Almarri, S., AlSaqufi, A., Hassanien, H., Abou Zied, R., Eldeeb, K. (2024). Discriminant Analysis Approach in Morphometric Traits to Differentiate the Thinlip Mullet, Liza ramada. Egyptian Journal of Aquatic Biology and Fisheries, 28(5), 1913-1936. doi: 10.21608/ejabf.2024.389754
Salem Almarri; Ahmed AlSaqufi; Hesham Hassanien; Ramadan Abou Zied; Kamal Eldeeb. "Discriminant Analysis Approach in Morphometric Traits to Differentiate the Thinlip Mullet, Liza ramada". Egyptian Journal of Aquatic Biology and Fisheries, 28, 5, 2024, 1913-1936. doi: 10.21608/ejabf.2024.389754
Almarri, S., AlSaqufi, A., Hassanien, H., Abou Zied, R., Eldeeb, K. (2024). 'Discriminant Analysis Approach in Morphometric Traits to Differentiate the Thinlip Mullet, Liza ramada', Egyptian Journal of Aquatic Biology and Fisheries, 28(5), pp. 1913-1936. doi: 10.21608/ejabf.2024.389754
Almarri, S., AlSaqufi, A., Hassanien, H., Abou Zied, R., Eldeeb, K. Discriminant Analysis Approach in Morphometric Traits to Differentiate the Thinlip Mullet, Liza ramada. Egyptian Journal of Aquatic Biology and Fisheries, 2024; 28(5): 1913-1936. doi: 10.21608/ejabf.2024.389754
Discriminant Analysis Approach in Morphometric Traits to Differentiate the Thinlip Mullet, Liza ramada
This study investigated the possibility of using morphometric measurements to differentiate the thinlip mullet, Liza ramada. For this purpose, one hundred and fifty specimens were randomly selected from the Qarun, Manzalla, and Burullus lakes in Egypt. Each specimen was assessed for 19 morphometric characteristics. The data were computed using principal component (PCA) and discriminant function analyses. The findings revealed that PC1, PC2, and PC3 accounted for over 76.24% of the observed morphometric variance. PC1 and PC2 accounted for 34.28 and 22.51%, respectively, of the variation. Morphological data from all L. ramada populations identified three primary categories. Univariate analysis revealed substantial differences across populations in all characteristics, except body weight and ocular diameter (ED) ratio, allowing separation along PCI and PC2. BW, CPD, PecFL, MBH, and CF ratios were selected using step-wise discriminant function analysis, which revealed three distinct morphotypes. Two canonical functions accounted for 100% of the variation, with the first function accounting for 80.11%. The first function distinguished the Qarun population that scored favorably (greater than zero), while the second function successfully separated the Burullus population that scored unfavorably (less than zero). It can be concluded that morphometric data acquired using PCA and DFA techniques revealed considerable difference amongst the thinlip mullet population morphotypes. The morphometric traits variation will help understand the genetic diversity of the L. ramada genotypes and can help to initiate the program for the preservation of the thinlip mullet genetic resources.
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