Regression Analysis between Body Weight and Body Size of Large-tail Sheep
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The phenotype correlation between body size and body weight,the direct and indirect effect of body size on body weight of Henan's large-tail sheep were analyzed with SAS software,and the optimum regression equation was established subsequently.The results indicated that body weight and chest girth were the major body size factors affecting the body weight of Henan's large-tail sheep.Therefore,besides body weight selection,the body height and chest girth selection should be strengtheaed at the same time.Keywords:
Girth (graph theory)
Body height
Lower body
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The SPSS was utilized in this article to separately analyze the correlation of body size and weight in the adult Dazu black goats,the direct and indirect influence of body size to body weight,and the decision degree of body size to body weight.Finally optimum regression mode was established about body weight and body size.The result was indicated: chest width and cannon circumference is the most significant factors that influenced the ram's body weight;the chest circumference is the most significant factor that influenced the ewe's body weight.The ram optimum regression equation was: Y=19.630-0.940X6 + 4.346X7,the ewe optimum regression equation was: Y=-17.942 + 0.661X4.
Circumference
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In order to research the correlation between body size and body weight of Huai goat and help selection and breeding,the determination results of body size and body weight of 179 Huai goats were analyzed by SPSS software with path analysis and correlation analysis,and the optimum regression equation was established.The results showed that there was a significant positive correlation(P0.01) between body weight(■) and body size(body height(X1),body length(X2),the chest girth(X3),the chest width(X4) and the chest depth(X5).The body weight was extremely affected by the direct action and indirect action of body height,body length,chest girth and chest width.The optimum regression equation was: ■ =0.353X1+0.316X2+0.234X3.
Girth (graph theory)
Body height
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This study aimed at evaluating the relationship between body weight and nine morphometric traits (withers height,rump height, body length, face length, rump length, chest circumference, head width, shoulder width and rumpwidth) of Uda sheep using regression tree technique. The data for the study were generated from 499 Uda ramsrandomly selected from different herds in Nasarawa State, north-central Nigeria. Pearson’s moment correlation (r)between body weight and morphometric traits ranged from moderate to high values (r = 0.43-0.76; P≤0.01). Basedon the importance of the independent variables in predicting the body weight of sheep, five body measurementsnamely; chest circumference, shoulder width, rump width, body length and face length were found to be moreefficient. Thus, they were the variables entered to obtain the optimal regression tree. Among these five variables,chest circumference was found to be the primary splitting variable; and together with face length accounted for about62% of the variation in body weight. The regression tree analysis indicated that animals with chest circumference >87.45cm or ≤ 94.05cm and face length > 28.85cm could be expected to have higher body weights. This informationcould be exploited by livestock producers for management, selection and genetic improvement of Uda sheep.
Tree (set theory)
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The relationship between the body weight of the Philippine native horse and its external body measurements such as height, hearth girth, midriff girth, flank g irth, and body length was determined. Possible equations for body weight estimation were constructed based on the said parameters. One hundred thirty three (133) female and 33 male apparently healthy Philippine native horses with age ranging from 4 months to 25 years old were used in the study. Regression analysis showed that a linear relationship exists between body weight and external body measurements. For the whole sample population, heart girth was found to be the best single predictor of weight. When combinations of parameters were used for predicting weight of the sample population, heart girth, midriff girth, body length 1 and height were found to be the best predictor of weight. Statistical analysis using t-test showed that a non-significant difference (P>O.05) exists between the actual weights and the estimated weights obtained using the derived formulae. Therefore, these formulae could be used to fairly estimate body weight in the absence of a suitable weighing scale.
