Multiphasic nonlinear mixed growth models for laying hens

Abstract

Appropriate evaluation of BW and gain during rearing is required for optimal extended laying performance in laying hens. The objective of this study was to compare monophasic, diphasic, and triphasic Gompertz and logistic models describing BW and gain in individually fed free-run laying hens and to study the variation between individuals in shape parameters. Fifteen Lohmann Brown Lite hens were fed ad libitum from week 0 to 43 with a precision feeding system, measuring feed intake and BW individually in a group housed setting. Random variables related to mature weight and timing of maximum gain during the pubertal growth phase were introduced into the multiphasic model for BW with the best fit. For both the weight-age and gain-age functions, the diphasic and triphasic Gompertz and logistic model models fitted the data better than the monophasic models. The Gompertz model was able to identify the ages at the highest gain at similar time points for both BW and gain, whereas the logistic models failed to do so. The derivative of the multiphasic Gompertz models for the gain-age relationship identified age at the highest gain at similar ages as compared with the logistic models for gain. The mixed models predicted that the individual mature BW ranged from 1.83 kg to 2.10 kg and the variability in the timing of the highest rate of gain during the pubertal growth spurt ranged from 15.26 wk to 19.79 wk. Including random terms associated with the mature BW and the second inflection point of the diphasic Gompertz growth model allowed for identification of variability in the growth curve shape between individuals, which can be a tool to study the relationship between the individual growth curve shape and performance parameters.

Growth curve mixed nonlinear models in quails

“…The flaws in the process of convergence in nonlinear mixed models were also verified by Galeano-Vasco et al [58], van der Klein et al [59], Aggrey [60] when studying the Brody and Von Bertalanffy models with random effects for the growth curve in commercial laying hens.…”

The genetic architecture of trait covariation in Populus euphratica, a desert tree

“…The relationship is a trade-off made by trees after they adapt to the external environment, which largely depends on their internal biological mechanisms. The multiphasic growth model shows that the growth of most organisms is composed of multiple “S”-shaped phases, which is superior to single-phase growth ( Koops, 1989 ; Van der Klein et al., 2020 ; Gong et al., 2021 ). The seedling stage of trees is a “S”-shaped phase.…”

Genetic Architecture of Multiphasic Growth Covariation as Revealed by a Nonlinear Mixed Mapping Framework

“…Koops proposed a multiphasic growth model, which is superior to singlephase growth in many studies and has been shown to more accurately estimate growth parameters (Koops, 1987;Grossman and Koops, 1988;Kwakkel et al, 1993). For example, Van der Klein et al (2020) compared the monophasic, diphasic, and triphasic Gompertz and logistic models to describe the weightage and gain-age functions of hens, and the results showed that the diphasic and triphasic Gompertz and logistic models yielded better fitting effects than the monophasic models. In addition, Treves et al (2017) studied the multiphase growth pattern of the green alga Chlorella ohadii and metabolic changes during the growth phases.…”