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作 者:何俊 蓝天一 刘颖 李宗涵 方军[3] 柴雪良[3] 王志勇[1,2] 任鹏 HE Jun;LAN Tianyi;LIU Ying;LI Zonghan;FANG Jun;CHAI Xueliang;WANG Zhiyong;REN Peng(Fishies College,Jimei University,Xiamen 361021,China;Key Laboratory of Healthy Mariculture for the East China Sea,Ministry of Agriculture and Rural Affairs,Xiamen 361021,China;Zhejiang Mariculture Research Institute& Zhejiang Key Lab of Exploitation and Preservation of Coastal Bio-Resource (Wenzhou) & Wenzhou Key Laboratory ofMarine Genetics and Breeding,Wenzhou 325005,China)
机构地区:[1]集美大学水产学院,福建厦门361021 [2]农业农村部东海海水健康养殖重点实验室,福建厦门321021 [3]浙江省海洋水产养殖研究所,浙江省近岸水域生物资源开发与保护重点实验室,温州市海洋生物遗传育种重点实验室,浙江温州325005
出 处:《集美大学学报(自然科学版)》2022年第2期107-113,共7页Journal of Jimei University:Natural Science
基 金:温州市基础性农业科技项目(N20190012);温州市育种协作组项目(2019ZX001)。
摘 要:为了探讨连续选育多代以后泥蚶形态性状对全重和软体部重的影响,采用相关分析、通径分析对330个2龄“乐清湾1号”泥蚶的壳长L、壳高H、壳宽W、全重Y_(1)和软体部重Y_(2)等5个性状指标进行分析,并建立形态性状对全重、软体部重的最优回归方程。结果显示:1)所测5个数量性状之间的相关系数均达到极显著水平(P<0.01),壳宽与全重的相关系数最大(0.952),壳长与软体部重的相关系数最大(0.928)。2)通径分析结果显示,壳宽对全重的直接影响最大(0.479),是影响全重的主要因素;壳长和壳高主要通过壳宽间接影响全重,是影响全重的次要因素;对软体部重的直接影响最大的是壳长(0.415),其次是壳宽(0.390),两者是影响软体部重的主要因素。3)用多元回归分析方法建立壳长、壳高、壳宽估计全重和软体部重的最优回归方程:Y_(1)=-18.798+0.265L+0.294H+0.646W;Y_(2)=-7.194+0.143L+0.088H+0.203W。In order to study the relationship between morphological traits and weight traits of Tegillarca granosa after selection of seven generations,the shell length(L),shell height(H),shell width(W),body weight(Y_(1))and soft-tissue weight(Y_(2))of 330 two-year-old T.granosa were measured.With the morphological traits(L,H and W)used as independent variables,the weight traits(Y_(1) and Y_(2))as dependent variables,the path coefficients and determinant coefficient were calculated using correlation analysis and path analysis,and the multiple regression equations of morphological traits on Y_(1) and Y_(2) was established.The results showed that:1)There were extremely significant correlations among the five measured traits(P<0.01),the correlation coefficient between W and Y_(1) was the largest;the correlation coefficient between L and Y_(2) was the largest.2)Path analysis results showed that W had the greatest direct impact on the Y_(1)(0.479),which was the main factor affecting Y_(1);L and H mainly affected Y_(1) indirectly through W,which were the secondary factors affecting Y_(1);L had the greatest direct impact on Y_(2)(0.415),the second was W(0.390),both of them mainly affected Y_(1).3)The multiple regression equations were obtained to estimate Y_(1) and Y_(2) as:Y_(1)=-18.798+0.265L+0.294H+0.646W;Y_(2)=-7.194+0.143L+0.088H+0.203W.The above results provided basic data for the further development of the breeding of“Yueqing Bay#1”of T.granosa.
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