Pomegranate molasses authentication using hyperspectral imaging system coupled with automatic clustering algorithm

Area of Science:

• Food Science
• Analytical Chemistry
• Spectroscopy

Background:

• Pomegranate molasses, a concentrated juice product, faces adulteration risks due to its value and cost.
• Date syrup is a common adulterant, impacting product authenticity and quality.

Purpose of the Study:

• To differentiate authentic pomegranate molasses from adulterated samples.
• To evaluate the effectiveness of hyperspectral imaging (HSI) for detecting date syrup adulteration.
• To compare HSI with traditional physicochemical methods for authenticity analysis.

Main Methods:

• Physicochemical analysis of 24 samples (brix, sucrose, acidity, ash, pH, formalin index).
• Hyperspectral imaging (HSI) system (400-1000 nm) for spectral data acquisition.
• Evolutionary wavelength selection, principal component analysis (PCA), and artificial bee colony (ABC) algorithm for data analysis and clustering.

Main Results:

• The formalin index proved effective for evaluating pomegranate molasses authenticity.
• HSI successfully captured spectral data for sample analysis.
• The developed HSI coupled with an unsupervised ABC clustering algorithm accurately detected date syrup adulteration from 5% levels.

Conclusions:

• Hyperspectral imaging offers a rapid, non-destructive method for pomegranate molasses authenticity assessment.
• The combination of HSI and advanced clustering algorithms provides a reliable tool for detecting adulteration.
• This approach can safeguard product integrity and consumer trust in pomegranate molasses.