Dairy cattle

Genotype-by-Environment Interaction in Dairy Systems: Modelling the Effect of Feeding Strategies on the Lifetime Productivity of Contrasting Cattle Breeds

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Abstract

This study aimed to examine whether genetically distinct dairy cattle breeds respond differently to changes in nutritional conditions and to quantify genotype-by-environment (GxE) interactions in relation to lifetime productivity. Data were collected from three cattle breeds that differ in genetic potential for milk yield: Sahiwal (n = 20; locally adapted with lower genetic merit), Crossbred (n = 10; intermediate genetic merit), and Holstein Friesian (n = 15; higher genetic merit).The dataset recorded breed and age, along with milk yield, body weight at key stages of development, and the length of each lactation. Feeding strategies were defined as an environmental factor and combined with animal traits to improve the LIVSIM model's predictions of genotype-by-environment outcomes. LIVSIM model was used to analyze data and simulate productivity under different feeding scenarios. Model prediction accuracy was high (MSPE = 0.010 to 3.31). Results revealed significant (P< 0.05) genotype-driven differences in productivity trajectories: Sahiwal cows peaked at 9-11 kg/day, Crossbreds at ~10-13 kg/day, and Holstein Friesians at 15-17 kg/day. Most importantly, the feeding scenario analysis demonstrated a clear GxE interaction: High-protein diets improved yield and persistency most markedly in high-genetic-merit Holsteins, indicating a greater capacity to utilize improved nutrition. In contrast, low-protein rations led to early and steep declines in this same group, suggesting that high genetic potential for yield is more vulnerable to suboptimal environments. The Sahiwal breed showed more stable performance across diets, highlighting genetic adaptation to variable conditions. These findings confirm that optimal feeding strategies are genotype-dependent and demonstrate LIVSIM's reliability in modeling these complex GxE interactions for precision dairy management.

Keywords: 2026

How to Cite:

Ahmad, S., Hyder, A., Riaz, M. & Zubair, M., (2026) “Genotype-by-Environment Interaction in Dairy Systems: Modelling the Effect of Feeding Strategies on the Lifetime Productivity of Contrasting Cattle Breeds”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2295584. doi: https://doi.org/10.31274/wcgalp.24346

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