Path coefficient and path analysis of body weight and biometric traits in indigenous goats

Abstract

The study was conducted in Sekhukhune District of the Limpopo province, South Africa where the goats between the ages of 20 and 30 months were used. A total of 613 indigenous goats of both sexes (62 male and 551 female) were selected and body weight and four morphological traits were taken on each goat in the morning before they were released for grazing. Means, standard deviations (SD) and coefficients of variation (CV) were calculated. Pair wise correlations among body weight and morphological traits were also determined which ranged from 0.81-0.91 for male and 0.72-0.89 for female goats, respectively and were statistically significant (P<0.01). The direct effect of heart girth on body weight was strongest in both sexes (path coefficient of 0.58 and 0.62 in males and females, respectively). Body length in males and body length and hip height in females also positively (P<0.05) influenced body weight. The direct effects of other linear type traits on body weight in both sexes were non-significant. The forecast indices obtained in this study could aid in weight estimation, selection and breeding programmes.

Karacabey Merinosu Koyunlarında Canlı Ağırlık İle Vücut Ölçüleri Arasındaki İlişkilerin Path Analizi Yaklaşımı İle İncelenmesi

“…This finding shows similarity with findings of other studies that examined the relationships between live weight and body measurements [6,8,10,[28][29][30] .…”

“…It was also reported in other studies with similar purposes [10,[29][30][31] that chest girth has the highest level of effect on live weight.…”

“…Here, P YX k : path coefficient, S X k : standard deviation of the independent variable , S Y : standard deviation of the dependent variable Y, and b k : partial regression coefficient [10] .…”

“…While the degree and direction of the relationship can be determined with correlation analysis in this case, regression analysis can be used when estimating live weight with body measurements. However, effects among variables in the correlation and regression analysis cannot be sufficiently explained as they can be also shaped by a third variable [10] . With developments in the area of computers in recent years, multivariate methods, which have been developed as alternatives to situations where correlation and regression analyses fall insufficient in analyzing relationships among complex variable structures, have become applicable.…”

“…Path analysis is utilized when identifying the causal (direct or indirect) and non-causal (unanalyzed and spurious) effects of one variable on another and breaking variables' correlation coefficients into the components of those variables [6,11] . Path analysis is a subset of structural equation models and presents itself as a methodology complementary to multiple regression model which helps determining the explanatory variable that affects the response variable more [10,12] . The purpose of this study was to identify direct and indirect effects between live weights and several body measurements of Karacabey Merino sheep bred at Karacabey Agricultural Enterprise and to evaluate the model set with different goodness of fit criteria.…”