Use of body linear measurements to estimate liveweight of crossbred dairy cattle in smallholder farms in Kenya

• Published in: SpringerPlus Vol. 5; no. 1; p. 63
• Main Authors: Lukuyu, M. N., Gibson, J. P., Savage, D. B., Duncan, A. J., Mujibi, F. D. N., Okeyo, A. M.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 22-01-2016; Springer Nature B.V
• Subjects: Biomedical and Life Sciences; Humanities and Social Sciences; multidisciplinary; Science; Science (multidisciplinary); Crossbreeds; Dairy cows; Small-scale farmers; Body weight; Liveweight prediction
• ISSN: 2193-1801; 2193-1801
• DOI: 10.1186/s40064-016-1698-3

Body linear measurements, and specifically heart girth (HG), have been shown to be useful predictors of cattle liveweight. To test the accuracy of body linear measurements for predicting liveweight, crossbred dairy cattle of different genotypes were measured and weighed. A total of 352 mature cows and 100 heifers were weighed using an electronic weighing scale and measurements of HG, body length, height at withers were taken using an ordinary measuring tape and body condition scored (BCS) using a five-point scale. The animals were grouped according to genotype and age. Genotype classification was undertaken from farmer recall and by visual appraisal as 40–60, 61–80 or 81–100 % exotic (non-indigenous). Age classification was simply as mature cows or heifers. Liveweight of the animals ranged from 102 to 433 kg. Liveweight was strongly correlated with HG (r = 0.84) and body condition scores (r = 0.70) and moderately correlated with body length (r = 0.64) and height at withers (0.61). Regressing LW on HG measurements gave statistically significant (P < 0.01) equations with R
2
ranging from of 0.53 to 0.78 and residual standard deviation ranging from 18.11 to 40.50 kg. The overall model developed (adjusted R
2
 = 0.71) had a prediction error of 26 kg (or 11 % of the mean) and predicted LW of over 95 % of crossbred dairy cattle in the range of 100–450 kg, regardless of age and breed group. Including BCS in the model slightly improved the model fit but not the prediction error. It was concluded that the model can be useful in making general management decisions in smallholder farms.