Predicting Satiety from the Analysis of Human Saliva Using Mid-Infrared Spectroscopy Combined with Chemometrics
Dongdong Ni1, Heather E Smyth1, Michael J Gidley1
1Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD 4072, Australia.
Foods (Basel, Switzerland)
|March 10, 2022
Summary
Mid-infrared spectroscopy of saliva shows potential for predicting satiety perception. While quantitative prediction was not robust, it successfully identified individuals with low or high satiety, aiding appetite study participant selection.
Area of Science:
- Biochemistry
- Spectroscopy
- Chemometrics
Background:
- Satiety prediction is crucial for understanding appetite regulation and human-food interactions.
- Non-invasive methods for assessing satiety are highly desirable in research and clinical settings.
Purpose of the Study:
- To evaluate mid-infrared (MIR) spectroscopy and chemometrics for analyzing unstimulated saliva to predict satiety in healthy individuals.
- To identify salivary features related to individual perceptions of human-food interactions.
- To assess the potential for classifying participants into low or high satiety perception groups.
Main Methods:
- Unstimulated saliva samples were analyzed using mid-infrared (MIR) spectroscopy.
- Chemometric methods, including partial least squares discriminant analysis (PLS-DA), were employed for data analysis.
- Spectra were analyzed for specific frequency ratios related to biochemical components like proteins, amino acids, and chlorides.
Main Results:
- A correlation between saliva composition and satiety was observed, but quantitative prediction of satiety using all saliva samples was not robust (R 2 = 0.62).
- Significant differences in MIR spectral ratios were found between low and high satiety groups, particularly for total protein, α-amino acids, and chlorides.
- A qualitative model using PLS-DA successfully predicted low or high satiety perception types with high accuracy (R 2 = 0.92), enabling participant classification for appetite studies.
Conclusions:
- MIR spectroscopy combined with chemometrics offers a promising, rapid, and cost-effective tool for qualitatively assessing satiety perception types.
- This method can be utilized to identify individuals with distinct satiety perceptions, facilitating participant selection for appetite and human-food interaction studies.
- Further research may refine quantitative prediction models and explore broader applications in understanding human-food interactions.
