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作 者:张进[1] 梁旭方[1] 易提林[1] 窦亚琪[1] 王乾[1] 余锐[1] 符云 叶卫
机构地区:[1]华中农业大学水产学院,湖北武汉430070 [2]广东省淡水名优鱼类种苗繁育中心,广东广州511453
出 处:《水产科学》2013年第1期1-6,共6页Fisheries Science
基 金:广州市科技计划项目(2009Z1-E711);广东省海洋渔业科技推广专项项目(A200899D02);广州市番禺区科技计划项目(2009-Z-73-1);中央高校基本科研业务费专项(2010PY010;2011PY030)
摘 要:对翘嘴鳜(♀)和斑鳜(♂)杂交F1代进行程序性的驯化,挑选出易驯化和不易驯化的2组。采用一维方差分析和主成分分析研究了易驯化和不易驯化杂交鳜的形态差异;对易驯化杂交鳜全长、体长、体宽、体高、吻长、头长、眼径、眼间距、尾长、尾柄高、尾柄长和体质量等12个性状进行了相关分析和通径分析。试验结果显示,所选易驯化杂交鳜F1代体长、体高和眼径3个形态性状对体质量的相关系数均达到极显著水平(P<0.01),对体质量的通径系数亦达到极显著水平(P<0.01),体长对体质量的直接影响最大,通径系数达0.435;所选3个形态性状与体质量的共同决定系数r2=0.949,说明所选性状是影响体质量的主要形态性状;应用逐步多元回归分析建立了以体质量为依变量(Y),体长(X2)、体高(X4)和眼径(X7)为自变量的回归方程:Y=-15.527+0.127 X2+0.344 X4+0.903 X7。试验结果说明,翘嘴鳜和斑鳜杂交F1代存在易驯化和不易驯化个体的食性分化;用体长、体高和眼径估计体质量的多元回归方程为易驯化杂交鳜选择育种提供了理论依据。The hybrid F1 by Siniperca scherzeri ( ♀ ) XS. chuatsi ( ♂ ) was screened out into two groups, the easy domestication and difficult domestication, by diet domestication. The morphological differences between the two groups were detected by variance analysis and principle component analysis, and the two groups were found to have a certain degree of morphological differentiation and to be distinguished by the phenotype after diet domestication. The effects of morphometric attribution on body weight in the easy domestication hybrids were analyzed, including total length (X1), standard length (X2) , body width (Xs), body depth(X4 ), snout length (Xs), head length (X6), eye diameter (X7), interorbital distance (Xs), tail length(Xg), caudal peduncle length (X10), caudal peduncle depth (Xn) and body weight(Y). The correlation coefficients among the morphometric attributes were calculated and eliminated the co-linear traits with body length. Snout length, caudal peduncle length and caudal peduncle depth were also kicked out from the variable data because of no significance in multiple regression equation. The three morphometrie attributes (X2, X4, and XT) were used as independent variables, and body weight(Y) was used as a dependent variable for path analysis in which path coefficients (Py.x), determination coefficients (dy.x) and correlation index (r2) were calculated. The results showed that the three independent variables showed very significantly effect on the body weight with correlation coefficient 0. 893, 0. 900, and 0. 771 (P〈. 01) ,respectively. All the path coefficient of the body length, body depth and interobital distance to the body weight were significant, in which the body length a key effective factor weighted the most (P2 = 0. 435) to the body weight. Judged from the results of high correlation index (r2 =0. 949), the main variables(X2, X4, and XT) have been selected, thus the multiple regression equation to
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