Meta-Analysis of Prediction Models for Weight Estimation of Philippine Native and Commercial Pigs Using External Body Measurements
Year: 2025
Type: review
Abstract: The study aimed to assess various models for accurately estimating the live weight of pigs. The research was driven by the need for cost-effective and accurate weight estimation methods, especially since most small-scale pig farmers lack access to weighing scales. Body measurements such as heart girth, body length, and body width were used as alternatives to traditional weighing techniques. The study used a 2x9 factorial design in a Randomized Complete Block Design (RCBD) with uneven samples using 112 native pigs and 195 commercial pigs, evaluating eight prediction models. Results indicated that heart girth was the most reliable predictor of actual body weight for both native and commercial pigs. The accuracy of weight prediction improved when body length, body width, and body height were added to the model, particularly for commercial pigs. Two models were found to be the most accurate for different pig breeds. For commercial pigs, prediction model 5 LW (kg) = -108.198 + 0.228 BL (cm) + 1.094 HG (cm)+ 0.267 BHT (cm) + 0.922 BWD (cm) showed high accuracy, while for Philippine native pigs, prediction model 8 = LW (kg) = -35.59+0.95 HG (cm) was the best fit. The study concluded that these models could significantly improve weight estimation and bargaining power for small-scale farmers, reducing profit losses due to weight underestimation.
Authors: Nora Cabaral-Lasaca, Monette Naagas
Language: English
Subfield: Agronomy and Crop Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
OpenAlex ID: W4408956172