基于矿物元素指纹的地理标志羊肉真实性鉴别  

Authenticity Identification of Geographical Indication Mutton Based on Mineral Element Fingerprint

作　　者：齐婧 李莹莹[1] 姜锐 张晨 张顺亮[1] 郭文萍[1] 王守伟[1] QI Jing;LI Yingying;JIANG Rui;ZHANG Chen;ZHANG Shunliang;GUO Wenping;WANG Shouwei(Beijing Key Laboratory of Meat Processing Technology,China Meat Research Center,Beijing 100068,China)

机构地区：[1]中国肉类食品综合研究中心,肉类加工技术北京市重点实验室,北京100068

出　　处：《食品科学》2022年第24期365-370,共6页Food Science

基　　金：北京市博士后科研活动经费资助项目(2017-zz-138)。

摘　　要：探究一种基于矿物元素指纹结合单分类建模策略的地理标志羊肉真实性鉴别技术。结果表明,盐池滩羊、巴里坤哈萨克羊、苏尼特羊3种地理标志羊肉中矿物元素含量均具有指纹特征。采用单分类建模策略,只需收集真实样本集建模,即可在多种欺诈样本中鉴别真实样本。基于3种地理标志羊肉样本分别建立的类类比软独立建模(soft independent modeling of class analogy,SIMCA)模型性能优良,对测试样本的鉴别准确率达到100%。因此,基于矿物元素指纹结合单分类建模(SIMCA)的真实性鉴别技术在地理标志羊肉真实性鉴别领域具有广泛的应用前景。This study proposed a technique for identifying the authenticity of geographic indication mutton based on mineral element fingerprint combined with one-class modeling strategy.The results showed that the contents of mineral elements in the meat of Yanchi Tan sheep,Balikun Kazak sheep and Sunit sheep under the protection of geographical indication had fingerprint characteristics.In the one-class modeling strategy,only real sample sets were collected for modeling to identify the real samples from a variety of fraud samples.The soft independent modeling of class analogy(SIMCA) model based on each of the geographical indication mutton samples had excellent performance,with an identification accuracy of 100% for the test samples.Therefore,mineral element fingerprint combined with one-class modeling has a wide application prospect in the field of authenticity identification of geographical indication mutton.

关 键 词：地理标志 羊肉 矿物元素 单分类建模 类类比软独立建模 真实性鉴别 

分 类 号：TS207.7[轻工技术与工程—食品科学]