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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Multiphasic nonlinear mixed growth models for laying hens.

S A S van der Klein1, R P Kwakkel2, B J Ducro2

  • 1Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada.

Poultry Science
|November 4, 2020
PubMed
Summary

Understanding body weight (BW) and gain in laying hens is key for performance. This study found multiphasic Gompertz models better describe individual hen growth curves than simpler models.

Keywords:
gaingrowthlaying henmodeling

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Area of Science:

  • Animal Science
  • Agricultural Science
  • Quantitative Biology

Background:

  • Optimal laying hen performance requires accurate monitoring of body weight (BW) and growth during rearing.
  • Growth modeling is essential for understanding and predicting animal development in poultry production.

Purpose of the Study:

  • To compare monophasic, diphasic, and triphasic Gompertz and logistic models for describing BW and gain in individually fed laying hens.
  • To investigate individual variations in growth curve shape parameters.

Main Methods:

  • Utilized a precision feeding system to individually measure feed intake and BW in 15 Lohmann Brown Lite hens from week 0 to 43.
  • Applied monophasic, diphasic, and triphasic Gompertz and logistic growth models to weight-age and gain-age data.
  • Incorporated random variables for mature weight and timing of maximum gain into multiphasic models.

Main Results:

  • Diphasic and triphasic Gompertz and logistic models provided a better fit to BW and gain data than monophasic models.
  • The Gompertz model accurately identified peak gain timing for both BW and gain, unlike logistic models.
  • Mixed models predicted mature BW between 1.83-2.10 kg and peak gain timing between 15.26-19.79 weeks.

Conclusions:

  • Multiphasic Gompertz models effectively capture individual growth variability in laying hens.
  • Identifying individual growth curve shapes can be a valuable tool for correlating growth with performance parameters.
  • This approach aids in optimizing rearing strategies for improved laying hen productivity.