# Measurement of Soy Contents in Ground Beef Using Near-Infrared Spectroscopy
## 3 Results and Discussion  
### Spectra Information  
The relationship information between the raw NIR spectra and the mixed soy content classes is shown in Figure 1. The wavelength used here ranged from 400 to 2500 nm for dispersive NIR (Figure 1a) and 1000 to 2500 nm for FT-NIR (Figure 1b).  
As for Figure 1a, the curve patterns resembled each other for the four types of soy protein in the full waveband. However, in the section of the visible and part of the shortwave infrared wavelengths (400-1000 nm), the correlation coefficients showed a poor relationship compared to the rest of the wavebands regardless of soy type. This indicates that spectra between 400 and 1000 nm were less suitable for the prediction of soy contents by dispersive NIR methods. In the majority of the curves, the correlation was negative with a high absolute value (above 0.8) in the region of 1000-2500 nm, indicating that these spectra might provide a better prediction of soy contents. Overall, toasted soy grits showed a generally lower correlation than the other three soy protein types in this region, suggesting that the ability for determining contents quantitatively for toasted soy grits was slightly worse. In the case of Vis/NIR applications, the use of a set of optimal wavelengths that contains the most relevant information is desired [9]. Thus, in this study, a data set of 1000-2500 nm for dispersive NIR spectra was chosen for quantitative analysis. Interestingly enough, the selected spectra were conducive to the same range measured with the FT-NIR method. Figure 1b shows the correlogram between the spectra measured with the FT-NIR instrument and the contents of soy products in the mixtures. The spectral data revealed an obvious relationship with the mixed level by showing a high coefficient of correlation (\(1\,r\,|>0.75\)). Among the four soy products, toasted soy grits again showed the lowest correlation and greatest fluctuation overall. This is similar to the results shown in Figure 1a. In the region of 1000 to 1200 nm, TVP also displayed a slightly poor relationship (\(1\,r\,|<0.8\)) compared with the other types. A similar pattern was also noticed in the same region for dispersive NIR spectra (Figure 1a). Through comparison, it indicates that both NIR methods would provide similar predictions in general.  
Figure 2 shows the average raw NIR spectra of ground beef and soy protein samples measured separately with the dispersive instrument (top) and the FT-NIR instrument (bottom). Due to the effect of the wavelength on the correlation coefficients (poor relationship at a wavelength less than 1000 nm) and for a better comparison between both spectral data sets (only 1000-2500 nm for FT-NIR spectra),  
Figure 1: Correlogram between spectral data and mixed soy content classes of soy products in ground beef. (**a**) Dispersive spectral correlogram; (**b**) FT-NIR spectral correlogram, NIR: near-infrared spectroscopy; FT-NIR: Fourier transform NIR; TVP: textured vegetable protein.  
only the region of 1000 to 2500 nm of the dispersive data was used for the analysis. The difference between the two spectra results from the different operational principle of light splitting by diffraction grating and Michelson interference of the two instruments. The results showed that there was some degree of differences between the two spectra, such as the locations of the absorbance peaks and the absorbance extent at different wavelengths.