|本期目录/Table of Contents|

[1]朱文,叶坤,王志勇.黄姑鱼“金鳞1号”形态性状对体重的影响分析[J].集美大学学报(自然科学版),2018,23(4):249-257.
　ZHU Wen,YE Kun,WANG Zhiyong.The Effects of Morphological Traits on Body Weight of New Variety Nibea albiflora (Richardson)“Jinlin 1”[J].Journal of Jimei University,2018,23(4):249-257.
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《集美大学学报（自然科学版）》[ISSN:1007-7405/CN:35-1186/N]

卷:
第23卷
期数:
2018年第4期
页码:
249-257
栏目:
水产、食品与生物工程
出版日期:
2018-07-28

文章信息/Info

Title:
The Effects of Morphological Traits on Body Weight of New Variety Nibea albiflora (Richardson)“Jinlin 1”
作者:
朱文1; 2; 叶坤1; 2; 王志勇1; 2
（集美大学水产学院，农业部东海海水健康养殖重点实验室，福建 厦门 361021）
Author(s):
ZHU Wen1; 2; YE Kun1; 2; WANG Zhiyong1; 2
(1.Fisheries College，Jimei University,Xiamen 361021,China;2.Key Laboratory of Healthy Mariculture for the East China Sea(Ministry of Agriculture),Xiamen 361021,China)
关键词:
黄姑鱼; 形态性状; 体重; 通径分析; 多元线性回归
Keywords:
Nibea albiflora; phenotypic trait; body weight; path analysis; multiple linear regression equation
分类号:
-
DOI:
-
文献标志码:
A
摘要:
为研究黄姑鱼“金鳞1号”新品种各形态性状与体重间的相关关系，从网箱中随机捞取402尾 16月龄个体，测量其全长（X1）、体长（X2）、头长（X3）、吻长（X4）、眼后头长（X5）、眼径（X6）、躯干长（X7）、体高（X8）、体厚（X9）、尾柄长（X10）、尾柄高（X11）、尾长（X12）及尾鳍长（X13）共13个形态学指标，通过Microsoft Excel 2016和SPSS 22.0软件采用相关分析和通径分析法，得到相关系数和决定系数。剔除不显著及共线性严重相关的性状后，对黄姑鱼的各形态性状与体重进行进一步回归分析，以寻找影响黄姑鱼体重的主要形态性状。结果表明：各相关系数中，全长与体重间相关系数最大（雌性0.871，雄性0.904）；被测性状与各回归系数均达到极显著正相关(P＜0.01)，性状与体重的总决定系数R2♀= 0.894，R2♂= 0.912。拟合得到的以雌性黄姑鱼体重（Y）为因变量，全长（X1）、体高（X8）、体厚（X9）为自变量的最佳线性回归方程为：Y♀= -522.895+18.018×X1+ 25.734×X8+ 34.077×X9，以雄性黄姑鱼体重（Y）为因变量，全长、体高、体厚、尾鳍长为自变量的最佳线性回归方程为：Y♂= -465.844+17.849×X１+24.157×X８+30.023×X９-7.045×X13。
Abstract:
In order to pursuit the correlation between various phenotypic traits and body weight of new variety Nibea albiflora “Jinlin 1”,402 fish were randomly fished out of the cage and 13 phenotypic traits were measured,such as total length(X1),body length(X2),head length(X3),snout length(X4),head length behind eyes(X5),eye diameter(X6),torso(X7),withers height(X8),body width(X9),length of caudal peduncle(X10),depth of caudal peduncle(X11),tail length(X12),and length of caudal fin(X13).The correlation coefficients and determination coefficients were obtained,using correlation and path analysis via Microsoft Excel 2016 and SPSS 22.0.All the traits collinear seriously or not significant were rejected,to hit the main phenotypic traits that affacting the body weight of N.albiflora,then multiple linear regression analysis was further performed,the results showed that the largest correlation coefficient was the effect of total length on body weight in all correlation coefficients (0.871 of female,0.904 of male).All the regression coefficients between measured traits and body weight had signifacant positive correlation (P＜0.01).Total coefficient of determination of female and male was 0.894 and 0.912 respectively.The optimal linear regression equation was found by the body weight as the dependent variable,total length(X1),withers height(X8) and body width(X9) as the independent variables for female:Yfemale= -522.895+18.018×X1+ 25.734×X8+ 34.077×X9. The optimal linear regression equation was found by the body weight as the dependent variable,total length(X1),withers height(X8) and body width(X9) and length of caudal fin(X13) as the independent variables for male:Ymale= -465.844+17.849×X1 + 24.157×X8 + 30.023×X9 – 7.045×X13

参考文献/References:

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备注/Memo

备注/Memo:
更新日期/Last Update: 2018-09-13