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不同生长时期大菱鲆(Scophthalmus maximus)形态性状与体质量的通径分析及曲线拟合研究
刘莹1, 于超勇1, 于道德1, 宋静静1, 宋宗诚2, 赵文溪1, 刘洪军1, 官曙光1
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(1.山东省海洋生物研究院, 山东省海水健康养殖工程技术研究中心, 山东省海水养殖病害防治重点实验室, 山东青岛 266104;2.威海圣航水产科技有限公司, 山东威海 264200)
摘要:
[目的]深入了解不同生长时期大菱鲆(Scophthalmus maximus)形态性状与体质量之间的关系,确定适于大菱鲆人工选育的主要测量指标。[方法]应用相关性分析、通径分析和多元回归分析方法对大菱鲆6月龄幼鱼及14月龄成鱼全长(TL)、体长(BL)、头长(HL)、体高(BD)、尾柄宽(THH)、体厚(BW)和体质量(BM)7个性状进行分析,同时通过曲线拟合分析获得形态性状与体质量之间的最佳拟合模型。[结果]不同生长时期,大菱鲆各形态性状与体质量的相关性均达到极显著水平(P<0.01)。6月龄阶段,全长(TL)、体高(BD)、体厚(BW)、头长(HL)的直接通径系数达到显著水平(P<0.05);14月龄阶段,全长(TL)、体厚(BW)、尾柄宽(THH)的直接通径系数达极显著水平(P<0.01),并建立2个生长时期不同性状对体质量的回归方程。6月龄阶段,进入回归方程的各形态性状与体质量(BM)的最优曲线拟合模型均为线性函数模型;14月龄阶段,进入回归方程的各形态性状与体质量(BM)的最优曲线拟合模型均为幂函数模型。[结论]不同时期,影响大菱鲆体质量的主要形态性状不同,且各形态性状对大菱鲆体质量的作用效果也不尽相同,适用的最优拟合模型也不同。建议将全长(TL)(6~14月龄)作为幼鱼与成鱼阶段的主要育种目标性状,同时幼鱼阶段辅以体高(BD)、体厚(BW)和头长(HL)作为参考性状,成鱼阶段辅以体厚(BW)和尾柄宽(THH)为参考性状,从而有效提高大菱鲆的选育效率,为大菱鲆选育提供测量指标与理论支持。
关键词:  大菱鲆  形态性状  体质量  相关分析  通径分析  模型拟合
DOI:10.13657/j.cnki.gxkxyxb.20180717.001
投稿时间:2018-05-09
基金项目:山东省农业良种工程"优质抗病速生鱼类新品种选良",山东省现代农业产业体系鱼类创新团队(SDAIT-14-02)和山东省2017年度自然科学基金(ZR2017PC014)资助。
Path Coefficient Analysis and Curve Estimates for Body Mass and Morphometric Traits of Scophthalmus maximus at Different Growth Stages
LIU Ying1, YU Chaoyong1, YU Daode1, SONG Jingjing1, SONG Zongcheng2, ZHAO Wenxi1, LIU Hongjun1, GUAN Shuguang1
(1.Healthy Mariculture Engineering Technology Research Center of Shandong Province, Shandong Province Key Laboratory for Disease Control in Mariculture, Marine Biology Institute of Shandong Province, Qingdao, Shandong, 266104, China;2.WeihaiShenghang Aquatic Science and Technology Co., LTD, Weihai, Shandong, 264200, China)
Abstract:
[Objective] In order to understand the relationship between body mass and morphometric traits of Scophthalmus maximus at different growth stages and determine the main measurement indicators suitable for artificial selection of Scophthalmus maximus. [Methods] Body mass (BM) and six morphometric traits which consists of total length (TL), body length (BL), head length (HL), body depth (BD), tail handle height (THH) and body width (BW) were measured in 489 individuals of 6 months old and 439 individuals of 14 months old. The correlations coefficient, path coefficient indirect path coefficient and determinant coefficient were calculated by correlation and path analysis. The multivariate regression equations which with the morphological traits as variables and body mass as the dependent variable were established by stepwise regression analysis. The best curve models for 6 months old and 14 months old individuals were selected in six curve-fitting models. [Results] The results showed that the correlations coefficient between two different traits were extremely significant (P<0.01). The path coefficients of TL, BD, BW, HL for body mass were significant (P<0.05) at 6 months old, and the path coefficients of TL, BW, THH were extremely significant (P<0.01) at 14 months old. Removed the unimportant traits, the multivariate regression equations were established at two different growth stages. At the age of 6 months, the optimal curve fitting models for each morphological trait and body mass (BM) of the regressi