Bioeconomic modeling of cattle breeding systems: sensitivity analysis and production scenarios in native grasslands of Paraguay

Abstract

This study evaluates the profitability of two cattle breeding operations located on native rangelands in Paraguay, using a deterministic simulation model as a technical and economic decision-support tool. The analysis focused on the variation of three key productive indicators: pregnancy rate, weaning calf weight and price, and the sale category of cull cows. These parameters were modified in hypothetical ±10% scenarios to estimate their impact on the system’s Gross Margin (GM). Results revealed that a 10% increase in the pregnancy rate led to a 121% improvement in GM, while upgrading cull cows from lean to fat categories increased profitability by up to 141%. In contrast, variations in calf price and weight also positively influenced GM, but with a smaller effect (34%–66%). These findings emphasize the high economic sensitivity of cow-calf operations to improvements in reproductive and herd management efficiency. The study concludes that process technologies particularly those related to reproductive performance have a greater influence on profitability than market-driven price changes. Moreover, the structured use of technical and administrative data enabled scenario simulations without the need for field implementation, supporting informed decision-making in the face of environmental and economic variability. This approach underscores the value of integrating simulation and sensitivity analysis tools into the strategic management of extensive cattle breeding systems.