Institute of Quality Standard & Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Beijing, China.
Key Laboratory of Agro-Product Quality and Safety, Ministry of Agriculture and Rural Affairs, Beijing, China.
Rapid Commun Mass Spectrom. 2020 Jul 15;34(13):e8795. doi: 10.1002/rcm.8795.
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.
Student's t-test (T-test) was used to determine significant differences between the δ C and δ N values in traditional and rapid beef sample preparation methods. The δ C, δ N, δ H, and δ 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).
There was no significant difference (P > 0.05) between the δ C and δ 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.
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.
多同位素分析用于追踪牛肉的方法越来越被广泛接受，但对于稳定同位素比值测定，尚无统一的预处理方法标准。通常应用干燥和脱脂来处理肉样。因此，需要一种快速的样品制备方法，为使用稳定同位素方法研究牛肉提供参考。
采用学生 t 检验（T 检验）比较传统和快速牛肉样品制备方法中 δC 和 δN 值的差异。采用元素分析仪-同位素比质谱法测定来自六个国家的牛肉样品的 δC、δN、δH 和 δO 值。对稳定同位素数据进行主成分分析、判别分析和偏最小二乘判别分析（PLS-DA）。
两种制备方法的 δC 和 δN 值无显著差异（P＞0.05）。原始验证率为 96.6%，交叉验证率为 95.9%，分类效果满意。PLS-DA 模型正确验证了区分来自六个国家的牛肉样品的能力。
本研究描述了一种快速的牛肉样品制备方法。结合稳定同位素数据和化学计量学方法的模型能够正确分配来自不同国家的牛肉样品的来源。结果表明，在使用多稳定同位素分析追踪来自不同国家的牛肉样品时，快速预处理方法可成功用于制备牛肉样品。
