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唇形态性状对体质量影响及网箱养殖 被引量:5

Mathematical Analysis of Effects of Morphometric Attributes on Body Weight and Growth of Hemibarbus labeo in Cage Culture
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摘要 测量234尾3月龄唇的全长(x1)、体长(x2)、体高(x3)、头长(x4)、吻长(x5)、眼径(x6)、眼后头长(x7)、尾柄长(x8)、尾柄高(x9)、头高(x10)及体质量(y)11个形态学指标。运用相关分析、通径分析和回归分析,分别计算了形态性状的相关系数、影响体质量的主要形态性状的通径系数和决定系数,建立了主要形态性状与体质量的回归方程。试验结果表明,唇的体质量变异系数最大(21.5806%)。各形态性状间的表型相关系数均达极显著水平(P<0.01)。通径分析结果表明,体长、体高、眼径、尾柄高与头高达显著水平,是影响体质量的主要形态性状,其通径系数分别为0.4316、0.3487、-0.0621、0.2071和0.1101。主要形态性状对唇体质量的决定系数中,体长最大,为0.1863,其他性状由大到小依次为体高(0.1216)、尾柄高(0.0429)、头高(0.0121)和眼径(0.0039);两两性状对体质量的决定程度中,体长和体高对体质量的影响最大。复相关分析和回归分析结果表明,体长、体高、眼径、尾柄高和头高5个性状对体质量的相关指数达到0.892,回归关系达到显著水平(P<0.05)。应用逐步多元回归分析建立了以体质量为依变量,体长、体高、眼径、尾柄高和头高为自变量的回归方程:y=-3.778+0.550x2+1.417x3-0.839x6+1.915x9+0.715x10,方程回归关系达到极显著水平(P<0.01)。唇幼鱼体长、体高、眼径、尾柄高、头高和体质量分别为(5.30±0.34)cm,(1.15±0.11)cm,(0.51±0.03)cm,(0.49±0.05)cm,(0.99±0.07)cm和(1.98±0.43)g,在网箱内饲养26个月,体长、体高、眼径、尾柄高、头高和体质量分别为(32.40±2.87)cm,(7.22±0.84)cm,(1.18±0.09)cm,(2.78±0.32)cm,(5.33±0.64)cm和(576.94±143.82)g。 Eleven morphometric attributes including total length (x1 ) ,body length(x2 ) ,body depth (x3 ) , head length (x4 ) ,snout length (x5 ) ,interorbital (x6 ) ,postorbital head length (x7 ) ,caudal peduncle length (x8 ) ,caudal peduncle depth (x9 ) ,head depth(x10 ) and body weight(y) were measured in 234 three‐month‐old H emibarbus labeo samples . T he correlation index , path coefficients and determination coefficient were calculated based on morphometric attributes by correlation analysis ,path analysis and multivariate analysis ,and the significan morphometric attributes (P〈0 .05) were used to establish the multiple regression equations .The results showed that the maximal coefficient of variation was found in y (21 .5806% ) , higher than that in variation of the other morphological attributes , with a normal distribution in morphometric attributes . T he correlation coefficients of morphological attributes to body weight were all at very significant level (P〈 0 .01) .The path analysis revealed that partial regression coefficients of x2 (0 .4316) , x3 (0 .3487) , x6 (-0 .0621) , x9 (0 .2071) and x10 (0 .1101) were found at significant level (P〈 0 .05) .The determination coefficients was larger in x2 (0 .1863) than that in x3 (0 .1216) ,x9 (0 .0429) ,x10 (0 .0121) and x6 (0 .0039) .The determination coefficient of x2 and x3 to y was higher than that of others .The high value of correlation index between morphometric attributes and body weight was 0 .892 (r2 ) with significant level (P〈0 .05) ,indicating that the five attributes (x2 ,x3 ,x6 ,x9 and x10 ) were key morphometric attributes to the body weight and practical in the selective breeding of H . labeo .The significant morphometric attributes (P〈0 .05) were used to establish the multiple regression equation as y = -3 .778+0 .550x2 +1 .417x3 -0 .839x6 +1 .915x9 +0 .715x10 ,in juvenile H .labeo[x2 =(5 .30 ± 0 .34) cm ,x3 = (1 .15 ± 0 .11) cm ,x6 = (0 .51 ± 0 .03) cm ,x9 = (0 .49 ± 0 .05) cm ,and x10 =(0 .99 ± 0 .07) cm ,Y = (1 .98 ± 0 .43) g] .The fish cultured in the cage for 26 months had x2 = (32 .40 ± 2 .87 ) cm ,x3 = (7 .22 ± 0 .84 ) cm , x6 (1 .18 ± 0 .09 )cm , x9 (2 .78 ± 0 .32 ) cm , x10 (5 .33 ± 0 .64 ) cm and y= (576 .94 ± 143 .82 ) g .
出处 《水产科学》 CAS 北大核心 2014年第6期363-368,共6页 Fisheries Science
基金 辽宁省科学技术厅"辽宁省重大 重点项目"(2008203001)
关键词 鱼骨唇 形态性状 相关分析 通径分析 多元回归方程 Hemibarbus labeo morphometric trait correlation analysis path analysis multiple regression equation
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