CORRELATION AND PATH ANALYSIS OF MORPHOLOGICAL TRAITS AND BODY WEIGHT IN SILVER POMFRET (Pampus argenteus) Authors: Cheng Zhang, Haipeng Yu, Danli Wang, Shanliang Xu Journal: Journal of Animal and Plant Sciences (JAPS) ISSN: 1018-7081 (Print), 2309-8694 (Online) Volume: 34 Issue: 2 Pages: 495-505 Year: 2024 DOI: https://doi.org/10.36899/JAPS.2024.2.0735 URL: https://doi.org/https://doi.org/10.36899/JAPS.2024.2.0735 Publisher: Pakistan Agricultural Scientists Forum Abstract:

Silver pomfret Pampus argenteus is an important economic fish for aquaculture industry in China and Southeast Asian countries. In order to study the relationship between morphological traits of P. argenteus, we analyzed the correlation, path analyses, and multiple linear regression among twelve morphological traits of P. argenteus at different growth stages [60-, 90-, 120-, and 360-days post hatching (dph)]. The results showed that the coefficient of variation of body weight and trunk length traits remained stable and at a high level across all age groups, while other traits were the opposite. Body length and tail length traits had great direct effect on the body weight of P. argenteus at the first three growth stages (60, 90, and 120 dph), while body length and body height traits had great direct effect in 360 dph, and the direct effect coefficient of caudal length was negative, indicating that the trait had a negative effect on body weight. Multiple linear regression analysis between morphological traits and body weight indicated that R2 was greater than 0.84 across all age groups. The optimal multiple linear regression equations, as determined with stepwise regression, were constructed with morphological traits as independent variables and body weight as dependent variables. The work clarified the correlation between various morphological traits and body weight of a commercially-important P. argenteus. The predictive models for body weight might be useful for the aquaculture and selective breeding of P. argenteus.

Keywords: Pampus argenteus, morphological traits, correlation analysis, path analysis, multiple linear regress