Assessing reproductive performance and predictive models for litter size in Landrace sows under tropical conditions

Abstract

Objective: Litter size and piglet loss at birth significantly impact piglet production and are closely associated with sow parity. Understanding how these traits vary across different parities is crucial for effective herd management. This study investigates the patterns of the number of born alive piglets (NBA), number of piglet losses (NPL), and the proportion of piglet losses (PPL) at birth in Landrace sows under tropical conditions. Additionally, it aims to identify the most suitable model for describing these patterns.Methods: A dataset comprising 2,322 consecutive reproductive records from 258 Landrace sows, spanning parities from 1 to 9, was analyzed. Modeling approaches including 2 nd and 3 rd degree polynomial models, the Wood gamma function, and a longitudinal model were applied at the individual level to predict NBA, NPL, and PPL. The choice of the best-fitting model was determined based on the lowest mean and standard deviation of the difference between predicted and actual values, Akaike information criterion (AIC), and Bayesian information criterion (BIC).Results: Sow parity significantly influenced NBA, NPL, and PPL (p<0.0001). NBA increased until the 4 th parity and then declined. In contrast, NPL and PPL decreased until the 2 nd parity and then steadily increased until the 8 th parity. The 2 nd and 3 rd degree polynomials, and longitudinal models showed no significant differences in predicting NBA, NPL, and PPL (p>0.05). The 3 rd degree polynomial model had the lowest prediction standard deviation and yielded the smallest AIC and BIC.