Quantification of Natural Sugars in Baby Food

A PLS algorithm was utilized to establish a calibration curve for each of the three sugar components. It was found that good correlation could be achieved without the use of pre-processing methods such as smoothing, derivatives, or zero corrections. In addition, the use of five factors accounted for all of the noise in the spectra and provided good calibration curves with acceptable R2 values.

To further demonstrate that the use of five factors was appropriate, the P Loadings for each sugar component were examined. As seen from the graphs (Figure 6), the P Loading of the fifth factor resembles a random noise spectrum, suggesting that all of the spectral noise had been accounted for.

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Figure 6: P Loading graphs for each sugar supporting the selection of five factors.

Calibration Validation

Once the calibration curve for each sugar component were established, FTIR spectra were acquired of the verification matrix of samples using the same acquisition parameters as was used for the training matrix.

Results of the verification matrix showed average residuals for each sugar of 0.004 percent and established that the calibration method was valid.

Sugar Component Analysis of Baby Foods

Commercial baby food samples from three major manufactures were acquired for fructose, glucose, and sucrose analysis. The baby foods selected consisted of pureed fruits and vegetables and fruit juices.

FTIR spectra for each baby food were acquired neat without any pretreatment using the HATR accessory and the spectral acquisition parameters noted previously. The fructose, glucose, and sucrose sugar contents were calculated using the calibration established for each sugar from the factor-spaced analysis.

Examination of the calculated residuals from the calibration suggested very good fits with the various sugar calibration curves. Baby foods that were more fruit based appeared to give better residual values, whereas baby foods that were more vegetable based generally gave higher residuals.

A total sugar concentration for each baby food was calculated from the sugar content provided on the nutrition label of each package. The calculated total sugar value from the nutritional label was compared to the total sugar value calculated from the FTIR quantitative spectral analysis. Measured total sugar values showed a high bias when compared to the reported total sugar values for all samples (Figure 7).

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Figure 7: Total measured sugar comparison to that listed on the nutritional labels for each commercial baby food sample.

Conclusion

Commercial baby food samples were analyzed for fructose, glucose, and sucrose sugar content. Residual data from the calibration suggested that the baby food samples were within the calibration algorithm’s area of analysis. A comparison was made of the total sugars measured to those reported on the nutritional labels of the baby food packages.

FTIR Analysis, using a horizontal attenuated total reflection accessory, was demonstrated to be a suitable method to acquire FTIR spectra of commercial baby foods without sample pretreatment or concern for IR water absorption.

Chemometric PLS routines were used to establish and validate calibration curves for fructose, glucose, and sucrose concentrations in aqueous solutions.

This data demonstrates that FTIR analysis of baby foods can offer a quick and efficient means of sugar analysis for QA/QC applications.

Clifford is an intern in the molecular spectroscopy group at Shimadzu Scientific Instruments and can be reached at 410-381-1227, x1822. Head and Dr. Kinyanjui are product specialists in the molecular spectroscopy at Shimadzu and can be reached at [email protected] and [email protected], respectively. Dr. Talbott, the primary contact for correspondence, is molecular spectroscopy product manager at Shimadzu and can be reached at [email protected].