| 陈胜军,刘先进,杨贤庆,李来好,黄卉,吴燕燕,李春生.不同产地鲍鱼特征元素分析与主成分评价模型的建立.渔业科学进展,2019,40(2):83-90 |
| This study was done to assess regional differences among abalone from different habitats and develop a new and efficient method to identify abalone from different habitats of origin. To do this, the content and composition of 13 major elements and trace elements (Na, K, Mg, Ca, Fe, Zn, Cu, Ni, As, Al, Mn, Cr, and Se) in the muscle tissue of 18 kinds of abalone samples from the four major breeding provinces of Guangdong, Fujian, Shandong, and Liaoning, China, were determined and analyzed using principal component analysis (PCA). The results showed that the elemental content differed among the 18 abalone samples. The variation in Manganese (Mn) was the largest [the coefficient of variation (CV) was 74% among samples], followed by Nickel (Ni) (CV = 65%), and then by Selenium (Se) (CV = 60%); all the rest of the analyzed elements had CVs higher than 10%. At the same time, after using the PCA method to reduce the dimensions of these data, six elements were effectively extracted from among the 13 elements examined that cumulatively explained 89.87% of the variance among samples. These characteristic elements of abalone from different habitats were Ca, Se, Na, Fe, Mn, K, and Ni, and a comprehensive model of the six principal components including them was established as follows: F = 0.2777F1 + 0.2652F2 + 0.1295F3 + 0.1066F4 + 0.0656F5 + 0.0541F6, where F1 represents the first principal component, and F2~F6 represent the second to sixth principal components, respectively. On the basis of the comprehensive PCA score, the top six samples were samples No. 2, 6, 17, 13, 7, and 15, and the lowest one was sample No. 5. Among these, sample No. 2 had a higher content of all characteristic elements and better quality than all others. The PCA approach was found to be quite suitable for the evaluation of the nutritive quality of abalone. The establishment of this PCA model provided an empirical basis for the theoretical determination of the origin of abalone samples. |
