An LC-Orbitrap-MS Based Non-targeted Metabolomics Approach for Investigation of Honey Adulteration

Importance of the Topic

Honey is widely consumed and vulnerable to adulteration due to its high economic value and health implications. Detecting added sugar syrups in honey is critical to ensure product authenticity and consumer safety.

Objectives and Study Overview

The study aimed to develop a rapid dilute and shoot non-targeted metabolomics workflow using high resolution accurate mass LC Orbitrap MS to screen honey samples. Six market samples were analyzed with both reverse phase and HILIC chromatography to detect native and adulterant markers.

Methodology and Instrumentation

Sample preparation involved simple dilution in water and methanol followed by centrifugation. Analysis was carried out on a Thermo Scientific Vanquish Flex UHPLC system using a C18 reverse phase column and an Accucore amide HILIC column with tailored gradients. Mass spectrometry was performed on an Exploris Orbitrap 240 in full scan data dependent MS2 mode at 240000 resolution. Data processing and non-targeted screening were conducted using Compound Discoverer software with accurate mass, retention time alignment, and spectral library matching.

Key Results and Discussion

• Detected over 200 metabolites in honey with mass accuracy below 5 ppm
• HILIC method identified 97 polar compounds including oligosaccharides and polysaccharides
• Reverse phase method detected 75 compounds in positive mode and 46 in negative mode, covering amino acids and polyphenols
• Negative polarity enhanced naringenin signal by fourfold; varying resolution between 60000 and 240000 had minimal impact on sensitivity
• PCA clearly separated four samples with elevated DP6 and DP16 sugar markers as adulterated
• High resolution acquisition delivered over 15 scans per chromatographic peak, supporting reliable quantitation

Benefits and Practical Applications

This fit-for-purpose workflow combines two chromatographic modes to achieve broad metabolite coverage in honey. The dilute and shoot approach reduces sample prep time and increases throughput. High resolution accurate mass data and non-targeted screening enable retrospective data mining and robust statistical differentiation between genuine and adulterated samples.

Future Trends and Applications

• Incorporation of additional separation techniques such as ion mobility to expand metabolite coverage
• Development of machine learning models for automated adulteration detection and classification
• Retrospective mining of existing data for emerging adulterants
• Adaptation of workflows to portable high resolution MS for on-site testing
• Standardization of non-targeted metabolomics methods for regulatory quality control in food authenticity

Conclusion

The non-targeted LC-Orbitrap MS strategy offers comprehensive detection of honey metabolites and adulterants with high confidence. Combining reverse phase and HILIC analysis delivers over 200 analytes, while high resolution data enables clear compound identification and statistical discrimination. This approach strengthens honey authentication protocols and supports regulatory compliance.

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