Predicting Freezing Point of Ice Cream Mix with Infrared Spectroscopy and Chemometrics

Area of Science:

• Dairy Science
• Analytical Chemistry
• Food Science

Background:

• Fourier transform infrared spectroscopy (FTIR) is a rapid, non-destructive technique valuable in the dairy industry.
• Determining the freezing point (FP) of ice cream mix (ICM) is crucial for quality but traditional methods are laborious, especially for high-solids dairy.

Purpose of the Study:

• To evaluate the feasibility of using FTIR spectroscopy with chemometric modeling to predict the freezing point of ice cream mix.
• To explore FTIR as a rapid alternative to traditional freezing point determination methods.

Main Methods:

• Fourier transform infrared spectroscopy (FTIR) was used to collect spectral data from ice cream mix samples.
• Partial least squares (PLS) regression models were developed to correlate FTIR spectral data with freezing point values obtained via a cryoscopic method.

Main Results:

• FTIR spectra contained information related to variations in freezing point.
• The predictive performance of the developed models was limited, indicating challenges in accurately predicting FP.
• Model accuracy was constrained by the complex nature of FP as a colligative property and dataset limitations (compositional range, sample size).

Conclusions:

• FTIR spectroscopy shows promise as a rapid screening tool for estimating the freezing point of ice cream mix.
• Further research with larger, more diverse datasets and refined reference methods is needed to improve model accuracy.
• This study provides a foundation for advancing FTIR-based methods in dairy product quality assessment.