Girth (graph theory)
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A total of 84 (41 males and 43 females) apparently healthy Philippine-born Thoroughbred horses two to 11 yrs old were weighed using a digital weighing scale and their external body measurements (height; heart girth; umbilical girth; body length 1=distance from point of shoulder to tuber ischium; and body length 2=distance from tuber ischium to olecranon) taken using a tailor’s tape measure to develop a method of weight determination based on the above external body parameters. Correlation analysis revealed a linear relationship between the external body measurements with the actual body weights of horses. Heart girth, as compared to the other external body measurements, has the strongest positive linear relationship with body weight (r=0.803), while body length 2 proved to be the least correlated (r=0.149). Heart girth was found to be the best single predictor of body weight for the male (r2=0.635), female (r2=0.714), and the combined population groups (r2=0.64). On the other hand, measuring the heart girth and umbilical girth increases the accuracy of weight determination in these animals to as much as 10 % (r2= 0.739). Multiple regression analysis revealed that the horses’ height and body length 1 are also significant (P Key words: body weight, correlation, regression, Thoroughbred horse
Girth (graph theory)
Equus
Body height
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The canonical correlation analysis was carried on 3 body weight traits and 5 body size traits in two groups from 577 Saba pigs by using SAS.The results showed that the first and second canonical correlation coefficients between body weight and size traits were significant(P0.01).They were 0.9532 and 0.3044 respectively,which represented 99.97% for the total correlation between 2 groups.The correlation between boby weight and body size traits was caused by the correlation between 2 boby weight traits(body weight for 4 and 6 months)and 2 body size traits(chest circumference and ham circumference for 6 months).The results also showed that the two canonical variables of body weight traits could predict body length,chest circumference and ham circumference for 6 months,and the 2 canonical variables also could predict body weight for 4 and 6 months effectivy.It indicated that the body weight would be increased when selecting on body size in practice.
Circumference
Canonical correlation
Canonical analysis
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145 seed ostriches(including 91 females,44 males) were used to measure their body weight,body size and performance indicators,and then analysis these data with correlation and regression analysis.The results indicated that: in females body weight is positively correlated with body height,body length,body width,neck length and the circumference;in males,body weight is positively correlated with body height,body length,body width,the circumference,and is negatively correlated with neck length;in female ostrich,there is significantly positive correlation only between laying performance and neck length,and less correlations between laying performance and body height、body weight、the circumference,and negative correlation between laying performance and body length,width.The regression equation between body weight and body size were established respectively both on male and female ostrich as follows: Y=-85.59+0.62X1+2.01X2+2.68X3(P0.05)(Y-weight X1-body length,X2-body width,X3 —circumference),and Y=-8.64+1.21X1+0.51X2+0.98X3(P0.05)(Y-weight,X1-body height,X2-body length,X3 —neck length).
Circumference
Positive correlation
Body adiposity index
Body height
Negative correlation
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Fifty 21-day-old white wing pigeons were used to measure their body weight,body size and slaughter performance indexes and then study these data with correlation and regression analysis.The correlation coefficients among body weight,body size and slaughter performance indexes were analyzed.The correlation coefficients between slaughter body weight and body slanting length,keel length,chest depth,chest width,shank length,body weight were 0.646,0.457,0.560,0.478,0.577,0.947 respectively(P0.01).Some regression equations were also constructed.
Keel
Positive correlation
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In order to research the correlation between body size and body weight of Henan small tail han sheep and dedicate to new breeding selection work.This paper analyzed the correlation between body size and body weight of 98 Henan small tail han sheep with the SPSS software,based on Path Analysis and Correlation Analysis,and establish the most superior regression equation.The results showed that the body weight(Y) with the body height(X1),the body length(X2),the heart girth(X3),the chest width(X4),chest depth(X5),tail width(X6) and tail length(X7) were significantly positive correlations(P0.01).The direct action and the indirect action of the body length,the heart girth,the chest width and chest depth were extremely maximum.The most superior regression equation was Y=0.226X2+0.535X3+0.200X4.
Girth (graph theory)
Body height
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In this research, linear regression models were improved for estimation of body weight using various linear body measurements from Sudanese Shugor sheep. Simple regression models were formed when Body weight (Bwt) was dependent variable and heart girth (HG), height at withers (HTW) and height at hip (HTH) as independent variables. The best derived regression prediction equation for estimation of body weight determinated by using beta (β) as the constant based on number of variables used for the equation, mean square error (MSE) and Coefficient of determination (R2). The model including the most appropriate measurements such as heart girth, height at wither and height at hip were the best fitted model (β = -47.54, MSE = 9.39 and R 2 =0.61) for estimation of
Withers
Girth (graph theory)
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