High Speed Simultaneous Analysis of Amino Acids in Foods Using Automatic Pretreatment Function

Significance of the Topic

Amino acid profiling is essential for assessing nutritional value, flavor development and quality control in food products. Rapid and reliable analysis methods support regulatory compliance and product innovation in the food industry.

Objectives and Study Overview

This work demonstrates a high-speed simultaneous analysis of 20 proteinogenic amino acids in diverse food matrices using an automated pre-column derivatization function. The goal is to simplify sample preparation, reduce analysis time and ensure robustness against matrix effects.

Used Instrumentation

• Nexera XR Ultra High Performance Liquid Chromatograph with automatic pretreatment module
• Shim-pack XR-ODS II column (100 mm × 3.0 mm I.D., 2.2 µm)
• Fluorescence detector (Ex/Em channels at 350/450 nm and 266/305 nm)
• Autosampler with programmable mixing and reaction delay

Methodology and Experimental Procedures

A pre-column derivatization scheme was implemented entirely within the autosampler needle. Key steps include:

• Dilution of sample with 10 mmol/L HCl and filtration or ultrafiltration as needed for each food type
• Sequential addition of borate buffer, mercaptopropionic acid (MPA) and OPA reagents to generate the fluorescent derivative
• Mixing with FMOC reagent for secondary labeling of selected amino acids
• Two-minute reaction delay before injection to ensure complete derivatization
• Low-pressure gradient elution using three mobile phases (acetate buffer pH 6, water/acetonitrile and acetate buffer pH 5 with EDTA)

Main Results and Discussion

The method achieved baseline separation of 20 amino acids in approximately 14 minutes. Representative chromatograms for standards and food samples—including mirin, beer, dried bonito broth, cricket powder, ketchup, Worcestershire sauce, soy meat and chicken—showed clear peak resolution. Spike-and-recovery tests yielded recoveries close to 100% for most amino acids, confirming minimal interference from complex food matrices.

The automated derivatization function eliminated manual reagent handling, reduced variability and improved throughput compared to traditional post-column approaches. The dual-channel fluorescence detection accommodated early and late-eluting derivatives with high sensitivity.

Benefits and Practical Applications

• Analysis time reduced by more than 50% relative to common post-column methods
• Fully automated derivatization simplifies routine operation and training
• High accuracy and reproducibility across a range of food samples
• Standard HPLC configuration suffices, lowering equipment investment and maintenance

Future Trends and Potential Applications

Advances in reagent chemistries may further shorten reaction times and expand analyte coverage. Integration with mass spectrometric detection could improve selectivity and enable isotope-labeled quantitation. Miniaturized flow cells and lab-on-a-chip platforms may increase throughput for high-volume testing. Machine learning driven data analysis could streamline interpretation and support predictive quality control.

Conclusion

The automatic pre-column derivatization method on the Nexera XR enables fast, accurate and robust amino acid analysis in complex food matrices. By automating sample pretreatment and using a simple HPLC setup, laboratories can achieve high throughput with minimal manual effort.