N.A. Ouchene-Khelifi*, N. Ouchene
Veterinary sciences institute, Saad Dahleb University, Blida 1, road of Soumaa, B.P. 270, Blida 09000, Algeria
(Manuscript received 24 September 2020; accepted for publication 31 March 2021)
Abstract. The objective of this study was to develop statistical models to predict body weight from goat’s body measurements. Data on 1702 goats for circumferences of chest (CG), abdominal circumference (AC) and spiral circumference (SC), height at withers (WH), body length (BL), and body weight (BW) were analysed to study the relationship between linear body measurements and body weight. The present study revealed that in the goats from all breeds studied (Arabia, Makatia, Kabyle, M’zabite, Saanen and Alpine), the weight evolved in the same direction and at the same rate as the linear measurements chosen. The linear measurements were all significantly correlated with animal weight (p<0.001). Results indicated that Arabia goats had the highest WH (71.07 cm) and CG (17.72 cm). The highest measurements were reported in Alpine goats for AC (97.73 cm), BL (78.05 cm), SC (106.29 cm) and BW (41.60 kg). The Kabyle breed were recorded with the lowest values for the WH (64.95 cm), BL (67.58 cm) and BW (29.52 kg). The average live weight was 38.15±10.90 kg with differences according to age, sex and breed (Arabia, Makatia, Kabyle and M’Zabite). Positive and highly significant (p<0.001) correlations were observed between BW and the majority of independent variables. The highest relationship was illustrated between CG with BW (r=0.922). Linear regression analyses were performed to develop the models. The simple regression analysis found all parameters to be significant (p<0.001) (WH, BL, CG, AC and CS) and CG gave more precision on the weight when using a single measurement parameter (R2 varied between 0.950 and 0.967). Therefore, the following formula can be used to estimate the live weight of the animals using only the chest circumference (P=75*CG). The development of these equations would enable producers and researchers to predict the animal body weight and develop strategic plans for the relevant goat herds.