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采用电感耦合等离子体质谱和原子吸收光谱测定东海4种经济鱼类中25种矿物元素,用多元统计分析元素组成,判断经济鱼类的地理起源。结果显示,主成分分析可以判别鱼类的产地,揭示在地理多样性中起重要作用的元素。用偏最小二乘判别分析和概率神经网络建立的判别模型,可准确地判别鱼类的产地。进一步分析显示,偏最小二乘判别分析和概率神经网络建立的判别模型在不考虑鱼种的情况下,准确率分别达到97.92%和100%。基于矿物元素指纹信息的产地判别技术可应用于近海3个产地的4种经济鱼类的产地判别。
Twenty-five mineral elements in four economic fish species in the East China Sea were determined by inductively coupled plasma mass spectrometry and atomic absorption spectrometry. Multivariate statistical analysis of elemental composition was used to determine the geographical origin of economic fish. The results show that principal component analysis can discriminate the origin of fish and reveal the elements that play an important role in geographical diversity. The discriminant model established by partial least-squares discriminant analysis and probabilistic neural network can accurately determine the origin of fish. Further analysis showed that the discriminant models established by partial least-squares discriminant analysis and probabilistic neural network achieved 97.92% and 100% respectively without considering species. The identification of origin based on mineral element fingerprint information can be applied to determine the origin of four kinds of economic fish in three offshore areas.