Morphological Indices and Simple Regression to Predict Live Body Weight from Morphological Traits of Indigenous Sheep

The data on 14 morphological trait measurements were obtained from 291 indigenous sheep found in the southern Punjab of Pakistan. Ten various body indices were obtained from 14 morphological traits. Pearson correlations between live body weight and 13 other morphological traits obtained to analyze the nature and strength of the relationship. Simple regression models were fitted to predict live body weight from 13 other morphological traits as independent variables. Descriptive statistics of body indices and morphological traits were also reported. The variation pattern was observed by coefficient of variation in both body indices and morphological traits. In body indices less variation was observed in BeronCrevit index, having a smallest coefficient variation of 8.50% and high variation in Area Index having largest coefficient of variation 23.98%. Similarly, in morphological traits less variation was observed in ear length, which had the smallest coefficient variation of 3.3%. The high variation pattern was observed in head width and percent weight, having the two largest coefficients of variations being 28.5% and 28.2%, respectively. As there was high Pearson correlation between live weight and barrel depth, the best regression model was on barrel depth with a high R-2 of 0.938. The simple regression analysis shows that barrel depth is best predictor of live body weight.

Automated summary

This study collected data on 14 morphological traits from 291 indigenous sheep in southern Punjab, Pakistan. The nature and strength of the relationship between live body weight and other morphological traits were analyzed using Pearson correlations. Regression models were built to predict live body weight based on 13 independent morphological traits. The study also reported descriptive statistics of body indices and morphological traits. The results showed significant variation in both body indices and morphological traits, with barrel depth being the best predictor of live body weight.