Modelling of growth curves and estimation of genetic parameters for growth curve parameters in Peruvian young llamas (Lama glama)

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The objectives of this study were to describe the growth of young llamas by the application of four non-linear functions (Gompertz, Logistic, Von Bertalanffy and Brody), evaluate the importance of fixed (environmental) effects (sex, type of llama, month and year of birth) on growth curve parameters...

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Detalles Bibliográficos
Autores: Canaza Cayo, A. W., Huanca Mamani, Teodosio, Gutiérrez, Juan Pablo, Beltrán, P. A.
Formato: artículo
Fecha de Publicación:2015
Institución:Instituto Nacional de Innovación Agraria
Repositorio:INIA-Institucional
Lenguaje:inglés
OAI Identifier:oai:null:20.500.12955/1687
Enlace del recurso:https://hdl.handle.net/20.500.12955/1687
https://doi.org/10.1016/j.smallrumres.2015.01.026
Nivel de acceso:acceso abierto
Materia:Non-linear functions
Environmental effects
Genetic parameters
Heritabilities
Genetic correlation
Llamas
https://purl.org/pe-repo/ocde/ford#4.02.00
Descripción
Sumario:The objectives of this study were to describe the growth of young llamas by the application of four non-linear functions (Gompertz, Logistic, Von Bertalanffy and Brody), evaluate the importance of fixed (environmental) effects (sex, type of llama, month and year of birth) on growth curve parameters and finally estimate the genetic parameters for growth curve parameters (A: asymptotic body weight and k: specific growth rate). A total of 35,691 monthly body weight records from birth up to 16 months of age from 2675 young llamas, collected from 1998 to 2008 in the Quimsachata Experimental Station of the Instituto Nacional de Innovación Agraria (INIA) in Peru were used. Growth curve parameters were estimated by non-linear procedures while genetic parameters were estimated by application of a bivariate animal model and the restricted maximum likelihood (REML) method. All non-linear functions closely fitted actual body weight measurements, while the Gompertz function provided the best fit in describing the growth data of young llamas. All environmental effects significantly influenced the asymptotic weight (A), while the specific growth rate (k) was only affected by the month and year of birth. Heritability estimates for parameters A and k were 0.10 and 0.01, respectively. Genetic correlation between A and k was high and negative (−0.82), indicating that a rapid decrease in growth rate after inflection point is associated with higher mature weight. Despite the low heritability estimates obtained herein, slight genetic gain(s) were observed in the current study suggesting that a selection program to change the slope of the growth curve of llamas may be feasible.
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