Work

1 H‐Nuclear Magnetic Resonance Metabolic Profiling of Pantaneiro and Curraleiro Beef Breeds: Unveiling Adaptation Mechanisms in Brazilian Livestock

Year: 2026

Type: article

Abstract: This study provides the first metabolomic characterization of serum from Pantaneiro and Curraleiro beef cattle, unveiling their unique adaptations to the Pantanal and Cerrado biomes of Brazil. Blood was collected during the summer season to capture metabolic responses to extreme environmental conditions, including high temperatures and varying humidity. Metabolomics on serum samples were analyzed using nuclear magnetic resonance ( 1 H‐NMR) spectroscopy; the spectra were processed using Chenomx NMR Suite software v.10. The processed data were analyzed using partial least squares discriminant analysis to identify key metabolites, separating the two breeds. Forty‐four metabolites were identified in serum samples collected from 27 animals (14 Pantaneiro in Pantanal Biome and 13 Curraleiro in Cerrado Biome), of which 33 exhibited significant differences between the breeds. Pantaneiro cattle exhibited elevated levels of betaine, 2‐hydroxybutyrate, and glycolate, indicative of adaptations to oxidative stress, osmoregulation, and metabolic efficiency under the humid and flood‐prone Pantanal biome. Conversely, Curraleiro cattle showed higher concentrations of valine, glutamate, acetate, and citrate, highlighting nutrient efficiency and energy metabolism, critical for survival in the nutrient‐poor and arid Cerrado biome. Elevated lactate levels in both breeds suggest shared adaptations to hypoxic or high‐energy demand conditions. This research reveals the biochemical underpinnings of the resilience of these breeds, providing additional knowledge about metabolic strategies for enhancing stress tolerance and productivity in extreme environments. The findings underscore the value of metabolomics for understanding livestock adaptation and contribute to the development of climate‐resilient livestock systems.

Source: New Zealand Journal of Agricultural Research

DOI: 10.1002/jag2.70001