**4. Conclusions**

Results from this study demonstrated the ability of MIR spectroscopy combined with chemometrics (e.g., PLS) to predict satiety from resting (unstimulated) saliva samples. Although quantitative PLS calibration models were not achieved, a qualitative model for the prediction of low and high satiety perception type was obtained using PLS-DA. Furthermore, this study indicated the possibility of evaluating the interactions between saliva and food using MIR spectroscopy as a rapid and cost-effective tool.

**Author Contributions:** D.N., formal analysis, writing—original draft preparation, writing—review and editing; H.E.S., supervision, writing—review and editing; M.J.G., supervision, writing—review and editing; D.C., methodology, formal analysis, writing—original draft preparation, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

**Funding:** Scholarship from the China Scholarship Council and the University of Queensland.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable. **Data Availability Statement:** Not applicable.

**Acknowledgments:** The authors acknowledge funding from Hort Innovation (Australia). Dongdong Ni acknowledges the award of a scholarship from the China Scholarship Council and the University of Queensland. The sensory panel from the Health and Food Sciences Precinct (Coopers Plains, Queensland, Australia) are acknowledged for their dedication and participation in this research.

**Conflicts of Interest:** The authors declare no conflict of interest.
