A simple method for water discrimination based on an light emitting diode (LED) photometer

Area of Science:

• Analytical Chemistry
• Environmental Science

Background:

• Mineral water quality and authenticity are crucial consumer concerns.
• Accurate discrimination of water sources is essential for quality control and regulatory purposes.

Purpose of the Study:

• To develop and validate a simple, cost-effective method for discriminating between different mineral water samples.
• To utilize a multi-LED photometer combined with chromogenic reagents and chemometric analysis for water classification.

Main Methods:

• Analysis of 45 water samples using a monosegmented flow system and three chromogenic reagents (murexide, PAR, eriochrome black T).
• Spectrophotometric measurements at multiple wavelengths (470-654 nm).
• Application of Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and SIMCA modeling for data interpretation and classification.

Main Results:

• Optimal discrimination achieved using murexide and eriochrome black T reagents, distinguishing 9 water groups.
• Reduced wavelength set (470, 500, 590, 654 nm) with four LEDs provided similar discrimination.
• SIMCA model achieved 94% correct sample classification, primarily based on calcium and magnesium ion content.

Conclusions:

• The developed method offers a straightforward and efficient approach for mineral water discrimination.
• Multi-LED photometry coupled with chemometrics provides a powerful tool for water quality assessment.
• The method's effectiveness relies on the differential metal ion profiles (Ca2+, Mg2+) in various water samples.