Statistical models based on morphometric traits for body weight prediction in four dog breeds raised in Algeria

Abstract

The present study aims to evaluate the morphological difference between sexes in four dog breeds: Belgian Shepherd Malinois, Siberian Husky, Algerian Sloughi, and German Shepherd. On the other hand, we are aiming to determine the correlation between live weight and body measurements according to the breed and to the breed and sex. 312 dogs belonging to four different breeds were used: Belgian Shepherd Malinois (36 females and 44 males), Siberian Husky (31 females and 33 males), Algerian Sloughi (41 females and 59 males), and German Shepherd (32 females and 36 males). Eleven body measurements and live weight were used. Multiple linear regression models have been proposed using some body measurements in order to predict the live weight of dogs. Among the multiple regression models formed, the highest coefficients of determination (R2) were obtained from the models in males German Shepherd using Height at Withers (HW), Head Width (HEW), Muzzle Length (ML) and Chest Girth (CG) together with a coefficient of determination (R2= 0.996) and a Lin’s concordance correlation coefficient (CCC = 0.998). We demonstrated in this study that the live weight of the four dog breeds could be estimated with a high degree of accuracy using some body measurements and statistical methods after checking the variance inflation factor to eliminate the error rate.