Modeling the growth of the Goettingen minipig

2007 | journal article. A publication with affiliation to the University of Göttingen.

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​Modeling the growth of the Goettingen minipig​
Koehn, F.; Sharifi, A. R. & Simianer, H.​ (2007) 
Journal of Animal Science85(1) pp. 84​-92​.​ DOI: https://doi.org/10.2527/jas.2006-271 

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Authors
Koehn, Friederike; Sharifi, Ahmad Reza; Simianer, Henner
Abstract
The Goettingen minipig developed at the University of Goettingen, Germany, is a special breed for medical research. As a laboratory animal it has to be as small and light as possible to facilitate handling during experiments. For achieving the breeding goal of small body size in the future, the growth pattern of the minipig was studied. This study deals with the analysis of minipig BW by modeling growth with linear and nonlinear functions and comparing the growth of the minipigs with that of normal, fattening pigs. Data were provided by Ellegaard Goettingen minipigs, Denmark, where 2 subpopulations of the Goettingen basis population are housed. In total 189,725 BW recordings of 33,704 animals collected from birth (d 0) to 700 d of age were analyzed. Seven nonlinear growth functions and 4 polynomial functions were applied. The growth models were compared by using the Akaike's information criterion (AIC). Regarding the whole growth curve, linear polynomials of third and fourth order of fit had the smallest AIC values, indicating the best fit for the minipig BW data. Among the nonlinear functions, the logistic model had the greatest AIC value. A comparison with fattening pigs showed that the minipigs have a nearly linear BW development in the time period from birth to 160 d. Fattening pigs have very low weight gains in their first 7 wk in relation to a specific end weight. After 7 wk, fattening pigs have increased growth, resulting in a growth curve that is more sigmoid than the growth curve of the minipig. Based on these results, further studies can be conducted to analyze the growth with random regression models and to estimate variance components for optimizing the strategies in minipig breeding.
Issue Date
2007
Status
published
Publisher
Amer Soc Animal Science
Journal
Journal of Animal Science 
ISSN
0021-8812

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