| 摘要: |
| 从广西琴文蛤(Meretrix lyrata)养殖群体中随机选取87 颗成贝, 测量其活体重(y)、壳长(χ1)、壳高 (χ2)、壳宽 (χ3)及外韧带长(χ4), 计算相关系数。采用通径分析方法计算了以体长性状为自变量对体重做依变量的通径系数、决定系数及相关指数, 对各性状的影响大小进行剖分, 明确影响琴文蛤体重的主要外部形态性状。结果表明, 所测各形态性状间的相关性均达到极显著水平(P＜0.01); 其中外韧带长(P=0.359 3)和壳宽(P=0.348 0)对体重的直接影响较大, 是影响体重的主要因素。决定系数分析结果与通径分析结果有一致的变化趋势; 所选各形态性状与体重的复相关指数为R2=0.943; 表明所选性状是影响体重的主要性状。利用多元回归分析法建立了壳长、壳宽及外韧带长为自变量的估计体重的回归方程: y=?32.2882+0.2604 χ1+0.2991 χ2+0.6737 χ3+0.5175 χ4, 为琴文蛤选种提供了理论和理想的测度标准。 |
| 关键词: 琴文蛤(Meretrix lyrata) 形态性状, 体重 相关分析 通径分析 |
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| 基金项目:浙江省科研院所专项项目(2009F20010); 温州市科技兴海项目(S20080019); 国家贝类产业技术体系项目(CARS-48) |
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| Mathematical analysis of the correlations between the morphometric attributes and body weight Meretrix lyrata |
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| Abstract: |
| Data for this study were collected from 87 Meretrix lyrata in Guangxi province. The shell length (χ1), the shell height(χ2), the shell width (χ3), the outer ligament length (χ4), and the body weight (y) were measured. The correlation coefficient matrix was constructed. The preceding four morphometric characters were used as independent variables, and the body weight was used as a dependent variable for calculations of path analysis, path coefficients (Pi), determination coefficients (di) and correlation index R2). It was found that all four correlations between the four morphological characters and the weight were significant(P＜0.01). Outer ligament length (X4, P1=0.3593) and shell width(X3, P2=0. 348) were the key effective factors, bearing predominant, direct effect and determinacy on the live body weight. The result of high correlation index (R2 = 0.943) clearly indicated that the path coefficient analysis could reveal the truthful relationship between the independent variables and the dependent variable. The multiple regression equation for estimation of live body weight was y=?32.2882+0.2604 χ1+0.2991 χ2+0.6737 χ3+0.5175 χ4. This paper provides theoretical evidence and appropriate measurement targets for breeding of M. lyrata. |
| Key words: Meretrix lyrata morphmetric attribute body weight Correlation analysis path analysis |
