The development of a body weight prediction method for Ongole Crossbred cattle using a meta-analysis and field experiment approach

This study aims to develop and validate a model for predicting the body weight (BW) of Ongole Crossbred (OC) cattle using body measurements. To achieve this, a combination of meta-analysis and field experiments was employed. The meta-analysis involved identifying relevant keywords and databases, reviewing titles and abstracts, extracting data, and subsequently tabulating and analyzing the data. A total of 1,141 animal records were included in the quantitative synthesis process. Following the meta-analysis, a BW prediction model for OC cattle was developed. The model incorporated recommendations obtained from the meta-analysis, considering body measurement, age, and sex. Data from 507 animals were utilised to construct the model. Finally, a field experiment was conducted on 35 animals to assess the accuracy of the model. The meta-analysis revealed that body volume (BV) (r=0.96) and heart girth (HG) (r=0.89) exhibited stronger correlations with BW compared to body length (BL) (r=0.68). Linear regression modeling of OC cattle BW, demonstrated that HG yielded high correlation coefficients for both male (r=0.98) and female (r=0.94) cattle. Similarly, BV showed strong correlations for male (r=0.99) and female (r=0.95) cattle. Furthermore, the analysis revealed that both HG and BV were effective predictors across different age groups, with high correlation coefficients observed for cattle aged 1-12 months and over 24 months. The field experiment confirmed the high reliability of the model, achieving an accuracy of 90.8 for HG and 91 for BV. In conclusion, HG and BV are strong predictors of OC cattle BW, with categorization by breed further improving prediction accuracy. © 2025, Chiang Mai University - Faculty of Veterinary Medicine. All rights reserved.