文献类型：期刊文献

中文题名：橄榄蛏蚌赣江群体数量性状的通径分析

英文题名：Path Analysis of Quantitative Traits of Shellfish Solenaia oleivora Population in Ganjiang River

作者：张根芳[1];张文府[2];方爱萍[2];杨受保[3]

机构：[1]金华职业技术学院,浙江金华321007;[2]金华市威旺养殖新技术有限公司,浙江金华321017;[3]绍兴文理学院,浙江绍兴312000

年份：2020

卷号：39

期号：2

起止页码：271

中文期刊名：水产科学

外文期刊名：Fisheries Science

收录：CSTPCD、、北大核心2017、CSCD_E2019_2020、北大核心、CSCD

基金：国家贝类产业技术体系项目(CARS-49);浙江省公益项目(2017C32088)

语种：中文

中文关键词：橄榄蛏蚌;赣江群体;数量性状;通径分析

外文关键词：Solenia oleivora;population in Ganjiang River;quantitative trait;path analysis

中文摘要：为探明橄榄蛏蚌各数量性状间的相关性以及影响肉质量的主要性状,随机选取40只3~4龄的野生橄榄蛏蚌,测量了壳长、壳宽、壳高、体质量(x1)、壳质量(x2)、高(x3)和肉质量(y)等7个数量性状,计算含肉率。运用相关分析、通径分析和多元回归分析等统计方法,对各数量性状之间的相互关系进行分析,计算各性状对肉质量的通径系数与决定系数,并建立了回归方程。研究结果显示,橄榄蛏蚌的含肉率达到65.62%,是极具开发潜力的食用淡水贝类;橄榄蛏蚌各数量性状间的表型相关均达到了极显著水平(P<0.01);体质量对肉质量的直接作用最大,为0.983,是影响肉质量的主要因素,而壳长、壳宽、壳高、高与壳质量等性状对肉质量的影响主要是通过体质量间接实现的;体质量的综合决定效应为96.08%,是影响肉质量的最主要因素,具有育种意义;运用逐步回归方法,建立了各数量性状对肉质量的回归方程为:y=-18.548+0.690x1-0.442x2+6.804x3。

外文摘要：Seven quantitative traits including shell length, shell width, shell height, body height, body weight, shell weight and soft part weight were measured in 40 wild shellfish Solenia oleivora collected from Poyang Lake randomly to analyze the correlation between quantitative traits and the main traits influencing soft part weight by correlation analysis, path analysis, multivariate regression analysis, and optimal regression equation. The results showed that the shellfish had 65.62% of dressing rate and very significant phenotypic correlation between various quantitative traits(P<0.01). Body weight, as the main factor, had the greatest direct effect on soft part weight, and the effects of shell length, shell width, shell height, body height and shell weight on soft part weight were mainly indirect through body weight, with the comprehensive determining effect of 96.08%, the most important factor affecting flesh weight and had breeding significance. The optimal regression equation of quantitative traits on soft part weight was expressed as: y=-18.548+0.690x1-0.442x2+6.804x3, through stepwise regression analysis, where y is soft part weight(g), x1 is body weight(g), x2 is shell weight(g), and x3 is body height(cm).