Xiong Cen, Su Zhiyi, Zhezng Yanjie, Wang Qi, Ling Yejing, Liu Zhongdong, Li Yongle, Zhang Jingru, Yang Guowu, Zhang Xieguang
Shenzhen Academy of Metrology and Quality Inspection, Food Testing Institute, Shenzhen 518131, People's Republic of China.
Henan University of Technology, College of Food Science and Technology, Zhengzhou, Henan 450001, People's Republic of China.
J AOAC Int. 2017 Mar 1;100(2):503-509. doi: 10.5740/jaoacint.16-0228. Epub 2016 Dec 9.
The pyrolysis (Py)-GC-MS technique was first introduced for the identification of two kinds of Chinese geographical indication vinegars because its advantages are that it is a simple and convenient sample pretreatment and inlet method. Abundant Py information about vinegars was obtained using Py-GC-MS; 21 common peaks were selected. With the help of the classical partial least-squares (PLS) modeling method for data analysis, two identification models for Shanxi extra-aged (SX) and Zhenjiang (ZJ) vinegars were established, respectively. An N-reducing method was used to select the variables. The variables were reduced one at a time to build the PLS models with the lowest number of misjudgments. Both models had good recognition rates, identifying over 90% of samples correctly. Thus, combining Py-GC-MS and PLS could be regarded as an effective method for the identification of SX and ZJ vinegars.
热解（Py）-气相色谱-质谱联用技术首次被用于两种中国地理标志食醋的鉴定，因为它的优点在于其是一种简单便捷的样品预处理和进样方法。使用Py-气相色谱-质谱联用技术获得了关于食醋丰富的热解信息；选取了21个常见峰。借助经典的偏最小二乘法（PLS）建模方法进行数据分析，分别建立了山西老陈醋（SX）和镇江（ZJ）香醋的两种鉴定模型。采用一种N-约简方法来选择变量。每次减少一个变量以构建误判数量最少的PLS模型。两种模型都具有良好的识别率，能正确识别超过90%的样品。因此，将Py-气相色谱-质谱联用技术和PLS相结合可被视为鉴定SX和ZJ香醋的有效方法。
