Figure 7: FWC visualization in mixture samples and images produced by LS-SVM model.  
In Table 2, among the preprocessing methods, the range normalization method was selected as the optimal. This approach did not produce the highest coefficient of determination values for calibration and prediction (\(R_{c}^{2}=0.87\) and \(R_{p}^{2}=0.83\), respectively) or the lowest SEC (7.44%) and SEP (8.46%) values compared with the SGD method (\(R_{c}^{2}=0.99\), \(R_{p}^{2}=0.83\), SEC = 2.26%, and SEP = 8.34%), the balance of the two coefficients of determination exceeded that of the SGD method because the ideal ratio of calculation to prediction values is 1 [33] for optimal model selection.  
The \(R_{p}^{2}\) of 0.83 obtained in this work is lower than those of the authors' previous studies based on HSI techniques for foreign particle detection in powder materials [22] and food deterioration evaluation [27; 32; 33]. This low coefficient of determination may have been caused by the relationship between the particle size and the wavelength of the illumination employed in this work.  
The disadvantage of the HSI technique is its low penetration depth, which occurs because of the scattering effects of photons on the specimen surface. In general, the average penetration depth depends on the imaging wavelength; the longer the wave, the deeper the penetration [39]. The penetration depth of Vis/NIR sensing is typically less than a millimeter [40], and the Vis/NIR region of this study was selected because of its color pigment selectivity for FWC detection. However, although the mixture samples containing FW particles used for this experiment were well-mixed, the FW particles may have been located toward the bottom or middle of the sample holders (3 mm). Thus, the model accuracy may have been affected by the FW particle positions. In future work, FWC particle sizes, according to penetration depth, will be investigated with application of different models in order to develop more precise prediction systems.  
In powdered materials, the detection performance tends to decrease simultaneously with the target particle size [41]. The FWC particle sizes of this work were tens to hundreds of micrometers, whereas the other OF particle sizes ranged from 5 to 0.1 mm. Therefore, the model prediction accuracy gradually decreased with increased FWC concentration in the mixture samples, as shown in Figure 6. To improve the model performance, the sample holder height and the particle size should be controlled according to the light source and target particle size.