文章摘要
白临建,杨爱国,周丽青,吴彪,刘志鸿.栉江珧形态性状对重量性状的影响.渔业科学进展,2012,33(6):87-92
栉江珧形态性状对重量性状的影响
Effects of morphometric traits on weight traits of Atrina pectinta
投稿时间:2012-03-24  修订日期:2012-04-10
DOI:
中文关键词: 栉江珧  形态特征  通径分析  回归方程
英文关键词: Atrina pectinta  Qualitative trait  Path analysis  Multiple regression
基金项目:山东省科技发展计划项目(2010GHY10513)、山东省自然科学基金项目(2009ZRB02158)和中央级公益性科研院所基本科研业务费专项(20603022011013)
作者单位
白临建 农业部海洋渔业可持续发展重点实验室中国水产科学研究院黄海水产研究所青岛 266071上海海洋大学水产与生命学院201306 
杨爱国 农业部海洋渔业可持续发展重点实验室中国水产科学研究院黄海水产研究所青岛 266071 
周丽青 农业部海洋渔业可持续发展重点实验室中国水产科学研究院黄海水产研究所青岛 266071 
吴彪 农业部海洋渔业可持续发展重点实验室中国水产科学研究院黄海水产研究所青岛 266071 
刘志鸿 农业部海洋渔业可持续发展重点实验室中国水产科学研究院黄海水产研究所青岛 266071 
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中文摘要:
      随机选取101只野生栉江珧,测量其壳长(SL)、壳宽(SW)、壳高(SH)、壳顶角(AG)4个形态性状和体重(WG)、软体重(WT)、闭壳肌重(WM)3个重量性状,采用相关分析和通径分析方法得出了不同形态性状对重量性状的影响效果。结果表明,除壳顶角与闭壳肌重的相关系数不显著外,其余形态性状与重量性状间的相关系数均达极显著水平(P<0.01);壳高对重量性状的直接作用和间接作用均较大,是影响重量性状的主要因素;壳长和壳宽通过壳长对重量性状的间接作用较大,直接作用较小,是影响重量性状的两个次要因素;利用逐步回归分析建立了栉江珧形态性状关于体重(Y=69.112SH+52.823SW-751.367)、软体重(Y=37.161SH+43.404SW+4.111SA-614.096)和闭壳肌重(Y=4.275SH-18.610)的最优回归方程。
英文摘要:
      Seven morphometric traits and weight traits of wild Atrina pectinta, including shell length (SL),shell width (SW), shell height (SH), live body weight (WG), tissue weight (WT), adductor muscle weight (WM) and shell dip angle(AG), were measured. The relationships between these morphological traits (SL, SW, SH, and SA) and weight traits (WG, WT, and WM) were evaluated by correlation analysis and path analysis. Traits such as SL, SW, SH and SA were used as independent variables, while WG, WT and WM were used as a dependent variables. It was found that correlation coefficients between morphometric traits (SL, SW, and SH) and weight traits (WG, WT, and WM) were significantly different (P<0.01). Shell height, as a key effective factor, had predominant direct impact and indirect impact on weight traits. Shell length and width, as two secondary factors, showed significant indirect impact through shell height and slight direct impact on weight traits. The morphometric traits having significant impact on weight traits were used to establish the multiple regression equations of WG, WT and WM: Y=69.112SH+52.823SW-751.36, Y=38.485SW-472.912, Y=4.275SH-18.610.The results provide a theoretical tool for genetic breeding study of A. pectinta.
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