02014naa a2200241 a 450000100080000000500110000800800410001902400540006010000170011424500900013126000090022152012980023065000200152865000280154865000170157665000140159365000180160765300310162565300270165670000190168370000200170277300500172221686322024-10-30       2024    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.1016/j.livsci.2024.1055512DOI1 aGOMES, A. P.  aBeef cattle mating recommendation based on bioeconomic models.h[electronic resource]  c2024  aRecognizing the pivotal role of mating in animal breeding, this study strives to establish a robust strategy for recommending optimal matings among bovines. This strategy is built to maximize a single value derived from the economic selection index of full-cycle system in Brangus cattle. The study endeavors to apply computational methodologies to explore economically significant traits comprehensively, thereby leading to amplified financial gains for Brangus cattle breeders. Anchored within this overarching objective, a strategic deployment of a genetic algorithm is employed to formulate mating recommendations that precisely align with the priority traits designated by the genetic evaluation program of the Brazilian Brangus Association (BBA). The data set of the BBA for the simulations in this study encompass a range of selection criteria, including: i) birth weight; ii) mature cow weight; iii) ribeye area; iv) subcutaneous fat thickness; v) subcutaneous fat thickness at the rump; vi) escape speed; vii) nematode egg count per gram of feces; and viii) tick count. The research findings underscore that the recommendations provided by the computational strategy converge to increase the bioeconomic index while controlling the trade-off between this index and progeny inbreeding.  aAnimal breeding  aArtificial intelligence  aAcasalamento  aCriação  aGado de Corte  aCombinatorial optimization  aEvolutionary computing1 aCAMARGO, S. S.1 aYOKOO, M. J. I.  tLivestock Sciencegv. 289, 105551, Nov. 2024.