Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-16T15:31:03.908Z Has data issue: false hasContentIssue false

Comparison of non-linear growth models to describe the growth curve in West African Dwarf sheep

Published online by Cambridge University Press:  01 July 2008

A. B. Gbangboche*
Affiliation:
Faculté des Sciences Agronomiques, Université d’Abomey Calavi, 01 BP 526 Cotonou, Republic of Benin
R. Glele-Kakai
Affiliation:
Faculté des Sciences Agronomiques, Université d’Abomey Calavi, 01 BP 526 Cotonou, Republic of Benin
S. Salifou
Affiliation:
Laboratoire de Recherche en Biologie Appliquée (LARBA), Ecole Polytechnique d’Abomey Calavi, Université d’Abomey Calavi, 01 BP 2009 Cotonou, Republic of Benin
L. G. Albuquerque
Affiliation:
Departamento de Zootecnia Via de Acesso Prof. Paulo Donato Castelani, Faculdade de Ciências Agrârias e veterinârias, Câmpus De Jaboticabal, Universidade estadual Paulista, km 5, UNESP 14884-900 Jaboticabal, SP, Brazil
P. L. Leroy
Affiliation:
Département des Productions Animales, Faculté de Médecine Vétérinaire, Université de Liège, Bât 43, 20 Boulevard de Colonster, 4000 Liège, Belgium
Get access

Abstract

The objectives of this study were to compare the goodness of fit of four non-linear growth models, i.e. Brody, Gompertz, Logistic and Von Bertalanffy, in West African Dwarf (WAD) sheep. A total of 5274 monthly weight records from birth up to 180 days of age from 889 lambs, collected during 2001 to 2004 in Betecoucou breeding farm in Benin were used. In the preliminary analysis, the General Linear Model Procedure of the Statistical Analysis Systems Institute was applied to the dataset to identify the significant effects of the sex of lamb (male and female), type of birth (single and twin), season of birth (rainy season and dry season), parity of dam (1, 2 and 3) and year of birth (2001, 2002, 2003 and 2004) on the observed birth weight and monthly weight up to 6 months of age. The models parameters (A, B and k), coefficient of determination (R2), mean square error (MSE) were calculated using language of technical computing package Matlab®, 2006. The mean values of A, B and k were substituted into each model to calculate the corresponding Akaike’s Information Criterion (AIC). Among the four growth functions, the Brody model has been selected for its accuracy of fit according to the higher R2, lower MSE and AIC. Finally, the parameters A, B and k were adjusted in Matlab®, 2006 for the sex of lamb, year of birth, season of birth, birth type and the parity of ewe, providing a specific slope of the Brody growth curve. The results of this study suggest that Brody model can be useful for WAD sheep breeding in Betecoucou farm conditions through growth monitoring.

