Quality control of honey with NIR spectroscopy

Importance of the Topic

Honey is a natural product whose quality depends primarily on its sugar composition and color characteristics. Traditional methods for sugar analysis, such as HPLC, require lengthy sample preparation, solvents, and skilled operators. Rapid, non-destructive techniques are needed in industrial and quality-control laboratories to streamline workflow and reduce costs.

Objectives and Study Overview

This application note demonstrates a near-infrared spectroscopy (NIRS) approach for simultaneous quantification of major sugars (glucose, fructose, sucrose, maltose, turanose) and color assessment in honey. The goal is to establish robust calibration models that deliver results in seconds without sample preparation.

Methodology

Honey samples were analyzed in transflection mode over the spectral range of 1000 to 2250 nm. Reference concentrations for sugars were determined by high-performance liquid chromatography (HPLC), while color was measured on the Pfund scale using a colorimeter. Calibration and validation sets were used to develop prediction models for each parameter.

Instrumentation

Analysis was performed on the OMNIS NIR Analyzer Solid equipped with a 2 mm gap transflection reflector and 28 mm disposable vials. OMNIS Software managed data acquisition and chemometric model building.

Main Results and Discussion

Prediction performance was evaluated by correlation diagrams and figures of merit. Key results include:

• Glucose: R2≈0.78, SEP≈1.5%
• Fructose: R2≈0.53, SEP≈0.6%
• Sucrose: R2≈0.92, SEP≈0.25%
• Maltose: R2≈0.56, SEP≈0.3%
• Turanose: R2≈0.67, SEP≈0.33%
• Color (Pfund): R2≈0.58, SEP≈14.6 mm

Models showed high accuracy for sucrose and glucose and moderate performance for other sugars and color, indicating the potential for rapid screening.

Benefits and Practical Applications

NIRS enables:

• Simultaneous multi-parameter analysis in under 10 seconds
• No chemical reagents or sample preparation
• Reduced analysis costs and waste
• Ease of use, requiring minimal operator training

Future Trends and Applications

Advancements in instrument sensitivity and chemometric methods may further improve prediction accuracy for minor sugars and color. Integration with automated sampling and machine-learning algorithms can expand applications to authenticity testing and process monitoring in the honey industry.

Conclusion

The NIR method provides a fast, solvent-free solution for honey quality control, delivering reliable sugar profiles and color measurements in seconds. This approach optimizes laboratory efficiency and supports real-time decision making.

Reference

1. Kolayli S, Boukraa L, Sahin H, et al. Sugars in Honey. In: Dietary Sugars: Chemistry, Analysis, Function and Effects. 2012:3–15.