A rapid quantitative method for determining glucose and fructose in honey using APSGS/GO/AuNPs SERS materials combined with machine learning

Key Points

• Quantitative analysis shows significant accuracy in detecting glucose and fructose levels using SERS.
• The method achieves up to 95% accuracy, demonstrating the potential for rapid analysis in food quality assessment.
• Assessment using surface-enhanced Raman spectroscopy combined with machine learning algorithms facilitates testing.
• This study highlights the need for efficient and rapid methods for assessing honey quality and composition.