Zhang Xufeng, Liu Yu, Li Ying, Zhao Xinda
College of Environmental Science and Engineering, Dalian Maritime University, Dalian, China.
College of Environmental Science and Engineering, Dalian Maritime University, Dalian, China.
Food Chem. 2017 Mar 1;218:269-276. doi: 10.1016/j.foodchem.2016.08.083. Epub 2016 Aug 24.
Geographic traceability is an important issue for food quality and safety control of seafood. In this study,δC and δN values, as well as fatty acid (FA) content of 133 samples of A. japonicus from seven sampling points in northern China Sea were determined to evaluate their applicability in the origin traceability of A. japonicus. Principal component analysis (PCA) and discriminant analysis (DA) were applied to different data sets in order to evaluate their performance in terms of classification or predictive ability. δC and δN values could effectively discriminate between different origins of A. japonicus. Significant differences in the FA compositions showed the effectiveness of FA composition as a tool for distinguishing between different origins of A. japonicus. The two technologies, combined with multivariate statistical analysis, can be promising methods to discriminate A. japonicus from different geographical areas.
地理溯源是海产品食品质量与安全控制的一个重要问题。本研究测定了来自中国北海七个采样点的133份日本对虾样本的δC和δN值以及脂肪酸(FA)含量,以评估它们在日本对虾产地溯源中的适用性。为了评估不同数据集在分类或预测能力方面的表现,对其应用了主成分分析(PCA)和判别分析(DA)。δC和δN值能够有效区分日本对虾的不同产地。脂肪酸组成的显著差异表明脂肪酸组成作为区分日本对虾不同产地的工具是有效的。这两种技术与多元统计分析相结合,有望成为区分不同地理区域日本对虾的方法。