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Body Measurements and Body Condition Scoring as Basis for Estimation of Live Weight in Nili-Ravi Buffaloes
 
Muhammad Tariq1, Muhammad Younas2, Abdul Basit Khan2 and Eva Schlecht1*
1Animal Husbandry in the Tropics and Subtropics, University of Kassel and Georg-August-UniversitätGöttingen, Steinstrasse 19, 37213 Witzenhausen, Germany; 2Department of Livestock Management, University of Agriculture Faisalabad, Pakistan *Corresponding author: tropanimals@uni-kassel.de

Abstract   

Implementation of management recommendations for the Nili-Ravi buffalo in small- and medium scale commercial dairy production systems in Pakistan is hampered by difficulties to determine body weight (BW) of the animal. A workable and reliable method of predicting BW of this breed by using body measurements and body condition scoring (BCS) was therefore explored.Nili-Ravi buffaloes (n=211)were divided into three age groups (1-3 years = G1; >3-8 years = G2; >8 years = G3). Animals were weighed on a mechanical scale and their heart girth (HG), body length (BL) and shoulder height (SH) was measured. In addition, BCS was performed using a 5 point scale. Recorded data were subjected to simple and multiple linear regression analysis.The overall mean values of BW, HG, BL, SH and BCS were 359±160.9 kg, 170±30.1 cm, 130±19.2 cm, 125±14.5 cm and 3.8±0.77. With correlation coefficients (r) of 0.97 (HG), 0.94 (BL), 0.93 (SH) and 0.43 (BCS), the relationship between the individual independent variable with BW were significant (P<0.01) in all cases. The multiple linear regression between BW and HG, BL and BCS was highly significant (P<0.001) for each of the three groups (G1: r²=0.95, G2: r²=0.86, G3: r²=0.83).Buffalo farmers who lack mechanical or electronic scales to regularly determine BW of their animals can thus combine simple morphometric body measurements (HG, BL) with BCS or just rely on HG in order to calculate feed requirements, monitor growth, determine breeding age, marketing weight and estimate the animals’ cash value.

Key words: Morphometric measurements, Multiple linear regression analysis, Water buffalo

 
   

ISSN 0253-8318 (Print)
ISSN 2074-7764 (Online)



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