Microsoft Excel software was used to process the data to eliminate the influence of fish body size on character parameters during data analysis and improve data accuracy. The data of these seven proportional traits were imported into SPSS 24.0 software for multivariate statistical analysis, including one-way analysis of variance (One-way ANOVA), principal component analysis, cluster analysis, and discriminant analysis.
One-way ANOVA was performed using SPSS 24.0. Multivariate comparison was performed by the Tukey s-b(K) method in one-way ANOVA, and a similar subset was divided, 0.05 was selected as the significance level. 18 (link) In SPSS software, "analysis-dimension reduction-factor" was used to conduct principal component analysis, and extract seven principal components and their eigenvalues, the contribution rate of each principal component, and the cumulative contribution rate according to the order of size. Scatter plots were drawn based on the scores of the first and second principal components to compare the variability and similarity of the five large yellow croaker populations and to determine their morphological differentiation. 19 Using the mean value of each parameter correction, SPSS 19.0 software was used to perform cluster analysis by using the shortest distance system clustering method of Euclidean distance. The species clustering tree was constructed to compare the distance between populations. 20
In formula: P 1 and P 2 are the discriminant accuracy rate (%), P is the comprehensive discriminant rate (%), O is the number of correctly discriminated large yellow croaker (tail), M is the number of measured large yellow croaker (tail). N is the number of large yellow croaker (tail); A i is the number of large yellow croaker (tail) correctly judged by the i group, B i is the number of large yellow croaker (tail) actually judged by the i group, and k is the number of groups (number).
Analysis of morphological differences in five large yellow croaker (Larimichthys crocea) populations 3. RESULTS
One-way ANOVA was performed using SPSS 24.0. Multivariate comparison was performed by the Tukey s-b(K) method in one-way ANOVA, and a similar subset was divided, 0.05 was selected as the significance level. 18 (link) In SPSS software, "analysis-dimension reduction-factor" was used to conduct principal component analysis, and extract seven principal components and their eigenvalues, the contribution rate of each principal component, and the cumulative contribution rate according to the order of size. Scatter plots were drawn based on the scores of the first and second principal components to compare the variability and similarity of the five large yellow croaker populations and to determine their morphological differentiation. 19 Using the mean value of each parameter correction, SPSS 19.0 software was used to perform cluster analysis by using the shortest distance system clustering method of Euclidean distance. The species clustering tree was constructed to compare the distance between populations. 20
In formula: P 1 and P 2 are the discriminant accuracy rate (%), P is the comprehensive discriminant rate (%), O is the number of correctly discriminated large yellow croaker (tail), M is the number of measured large yellow croaker (tail). N is the number of large yellow croaker (tail); A i is the number of large yellow croaker (tail) correctly judged by the i group, B i is the number of large yellow croaker (tail) actually judged by the i group, and k is the number of groups (number).
Analysis of morphological differences in five large yellow croaker (Larimichthys crocea) populations 3. RESULTS
