Literature DB >> 32220138

A rapid sample preparation method for the analysis of stable isotope ratios of beef samples from different countries.

Shanshan Zhao1,2, Hongbo Zhang3, Bin Zhang4, Zhenzhen Xu1,2, Ailiang Chen1,2, Yan Zhao1,2.   

Abstract

RATIONALE: The use of multi-isotopic analyses to trace beef is gaining wider acceptance, but no uniform standard for the pretreatment method is available for the determination of stable isotope ratios. Drying and defatting of meat samples are usually applied. Thus, a rapid sample preparation procedure is required to provide a reference for the study of beef using stable isotope methods.
METHODS: Student's t-test (T-test) was used to determine significant differences between the δ13 C and δ15 N values in traditional and rapid beef sample preparation methods. The δ13 C, δ15 N, δ2 H, and δ18 O values of beef samples from six countries were assayed using elemental analyzer-isotope ratio mass spectrometry. Stable isotope data were subjected to principal component analysis, discriminant analysis, and partial least-squares discriminant analysis (PLS-DA).
RESULTS: There was no significant difference (P > 0.05) between the δ13 C and δ15 N values of the two preparation approaches. A classification of satisfactory was obtained with the original-validation rate of 96.6% and the cross-validation rate of 95.9%. The PLS-DA model was correctly validated to differentiate beef samples from six countries.
CONCLUSIONS: We describe a rapid sample preparation method for beef samples. A model combining stable isotope data and chemometric methods correctly assigned the origin of beef samples from different countries. The results demonstrated the successful utilization of rapid pretreatment methods to prepare beef samples when using multiple stable isotope analyses to trace beef samples from different countries.
© 2020 John Wiley & Sons, Ltd.

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Year:  2020        PMID: 32220138     DOI: 10.1002/rcm.8795

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  2 in total

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