Type
Full Paper
Copyright
Copyright © The Animal Consortium 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abassa, KP, Pessinaba, J, Adeshola-Ishola, A 1992. Croissance pré-sevrage des agneaux Djallonké au Centre de Kolokopé (Togo). Revue d’Élevage et de Médecine Vétérinaire des Pays Tropicaux 45, 4954.CrossRefGoogle Scholar
Akaike, H 1974. A new look at the statistical model identification. IEEE transactions on Automatic Control 19, 716723. ISSN 0018-9286.Google Scholar
Akbas, Y, Taskýn, T, Demirören, E 1999. Comparison of several models to fit the growth curves of Kivircik and Daglic male lambs. Turkish Journal of Veterinary & Animal Sciences 23 (Suppl. 3), 537544.Google Scholar
Armbruster, T, Peters K, J, Hadji-Thomas, A 1991a. Sheep production in the humid zone of West Africa. III. Mortality and productivity of sheep in improved production systems in Côted’Ivoire. Journal of Animal Breeding and Genetics 108, 210220.CrossRefGoogle Scholar
Armbruster, T, Peters K, J, Hadji-Thomas, A, Lamizana, P 1991b. Sheep production in the humid zone of West Africa. I. Reproduction performance in improved systems in Côte- d’Ivoire. Journal of Animal Breeding and Genetics 108, 220226.Google Scholar
Bathaei, SS, Leroy, PL 1998. Genetic and phenotypic aspects of the growth curve characteristics in Mehraban Iranian fat-tailed sheep. Small Ruminant Research 29, 261269.CrossRefGoogle Scholar
Beltran, JJ, Butts, WT, Olson, TA, Koger, M 1992. Growth patterns of two lines of Angus cattle selected using predicted growth parameters. Journal of Animal Science 70, 734741.CrossRefGoogle ScholarPubMed
Brown, JE, Fitzhugh, HA Jr, Cartwright, TC 1976. A comparison of nonlinear models for describing weight–age relationships in cattle. Journal of Animal Science 42, 810818.CrossRefGoogle Scholar
Charray, J, Humbert, JM, Levif, J 1992. Manual of Sheep Production in the Humid Tropics of Africa. CAB International, Wallingford, UK.Google Scholar
DeNise, RS, Brinks, JS 1985. Genetic and Environmental aspect of the growth curve parameters in beef cows. Journal of Animal Science 61, 14311440.CrossRefGoogle ScholarPubMed
Doren, PE, Baker, JF, Long, CR, Cartwright, TC 1989. Estimating parameters of growth curves of bulls. Journal of Animal Science 67, 14321445.Google Scholar
Ebangi, AL, Nwakalor, LN, Mbah, DA, Abba, D 1996. Factors affecting the birth weight and neonatal mortality of Massa and Fulbe sheep breeds in a hot and dry environment, Cameroon. Revue d’Élevage et de Médecine Vétérinaire des Pays Tropicaux 49, 349353.CrossRefGoogle Scholar
Epstein, H 1971. The origin of domestic animals of Africa , vol. 2 . Africana Publishing Corporation, New York, USA.Google Scholar
Fall, A, Diop, M, Sandford, J, Wissocq, YJ, Durkin, J, Trail, JCM 1982. Evaluation of the Productivities of Djallonke Sheep and N’Dama Cattle at the Centre de Recherches Zootechniques, Kolda, Senegal. Research report no. 3. ILCA, Adis Abeba, Ethiopia.Google Scholar
Faostat 2005. Food and Agriculture Organization of the United Nations. Retrieved November 2007 from http://faostat.fao.orgGoogle Scholar
Gatenby, RM 2002. The Tropical Agriculturist, Sheep, 2nd edition. Macmillan Publishers Limited, London, UK.Google Scholar
Gbangboche, AB, Adamou-Ndiaye, M, Youssao, AKI, Farnir, F, Detilleux, J, Abiola, FA, Leroy, PL 2006a. Non-genetic factors affecting the reproduction performance, lamb growth and productivity indices of Djallonke sheep. Small Ruminant Research 64, 133142.Google Scholar
Gbangboche, AB, Youssao, AKI, Senou, M, Adamou-Ndiaye, M, Ahissou, A, Farnir, F, Michaux, C, Abiola, FA, Leroy, PL 2006b. Examination of non-genetic factors affecting the growth performance of Djallonke sheep in Soudanian zone at the Okpara breeding farm of Benin. Tropical Animal Health and Production 38, 5564.Google Scholar
Goliomytis, M, Panopoulou, E, Rogdakis, E 2003. Growth curves for body weight and major component parts, feed consumption, and mortality of male broiler chickens raised to maturity. Poultry Science 82, 10611068.Google Scholar
Goonewardene, LA, Berg, RT, Hardin, RT 1981. A growth study of beef cattle. Canadian Journal of Animal Science, 10411048.CrossRefGoogle Scholar
Imai, C, Sakai, H, Katsura, K, Honto, W, Hida, Y, Takazawa, T 2002. Growth model for the endangered cyprinid fish Tribolodon nakamurai based on otolith analyses. Fisheries Science 68, 843848.Google Scholar
Kaps, M, Herring, WA, Lamberson, WR 1999. Genetic and Environmental parameters for mature weight in Angus cattle. Journal of Animal Science 77, 569574.Google Scholar
Lambe, NR, Navajas, EA, Simm, G, Bunger, L 2006. A genetic investigation of various growth models to describe growth of lambs of two contrasting breeds. Journal of Animal Science 84, 26422654.CrossRefGoogle ScholarPubMed
Lewis, RM, Brotherstone, S 2002. A genetic evaluation of growth in sheep using random regression techniques. Animal Science 74, 6370.Google Scholar
Lewis, RM, Emmans, GC, Dingwall, WS, Simm, G 2002. A description of the growth of sheep and its genetic analysis. Animal Science 74, 5162.CrossRefGoogle Scholar
London, JC, Weniger, JH 1995. Investigations into traditionally managed Djallonke-sheep production in the humid and subhumid zones of Asante, Ghana. III. Relationship between birth weight, preweaning growth, and postweaning growth of lambs. Journal of Animal Breeding and Genetics 112, 431453.Google Scholar
Matlab® 2006. The language of Technical Computing. Version 7.2.0. 232 (2006a). Copyright 1984–2006. The MathWorks Inc., producted by US patents, MA, USA. (http://www.mathworks.com/patents).Google Scholar
McManus, C, Evangelista, C, Fernandes, LAC, de Miranda, MR, Moreno-Bernal, FE, dos Santos, NR 2003. Curvas de crescimento de ovinos Bergamácia criados no Distrito Federal. Revista Brasileira de Zootecnia 32, 12071212.Google Scholar
Poivey, JP, Charray, J, Hubert, JM 1986. Research on sheep in Ivory-Coast, Study and improvement of the Djallonke breed. World Review of Animal Production 22, 7782.Google Scholar
Rege JEO, 1992. Indigenous African small ruminants, a case for characterization and improvement. Proceedings of the Second Biennial Conference of the African small ruminant research network AICC, Arusha, Tanzania, 7-11 December, 1992.CrossRefGoogle Scholar
Renne, U, Langhammer, M, Wytrwat, E, Dietl, G, Bunger, L 2003. Genetic statistical analysis of growth in selected and unselected mouse lines. Journal of Experimental Animal Science 42, 218232.CrossRefGoogle Scholar
Rogers, SR, Pesti, GM, Marks, HL 1987. Comparison of three nonlinear regression models for describing broiler growth curves. Growth 51, 229239.Google ScholarPubMed
SAS Institute 2002–2003. SAS version 9.1. SAS Institute Inc., Cary, NC, USA.Google Scholar
Topal, M, Ozdemir, M, Aksakal, V, Yildiz, N, Dogru, U 2004. Determination of the best nonlinear function in order to estimate growth in Morkaraman and Awassi lambs. Small Ruminant Research 55, 229232.Google Scholar
Tsangridis, A, Filippousis, N 1994. Analysis of two models for picarel (Spicara smaris L.) growth using Schnute’s micro-simplex nonlinear estimation procedure. Fisheries Research 20, 181189.Google Scholar
Varona, L, Moreno, C, García Cortés, L, Altarriba, J 1997. Multiple trait genetic analysis of underlying biological variables of production functions. Livestock Production Science 47, 201209.CrossRefGoogle Scholar
Yapi-Gnaoré, CV, Oya, A, Rege, JEO, Dagnogo, B 1997. Analysis of an open nucleus breeding programme for Djallonke sheep in the Ivory Coast. 1. Examination of non-genetics factors. Animal Science 64, 291300.Google Scholar