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斑鳢后备亲本体质量与形态性状间的关系分析
引用本文:夏威威,刘海洋,欧密,罗青,黄苏静,赵训金,熊炳源,吴国宏,陈昆慈,赵建.斑鳢后备亲本体质量与形态性状间的关系分析[J].南方农业学报,2022,53(12):3584-3592.
作者姓名:夏威威  刘海洋  欧密  罗青  黄苏静  赵训金  熊炳源  吴国宏  陈昆慈  赵建
作者单位:1 上海海洋大学水产与生命学院, 上海 201306;2 中国水产科学研究院珠江水产研究所/农业农村部热带亚热带水产资源利用与养殖重点实验室, 广东广州 510380;3 佛山市南海区九江镇农林服务中心, 广东佛山 528200;4 佛山市南宏渔业有限公司, 广东佛山 528200
基金项目:国家现代农业产业技术体系项目(CARS-46);中国水产科学研究院基本科研业务费专项(2020TD34,2021SJ-XT1);广东省九江鱼花产业园项目(JJ-2020-009)
摘    要:【目的】明确斑鳢体质量与形态性状间关系,为提高斑鳢亲本选育效率提供理论依据。【方法】测量1165条斑鳢后备亲本,指标包括体质量(Y)、全长(X1)、体长(X2)、头长(X3)、吻长(X4)、眼径(X5)、体高(X6)、肛门处体高(X7)、尾柄长(X8)、尾柄高(X9)共10个性状。利用分子标记进行性别鉴定后,运用方差分析、相关分析及通径分析等方法分析雌雄斑鳢体质量与形态性状间关系,运用多元回归分析建立形态性状对体质量的回归方程。【结果】 1165条斑鳢包含雄性711条、雌性454条。雌雄斑鳢各形态性状与体质量相关系数均达极显著差异水平(P<0.01,下同),通径分析显示,雄性斑鳢体长对体质量影响最大,其次为体高、尾柄高、肛门处体高、尾柄长和眼径;雌性斑鳢体长对体质量影响作用最大,其次为肛门处体高、尾柄高、眼径和尾柄长。对雌雄斑鳢分别建立多元回归方程,雄性斑鳢多元回归方程为Y=-484.547+21.628X2+21.577X7-130.000X5+54.475X9-33.605X8+32.055X6,雌性斑鳢多元回归方程为Y=-503.361+24.994X2+31.786X7+56.763X9-38.272X8-83.860X5。检验回归方程达极显著差异水平,将斑鳢形态性状带入回归方程得到预测值。对预测值与实际值进行配对样本T检验分析,结果显示无显著差异(P>0.05),表明回归方程可用于斑鳢的选育及实际生产工作中。【结论】在斑鳢生产及选育过程中应以体质量为首要考虑因素,并综合考虑体长、体高、尾柄长和尾柄高的影响,以期获得优良性状的个体。

关 键 词:斑鳢    形态性状    通径分析    多元回归分析
收稿时间:2022-05-30

Relationship between body weight and morphological traits of the backup parents of Channa maculata
XIAWei-wei,LIU Hai-yang,OU Mi,LUO Qing,HUANG Su-jing,ZHAO Xun-jin,XIONG Bing-yuan,WU Guo-hong,CHEN Kun-ci,ZHAO Jian.Relationship between body weight and morphological traits of the backup parents of Channa maculata[J].Journal of Southern Agriculture,2022,53(12):3584-3592.
Authors:XIAWei-wei  LIU Hai-yang  OU Mi  LUO Qing  HUANG Su-jing  ZHAO Xun-jin  XIONG Bing-yuan  WU Guo-hong  CHEN Kun-ci  ZHAO Jian
Abstract:【Objective】 To improve the breeding efficiency of Channa maculata parents, it is necessary to clarify the relationship between the body weight and morphological characters.【Method】 In this study, 1165 backup parents of C. maculata were measured, the 10 traits included body weight(Y), full length(X1), body length(X2), head length(X3), mouth length(X4), eye diameter(X5), body depth(X6), body depth at the anus(X7), tail peduncle length(X8), tail peduncle depth (X9). After gender identification using molecular markers, the relationship between body weight and morphological traits was analyzed using variance analysis, correlation analysis, and path analysis for both male and female C. maculata, and and the regression equation of morphological traits on body weight was established using multiple regression analysis.【Result】 The results showed that there were 711 males and 454 females among the 1165 C. maculata. The correlation coefficients between the morphological traits and body weight of male and female C. maculata all reached extremely significant levels(P<0.01, the same below). Path analysis showed that the body length of male C. maculata had the greatest impact on body weight, followed by body height, caudal peduncle height, and body depth at the anus, tail handle length, eye diameter. The body length of female C. maculata had the greatest effect on body weight, followed by body depth at the anus, tail peduncle depth, eye diameter and tail peduncle length. Finally, multiple regression equations were established for male and female C. maculata respectively, that for male was Y=-484.547 + 21.628X2 + 21.577X7-130.000X5+54.475X9-33.605X8+32.055X6, and for female was Y=-503.361+24.994X2+31.786X7+56.763X9-38.272X8-83.860X5. After testing, the regression equation reached highly significant level, and the morphological traits of C. maculata were brought into the regression equation to obtain the predicted value. The paired sample T-test analysis between the predicted value and the actual value showed no significant difference(P>0.05), indicating that the regression equation can be used in the breeding and actual production of C. maculata.【Conclusion】 In the production and selection of C. maculata, body weight should be the primary consideration, and the effects of body length, body depth, tail peduncle length and tail peduncle depth should be taken into account in order to obtain individuals with excellent traits.
Keywords:
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