Correlation and Path Analysis on Morphometric Traits and Body Weight for Adult Chinese Mitten Handed Crab(Eriocheir sinensis)from Yellow River Delta
In order to find out the important morphological traits affecting the body weight of adult Chinese mitten handed crab(Eriocheir sinensis)in Yellow River Delta and provide reference for the breeding of new varieties of Chinese mitten handed crab in Yellow River Delta,a total of 247 mature hairy crab were randomly sampled,and four appearance morphological traits,including the carapace length(X1),carapace width(X2),and the body height(X3),and meropodit length of the third periopod(X4)were measured,with record of the body weight(Y).Through correlation analysis,multiple regression analysis and path analysis,the multiple linear regression equation between morphological traits and body weight was established,and the correlation coefficient,path coefficient and determination coefficient of morphological traits were obtained.The results showed that the relationship between morphological traits and body weight was detected with significantly positive correlation(P＜0.01).Based on regression analysis,the optimal multiple linear regression equation was established as Y=-328.06+5.43X2+2.43X4.The path analysis revealed that there was the maximal direct effect of carapace width on the body weight,and the greater direct effect than the indirect effect,indicating that the width of the carapace width was the main morphological trait affecting the body weight of the adult individuals of the crab.Therefore,the main selection morphological trait should be the carapace width(X2),and the meropodit length of the third periopod(X4)to selective breed of adult Chinese mitten handed crab with large body weight in Yellow River Delta.The findings are used in production practice and provide basic data for the breeding of Chinese mitten handed crab in Yellow River Delta.
Yellow River DeltaChinese mitten handed crab(Eriocheir sinensis)morphological traitbody weightcorrelation analysispath analysis
NETL
NSTL
万方数据
