Data-Driven Monitoring of Probiotic Fermentation in Fruit Juices Using Near-Infrared Spectroscopy and Aquaphotomics:...

Area of Science:

• Food Science and Technology
• Biotechnology
• Analytical Chemistry

Background:

• Functional foods fortified with probiotics offer nutritional benefits but face challenges in maintaining probiotic viability during processing due to pH fluctuations.
• Accurate monitoring of probiotic activity is crucial for ensuring the quality and efficacy of probiotic-rich food products.

Purpose of the Study:

• To investigate near-infrared spectroscopy (NIR) coupled with aquaphotomics as a method for monitoring probiotic fermentation processes.
• To develop a correlative analytical method for tracking fermentation times and predicting key parameters like pH and cell count.

Main Methods:

• Utilized near-infrared spectroscopy (NIR) in the 1300-1600 nm range to analyze absorption patterns of bound water (aquaphotomics).
• Applied Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) for classification of fermentation times.
• Employed Partial Least Squares Regression (PLSR) for predicting pH and log cell count (CFU/mL).

Main Results:

• PCA-LDA achieved high classification accuracies (99-100% calibration, 99-93% validation) for discriminating fermentation times of bacterial groups.
• PLSR models for pH prediction showed strong validation coefficients of determination (0.96-1) and low root mean square errors (0.05-0.19).
• PLSR model for log cell count (CFU/mL) demonstrated a good coefficient of determination (0.85) and a root mean square error of 0.23.

Conclusions:

• The combination of NIR spectroscopy and aquaphotomics is a viable and accurate bioprocess monitoring tool for probiotic fermentation.
• This approach can be applied in various industrial settings to ensure probiotic survival and product quality.
• The method offers a non-destructive and efficient way to track critical fermentation parameters.