Vis-NIR hyperspectral imaging coupled with independent component analysis for saffron authentication.

Area of Science:

• Analytical Chemistry
• Chemometrics
• Spectroscopy

Background:

• Saffron authentication is crucial due to its high value and susceptibility to adulteration.
• Traditional methods for saffron analysis can be time-consuming and lack comprehensive detection capabilities.
• Developing rapid and accurate methods for saffron quality control is essential for the food and pharmaceutical industries.

Purpose of the Study:

• To develop and validate a novel chemometric approach for authenticating saffron using visible-near infrared hyperspectral imaging (Vis-NIR-HSI).
• To detect common plant-derived adulterants in saffron samples.
• To achieve high classification accuracy for both authentic and adulterated saffron.

Main Methods:

• Visible-near infrared hyperspectral imaging (Vis-NIR-HSI) acquisition.
• Mean-field independent component analysis (MF-ICA) for spectral and spatial profile extraction.
• Principal component analysis (PCA) and hierarchical cluster analysis (HCA) for pattern recognition.
• Partial least squares-discriminant analysis (PLS-DA) for supervised classification.
• Data-driven soft independent modeling of class analogy (dd-SIMCA) for model evaluation.

Main Results:

• The proposed Vis-NIR-HSI combined with MF-ICA and multivariate analysis achieved 100% classification accuracy for calibration and prediction sets.
• The method successfully differentiated authentic saffron from five common adulterants: safflower, saffron style, calendula, rubia, and turmeric.
• Sensitivity for the authentic saffron class was 95%, with specificities of 100% for all adulterants.

Conclusions:

• The integrated Vis-NIR-HSI and MF-ICA chemometric approach provides a powerful and accurate tool for saffron authentication and adulteration detection.
• This method offers a reliable solution for quality control, ensuring the integrity of saffron in commercial applications.
• The high accuracy and specificity demonstrate the potential of this technique for routine analysis in the saffron industry.