食品科学 ›› 2020, Vol. 41 ›› Issue (6): 316-321.doi: 10.7506/spkx1002-6630-20190218-097

• 安全检测 • 上一篇    下一篇

基于矿物元素指纹差异的不同产地滩羊肉判别

马梦斌,罗瑞明,李亚蕾   

  1. (宁夏大学农学院,宁夏 银川 750021)
  • 出版日期:2020-03-25 发布日期:2020-03-23
  • 基金资助:
    宁夏回族自治区重点研发计划项目(2017BY068)

Discrimination of Different Geographical Origins of Tan Sheep Meat Based on Mineral Element Fingerprints

MA Mengbin, LUO Ruiming, LI Yalei   

  1. (School of Agricultural, Ningxia University, Yinchuan 750021, China)
  • Online:2020-03-25 Published:2020-03-23

摘要: 通过分析不同地域滩羊肉中矿物质元素含量差异,结合多元统计分析,筛选出有效的溯源指标,构建用于原产地鉴别的判别模型。采用电感耦合等离子质谱技术测定宁夏盐池县、内蒙古自治区鄂托克前旗、陕西省定边县和甘肃省环县滩羊背最长肌样品中25 种矿物质元素含量,对采样地区样品中的矿物质元素含量进行方差分析、主成分分析及线性判别分析,建立判别模型并验证。结果显示,滩羊肉样品中测定的25 种矿物质元素其中17 种矿物质元素含量在不同地域间存在显著差异,主成分1主要由Cr、Mn、Ni、Cu、Se和Rb 6 种元素构成,判别贡献率最大,为26.403%;主成分2主要由K、P、Fe和Sn 4 种元素构成,贡献率为22.285%。通过逐步判别分析筛选出Ca、P、Cr、Mn、Ni、Cu、Se、Rb、Mo和Sn 10 项元素指标建立滩羊肉产地判别模型,所建立的模型对滩羊肉产地判别整体正确率均为100%,模型对不同产地滩羊肉的区分判别准确。因此,基于矿物元素指纹的判别可以有效鉴别不同产地滩羊肉。

关键词: 滩羊肉, 矿物元素, 指纹, 产地, 溯源

Abstract: The geographical traceability indicators were selected by analysis of the differences in mineral element contents of Tan sheep meat of different geographical origins and multivariate statistical analysis to construct a discriminant model for the identification of the geographic origin of mutton. Inductively coupled plasma-mass spectrometry was used to determine the contents of 25 mineral elements in the Longissimus dorsi muscle of Tan sheep from Yanchi county of Ningxia, Etuokeqian banner of Inner Mongolia autonomous region, Dingbian county of Shanxi province and Huanxian county of Gansu province. Analysis of variance, principal component analysis and linear discriminant analysis were carried out to develop and validate the discriminant model. The results showed that the contents of 17 of the 25 mineral elements in mutton were significantly different among growing regions. The principal component 1 was mainly composed of six elements: Cr, Mn, Ni, Cu, Se and Rb, with the highest discriminant contribution rate of 26.403%; the principal component 2 was mainly composed of four elements of K, P, Fe and Sn, with contribution rate of 22.285%. Through the stepwise discriminant analysis, Ca, P, Cr, Mn, Ni, Cu, Se, Rb, Mo and Sn were selected for modeling. The overall correct discrimination rate for the geographical origins of mutton was 100%, suggesting the model could accurately distinguish Tan sheep meat from different producing areas. Therefore, discrimination based on mineral element fingerprints can effectively identify Tan sheep meat from different producing areas.

Key words: Tan sheep meat, mineral element, fingerprint, geographical origin, traceability

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