Development of a New Gradient Elution Program for the Analysis of Amino Acids in Pet Foods and Plant Proteins

Importance of the Topic

In modern pet food and plant protein quality control, precise profiling of amino acids underpins nutritional labeling, contamination screening and process validation. Hydroxyproline, a key marker of collagen-derived ingredients, is absent from many official amino acid methods. Extending established procedures to include this residue supports detection of adulteration, authentication of halal/kosher status and comprehensive nutritional analysis.

Objectives and Study Overview

This work aimed to adapt the AOAC International Official Method 2018.06—based on pre-column derivatization with AQC and UPLC–UV detection—for pet foods and plant proteins by:

• Incorporating hydroxyproline (HyPro) into the target amino acid list
• Modifying the gradient elution program to achieve baseline separation of all analytes
• Validating the optimized method using representative commercial samples

Methodology and Instrumentation

The existing hydrolysis and AQC derivatization steps of AOAC 2018.06 were retained. An analytical Quality by Design (aQbD) approach using Design of Experiments (DoE) guided the optimization of the gradient profile, focusing on critical resolution pairs: Ser/Arg, Asp/MetSO₂, and S-2-carboxyethylthiocysteine/Met. Robustness was assessed via a full factorial design varying column temperature, flow rate and mobile phase composition.

Instrumentation Used:

• ACQUITY Premier UPLC System with Binary Solvent Manager and Fixed Loop Sample Manager
• ACQUITY UPLC BEH C18 or AccQ Tag Ultra C18 Column (2.1×150 mm, 1.7 μm)
• 2998 Photodiode Array Detector at 260 nm
• ACQUITY QDa Mass Detector for peak confirmation (positive ion mode, 100–600 Da)
• Empower 3 CDS and Fusion QbD software for data processing and optimization

Main Results and Discussion

The optimized gradient achieved baseline separation (resolution ≥2.0) of all 24 amino acids, including HyPro. Method specificity was confirmed despite coelution challenges (e.g., Gln/Arg), which do not impact hydrolyzed protein quantification. Repeatability (RSDr) for retention times was below 0.8 % (early eluents) and 0.1 % (late eluents) on a single column. Intermediate reproducibility (RSDiR) remained under 7.7 % for early eluents and 0.8 % for late eluents across columns and days. Limits of quantitation ranged from 0.02 to 0.10 μM and calibration linearity (R² ≥0.9975) matched the original AOAC method. Analysis of six pet foods and four plant protein powders confirmed method applicability and revealed expected HyPro and hydroxylysine in animal-derived feeds; an unexpected hydroxylysine signal in pumpkin seed protein suggested potential contamination.

Benefits and Practical Applications

• Enables inclusion of hydroxyproline as a collagen marker in routine amino acid profiling
• Maintains high sensitivity, linearity and robustness comparable to AOAC 2018.06
• Applicable to both pet nutrition products and plant-based protein ingredients
• Supports regulatory compliance, adulteration screening and nutritional labeling

Future Trends and Applications

Emerging directions include coupling the optimized UPLC–UV method with high-resolution MS for deeper peptide mapping, extending the aQbD framework to other challenging matrices (e.g., insect meal) and automating sample preparation via microwave-assisted hydrolysis. Integration with informatics platforms may further streamline QC workflows and data traceability.

Conclusion

A revised gradient elution program based on AOAC 2018.06 has been successfully developed for comprehensive amino acid analysis in pet foods and plant proteins. The method delivers baseline separation of all amino acids, including hydroxyproline, with excellent repeatability, reproducibility, sensitivity and linearity. Its deployment enhances feed authenticity testing and nutritional quality control.

References

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