Abstract

VELAZQUEZ-VILLALVA, Héctor Hugo; POSADAS-DOMINGUEZ, Rodolfo Rogelio; REBOLLAR-REBOLLAR, Samuel  and  BOBADILLA-SOTO, Encarnación Ernesto. Technical-economic optimization in the fattening of turkeys from commercial genetic lines in Temascaltepec, Mexico. Rev. mex. de cienc. pecuarias [online]. 2025, vol.16, n.3, pp.630-645.  Epub Dec 08, 2025. ISSN 2448-6698.  https://doi.org/10.22319/rmcp.v16i3.6876.

The objective of the study was to develop a combined approach of deterministic modeling and Monte Carlo simulation to establish the optimal technical-economic level for fattening commercial genetic lines of turkeys in the municipality of Temascaltepec, Mexico. Data from 42 turkeys of the double-breasted diamond genetic variety, with an average age of three weeks and an initial body weight of 1.077 ± 0.132 kg, were analyzed. In order to model the relationship between feed consumption and final weight of the turkeys, a quadratic production function was fitted using nonlinear regression along with a Monte Carlo simulation analysis to evaluate the risk associated with fluctuations in feed costs and the selling price of turkeys. The deterministic analysis identified that economic profitability is maximized when turkeys consume 26.81 kg of feed and reach a live weight of 11.30 kg. The Monte Carlo simulation confirmed the validity of these results under scenarios of uncertainty in sales prices and feed costs, estimating an average net profit of $379.29 per bird in the economic optimum, compared to $325.39 in the technical optimum, representing a 16.56 % increase in profitability per turkey. These findings confirm that integrating deterministic modeling with stochastic simulation constitutes an effective methodological tool for production decision-making under conditions of variability and uncertainty. It is recommended that this approach be validated in other agricultural contexts to strengthen its practical applicability.

Keywords : Economic analysis; Feed consumption; Nonlinear regression; Optimal economic level; Stochastic simulation.

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