YIN Xingjun, HUA Chuanxiang, ZHU Qingcheng. Analysis of morphological differences and discrimination between female and male Cololabis saira based on geometric morphometrics[J]. South China Fisheries Science. DOI: 10.12131/20240077
Citation: YIN Xingjun, HUA Chuanxiang, ZHU Qingcheng. Analysis of morphological differences and discrimination between female and male Cololabis saira based on geometric morphometrics[J]. South China Fisheries Science. DOI: 10.12131/20240077

Analysis of morphological differences and discrimination between female and male Cololabis saira based on geometric morphometrics

  • Pacific saury (Cololabis saira) is widely distributed in the Northwest Pacific Ocean and is one of the main targets of Chinese pelagic operations. To investigate the morphological differences between female and male individuals and differentiate the two sexes effectively, we applied geometric morphometrics for the first time on 150 Pacific saury samples which were collected from the Northwest Pacific high seas during May–November, 2022, so as to analyze their morphology and establish a sex differentiation model via discriminant analysis with fish images and biological data. The samples were divided into two batches: Batch 1 (107 individuals) was used for morphological analysis and model construction, while Batch 2 (43 individuals) was used to test the model's practical application. The results show that in the relative warp analysis, the first and second principal components explained 63.43% and 11.79% of the total variation, respectively, with good dimensionality reduction and scatter plot separation effects. Landmark I and II contributed cumulatively to 57.94% and 41.83% of the variance, respectively, indicating that these landmark types play a significant role in discrimination between the two sexes, whereas Landmark III had lesser influence. The results of the thin-plate spline analysis show that the morphological differences between them were mainly in the eyes, the front part of the trunk and the tail. The results of discriminant analysis and cross-validation of Batch 1 showed correct discrimination rates of 91.6% and 88.8%, respectively. When applying the model to Batch 2 for sex discrimination, the correct discrimination rate was 88.45%. Thus, geometric morphometrics analysis is an effective method for morphological studies and sex identification of C. saira.
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