大口黑鲈形态性状对体重的影响效果分析  

Mathematical analysis of effects of morphometric attribute on body weight of largemouth bass(Micropterus salmoides)

作　　者：何小燕[1,2] 刘小林[2] 白俊杰[1] 李胜杰[1] 樊佳佳[1,3] 

机构地区：[1]中国水产科学研究院珠江水产研究所,中国水产科学研究院热带亚热带鱼类选育与养殖重点开放实验室,广东广州510380 [2]西北农林科技大学动物科技学院,陕西杨凌712100 [3]大连水产学院生命科学与技术学院,辽宁大连116023

出　　处：《水产学报》2009年第4期597-603,共7页Journal of Fisheries of China

基　　金：国家科技支撑项目(2006BAD01A1209);国家科技基础条件平台工作项目(2005DKA21103)

摘　　要：对大口黑鲈全长、体长、体高、体宽、眼间距、头长、吻长、尾柄长、尾柄高和体重共10个性状进行测定,运用相关分析、通径分析和多元回归分析,剔除与体长存在显著共线性的全长、体高、头长,尾柄高及回归方程中不显著的吻长和尾柄长,计算以体宽、体长、眼间距3个形态性状为自变量,体重为依变量的相关系数、通径系数、决定系数及相关指数,定量分析大口黑鲈形态性状对体重的影响效果。结果显示,3个形态性状与体重的相关系数(0.942,0.979,0.928)均达到极显著水平(P<0.01);通径分析中,3个形态性状对体重的通径系数亦达到极显著水平(P<0.01),它们是直接影响体重的重要指标,其中体宽(P4=0.599)对体重的直接影响最大。所选形态性状与体重的相关指数R2=0.980,说明所选性状是影响体重的主要形态性状。应用逐步多元回归分析建立了以体重为依变量(Y),体宽(X4)、体长(X2)和眼间距(X5)为自变量的回归方程:LgY=1.065+0.765 LgX2+1.441 LgX4+0.543 LgX5。以上形态性状对体重影响效果相关数据的获得为大口黑鲈选育测量指标的确定提供了理论依据。The effects of morphometric attributes on body weight of largemouth bass were analyzed. Data of total length （X1 ）, standard length （X2 ）, body depth （X3 ）, body width （ X4 ）, interorbital distance （X5）, head length （ X6 ）, snout length （ X7 ）, caudal peduncle length （X8 ）, caudal peduncle depth （ X9 ） and body weight （ Y ）were collected from culture pond in this study. Correlation analysis, path analysis and multiple regression were used. The correlation coefficients among the morphometric attributes were calculated, then the total length, body depth, head length and caudal peduncle depth were eliminated from the variable data, because all of them were co-linear with standard length. Snout length and caudal peduncle length were also kicked out from the variable data because of no significance in multiple regression equation. The three morphometric attributes （ X2 , X4, X5） were used as independent variables, and body weight （Y） was used as a dependent variable for path analysis. Path coefficients （Py-x） , determination coefficients （dy,x） and correlation index （R2） were calculated in path analysis. The results showed that the three independent variables significantly affect body weight with correlation coefficient 0. 942, 0.979, 0. 928 （ P 〈 0.01 ） respectively. The path coefficients （Py, x ） of the body width, standard length and interorbital distance to the body weight have all reached a level of significance. These attributes were very indicative of determining the body weight, among them the body width weighted the most （P4 = 0. 599） to the body weight, it was a key effective factor, and standard length and interorbital distance weighted the second and the third （P2 = 0. 231, P5 = 0. 189 ）. Judged from the results of high correlation index （ R2 = 0. 980 ） , the main variables （X2, X4, Xa） have been selected. We have obtained the multiple regression equation to estimate the body weight as LgY = 1.065 ＋ 0.765 LgX2 ＋ 1.441

关 键 词：大口黑鲈 形态性状 相关分析 多元回归 

分 类 号：S917[农业科学—水产科学]