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Cited by 5 publications
(1 citation statement)
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“…This was accomplished by using the allometric scheme: M adj = M × (L s /L 0 ) b [ 30 ], where M is the original measurement, M adj is the size-adjusted measurement, L 0 is the standard length, L s is the mean of standard length, and parameter b is estimated for each character from experimental data as the slope of the regression of log M on log L 0 using all fish in all populations. PCA was used to reduce redundancy among the morphometric variables and eliminate redundant autonomous variables for population differentiation and cluster heatmap to investigate the phenotypic relations among populations [ 31 , 32 ]. The Statistical Package for Social Sciences (SPSS) version 25.0 was used for statistical analyses at 5% (p < 0.05) and Software R version 3.6.2 (R Core Team, Vienna, Austria) for performing PCA and cluster heatmap analyses.…”
Section: Methodsmentioning
confidence: 99%
“…This was accomplished by using the allometric scheme: M adj = M × (L s /L 0 ) b [ 30 ], where M is the original measurement, M adj is the size-adjusted measurement, L 0 is the standard length, L s is the mean of standard length, and parameter b is estimated for each character from experimental data as the slope of the regression of log M on log L 0 using all fish in all populations. PCA was used to reduce redundancy among the morphometric variables and eliminate redundant autonomous variables for population differentiation and cluster heatmap to investigate the phenotypic relations among populations [ 31 , 32 ]. The Statistical Package for Social Sciences (SPSS) version 25.0 was used for statistical analyses at 5% (p < 0.05) and Software R version 3.6.2 (R Core Team, Vienna, Austria) for performing PCA and cluster heatmap analyses.…”
Section: Methodsmentioning
confidence: 99%