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Article . 2025 . Peer-reviewed
Data sources: Crossref
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Modelos no lineales en curvas de crecimiento de conejos

Authors: José Ángel Pérez Ramírez; Fernando González Cerón; Diego Zárate Contreras; José Guadalupe Herrera Haro; Eliseo Sosa Montes; Sergio Iban Mendoza Pedroza; Arturo Pro Martínez;

Modelos no lineales en curvas de crecimiento de conejos

Abstract

El progreso de la cunicultura mexicana se ha visto limitado por diversos factores, a pesar de ello la actividad cunícola ha ido mejorando en las últimas décadas, desarrollando avances tecnológicos en las áreas de nutrición e instalaciones, sin embargo, se cuenta con pocos avances en la mejora genética de la especie, constituyéndose en un factor limitante al desconocer las características que permitan una mejor productividad y, consecuentemente, una mayor rentabilidad. Para evaluar el desempeño productivo de una población cunícola, se requiere de información sobre el crecimiento de los animales para desarrollar modelos de fácil interpretación gráfica como las curvas de crecimiento. Por lo tanto, el empleo de ecuaciones matemáticas no lineales cobra importancia; ya que permiten el estudio e interpretación de ciertos procesos biológicos, como la descripción del cambio del peso de los animales en función de un tiempo determinado. La mayoría de investigaciones que relacionan modelos no lineales con el crecimiento de conejos, muestran ajustes a un rango de edades de los 30-35 días de edad hasta los 84-91 días; generando por lo menos 3 parámetros para comparar y seleccionar el modelo con un mejor ajuste.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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