Modeling of crossbred cattle growth, comparison between cubic and piecewise random regression models

Genetics and Molecular Research

Volumn 10, Issue 3, 2011, Pages 2230-2244

  Mirzaei, H R ^a   Pitchford, W S ^b   Verbyla, A P ^b  

^a UNIVERSITY OF ZABOL   (Iran)

^b UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

Crossbred cattle; Cubic; Growth; Piecewise; Random regression

Indexed keywords

AGE; ARTICLE; AUSTRALIA; BODY GROWTH; BODY WEIGHT; BREED DIFFERENCE; CATTLE FARMING; CONTROLLED STUDY; CROSS BREEDING; CUBIC MODEL; ENVIRONMENTAL FACTOR; NONHUMAN; PIECEWISE RANDOM REGRESSION ANALYSIS; REGRESSION ANALYSIS; SEASONAL VARIATION; SEX DIFFERENCE; STATISTICAL MODEL; WEANING;

ANIMAL HUSBANDRY; ANIMALS; BODY WEIGHT; BREEDING; CATTLE; CROSSES, GENETIC; HYBRIDIZATION, GENETIC; MODELS, BIOLOGICAL; REGRESSION ANALYSIS;

BOS;

EID: 80955124596     PISSN: None     EISSN: 16765680     Source Type: Journal    
DOI: 10.4238/vol10-3gmr1302     Document Type: Article

References (27)

1. Aggrey SE (2002). Comparison of three nonlinear and spline regression models for describing chicken growth curves. Poult. Sci. 81: 1782-1788.
2. Aggrey SE (2009). Logistic nonlinear mixed effects model for estimating growth parameters. Poult. Sci. 88: 276-280.
3. Arango JA, Cundiff LV and Van Vleck LD (2002). Breed comparisons of Angus, Charolais, Hereford, Jersey, Limousin, Simmental, and South Devon for weight, weight adjusted for body condition score, height, and body condition score of cows. J. Anim. Sci. 80: 3123-3132.
4. Atchley WR, Xu S and Cowley DE (1997). Altering developmental trajectories in mice by restricted index selection. Genetics 146: 629-640.
5. Bohmanova J, Miglior F, Jamrozik J, Misztal I, et al. (2008). Comparison of random regression models with Legendre polynomials and linear splines for production traits and somatic cell score of Canadian Holstein cows. J. Dairy Sci. 91: 3627-3638.
6. Brown JE, Fitzhugh HA Jr and Cartwright TC (1976). A comparison of nonlinear models for describing weight-age relationships in cattle. J. Anim. Sci. 42: 810-818.
7. Fitzhugh HA Jr (1976). Analysis of growth curves and strategies for altering their shape. J. Anim. Sci. 42: 1036-1051.
8. Forni S, Piles M, Blasco A, Varona L, et al. (2009). Comparison of different nonlinear functions to describe Nelore cattle growth. J. Anim. Sci. 87: 496-506.
9. Gilmour AR, Thompson R and Cullis BR (1995). Average information reml: An efficient algorithm for variance parameter estimation in linear mixed models. Biometrics 51: 1440-1450.
10. Gilmour AR, Bulls BR, Welham SJ and Thompson R (2000). Asreml Reference Manual, NSW Agriculture Biometric Bulletin no. 3. Orange Agricultural Institute, Orange.
11. GrassGro (2002). Analysing pasture and animal production. Version 2.4.1. Horizon Agriculture Pty Limited, New South Wales.
12. Hassen A, Wilson DE and Rouse GH (2003). Estimation of genetic parameters for ultrasound-predicted percentage of intramuscular fat in Angus cattle using random regression models. J. Anim. Sci. 81: 35-45.
13. Hodson DJ (1966). Fitting segmented curves whose join points have to be estimated. Am. Stat. Assoc. 61: 1097-1125.
14. Kirkpatrick M, Lofsvold D and Bulmer M (1990). Analysis of the inheritance, selection and evolution of growth trajectories. Genetics 124: 979-993.
15. Meyer K (2004). Scope for a random regression model in genetic evaluation of beef cattle for growth. Livest. Prod. Sci. 86: 69-83.
16. Meyer K (2005a). Advances in methodology for random regression analyses. Aust. J. Exp. Agric. 45: 847-858.
17. Meyer K (2005b). Random regression analyses using B-splines to model growth of Australian Angus cattle. Genet. Sel. Evol. 37: 473-500.
18. Patterson HD and Thompson R (1971). Recovery of inter-block information when block sizes are unequal. Biometrika 58: 545-554.
19. Pitchford WS, Mirzaei HR, Deland MPB, Afolayan RA, et al. (2006). Variance components for birth and carcass traits of crossbred cattle. Aust. J. Exp. Agric. 46: 225-231.
20. Robinson GK (1991). That blup is a good thing: the estimation of random effects. Stat. Sci. 6: 15-32.
21. Schenkel FS, Miller SP, Jamrozik J and Wilton JW (2002). Two-step and random regression analyses of weight gain of station-tested beef bulls. J. Anim. Sci. 80: 1497-1507.
22. Schinckel AP, Adeola O and Einstein ME (2005). Evaluation of alternative nonlinear mixed effects models of duck growth. Poult. Sci. 84: 256-264.
23. Speidel SE, Enns RM and Crews DH Jr (2010). Genetic analysis of longitudinal data in beef cattle: a review. Genet. Mol. Res. 9: 19-33.
24. Varona L, Moreno C, García Cortes LA and Altarriba J (1997). Multiple trait genetic analysis of underlying biological variables of production functions. Livest. Prod. Sci. 47: 201-209.
25. Vitezica ZG, Marie-Etancelin C, Bernadet MD, Fernandez X, et al. (2010). Comparison of nonlinear and spline regressionmodels for describing mule duck growth curves. Poult. Sci. 89: 1778-1784.
26. Warren JH, Schalles RR and Milliken G (1980). A segmented line regression procedure to describe growth in beef cows. Growth 44: 160-166.
27. Williams JL, Garrick DJ and Speidel SE (2009). Reducing bias in maintenance energy expected progeny difference by accounting for selection on weaning and yearling weights. J. Anim. Sci. 87: 1628-1637.