The concentration of trans-4-hydroxy-l-proline has been traditionally employed as an estimate of collagen content in meat to assess meat quality. Conventional methods use chemical derivatization followed by UV–visible detection. However, complexity of the matrix may cause interferences due to lack of specificity and consequently bias quantification. On the contrary, liquid chromatography (LC) separation coupled to mass spectrometry (MS) detection overcomes these limitations, giving more accurate results. This study describes the development and validation of an exact matching-isotopic dilution mass spectrometry method for the determination of hydroxyproline in meat hydrolysates in the certification of a candidate meat reference material (CRM LGC7154). The method is not biased by changes in method conditions or by matrix load. Hydroxyproline concentrations and relative uncertainties for quality control samples revealed good agreement with the certified values. A mean hydroxyproline concentration of 1.78 ± 0.28 g/kg (k = 2) was found for the CRM LGC 7154 material.
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The work described here was funded by the Business, Innovation and Skills (BIS). The authors would like to thank Hayley Forbes for her help in the sample preparation and Philip Wilson for the support in the statistical analysis.
Conflict of Interest
Author Camilla Liscio declares that she has no conflict of interest. Author Christopher Hopley declares that he has no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
• Colorimetric method is fit for the purpose but can be biased by matrix complexity
• LC-MS approach can overcome limitations giving accurate results
• An EM-IDMS-LC-MS method for hydroxyproline in meat hydrolysates was developed
• Validated method was robust and unbiased by condition changes in or matrix load
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Liscio, C., Hopley, C. Development of a Reference Measurement Procedure and Certified Reference Material for the Determination of Hydroxyproline in Meat. Food Anal. Methods 9, 1461–1469 (2016). https://doi.org/10.1007/s12161-015-0329-x