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一龄栉孔扇贝壳长与壳高对湿重的相关性和通径分析 被引量:14

Correlation and Path Analysis on Shell Length and Shell Heightto Wet Weight of Chlamys Farreri at One-year Old
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摘要 为了查清栉孔扇贝数量性状的相关性和影响湿重的因素以及各因素所占的比例。选取栉孔扇贝春季升温苗种进行为期6个月680组扇贝形态学数据的跟踪,测定壳长、壳高、湿重,计算相关系数,采用通径分析方法计算了以壳长和壳高为自变量对湿重的相关系数,通径系数和决定系数。结果表明:其壳长和壳高对湿重的相关系数达到极显著水平(P<0.01)。壳高对湿重的直接影响最大P1=0.867,是影响湿重的主要因素,壳高对湿重的直接影响则较小P2=0.080,间接作用较大(0.862),壳高通过壳长间接的影响湿重,壳长与壳高对湿重的回归系数为R2=0.897。采用回归分析的方法建立壳长和壳高对湿重的多元回归方程为:W=-0.842+0.099SL+0.009SH。该结果为栉孔扇贝选育种提供了理论依据,即以提高湿重为目标,主要选择壳长,同时加强对壳高的协同选择。 To clarify correlation among quantitative traits and compositions influencing wet weight and the ratio of influence, the shell length, shell height and wet weight of 675 individuals that produced in the spring were measured during six months. The correlation coefficient matrix, path coefficient and determination coefficient of was calculated with path analysis. The shell length, shell height was used as the independent variables and wet weight was used as the dependent various for path analysis. The results showed that the correlation coefficient matrix between shell character and wet weight were all very significantly different (P〈 0.01). Shell length gave predominant direct effect (P~=0.867) on the wet weight, it is the key effective factor. Shell height gave slightly direct effect (P2=0.080) and significant indirect effect (0.862) through shell height on the wet weight. The multiple correlation matrix between shell length, shell height and wet weight was ff=0.897. The multiple regression equation relating the wet weight was W=-0.842 + 0.099SL+ 0.009SH. The results provided a theoretical basis for selective breeding in C. Farreri, that was shell height should be firstly selected and shell length should be simultaneously selected in order to improve wet weight.
出处 《中国农学通报》 CSCD 2012年第20期136-139,共4页 Chinese Agricultural Science Bulletin
基金 中央级公益性科研院所基本科研业务费专项(20603022011003 YJ2010-02) 国家"863"计划项目(2012AA10A405-2) 国家863计划项目(2012AA10A405-2) 十二五支撑计划课题(2011BAD13B06)
关键词 栉孔扇贝 壳长、壳高、湿重 相关性 通径分析 多元回归 Chlamys Farreri shell length, shell height, wet weight correlation analysis path analysis multiple regression
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