Modelling of Rhode Island Red chicken strains


345 / 146

Authors

  • HINA KAUSAR ICAR - Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh 243 122 India
  • MED RAM VERMA ICAR - Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh 243 122 India
  • SANJEEV KUMAR ICAR- Central Avian Research Institute, Izatnagar
  • VIJAY BAHADUR SHARMA ICAR - Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh 243 122 India
  • ANANTA KUMAR DAS Howrah KVK, West Bengal
  • LEENA DILLIWAR ICAR - Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh 243 122 India

https://doi.org/10.56093/ijans.v86i5.58536

Keywords:

Adjusted R2, Durbin Watson (DW) test, MAE, MSE, Non linear models, R2

Abstract

To study the growth pattern in body weight of 3 strains of Rhode Island Red chicken Bertalanffy, gompertz and logistic nonlinear models were fitted. From the data on body weights of three strains of Rhode Island Red, we observed that average body weights of male chicken were higher than the female chicken. Based on the various measures of goodness fit criteria we have observed that in modelling of body weight of the Rhode Island Red chicken Bertalanffy was the best fitted model. In case of Rhode Island Control, Bertalanffy was the best fitted model and for Rhode Island Control male chicken logistic was the best fitted model. In case of Rhode Island White chicken logistic was the best fitted model and in case of Rhode Island White male chicken Bertalanffy was the best fitted model. In case of female chicken of Rhode Island Red, Rhode Island Control and Rhode Island White strains gompertz model was the best fitted model. From these fitted models one can determine the expected average body weight of a group of birds of three strains of RIR chicken at any given age under normal conditions.

Downloads

Download data is not yet available.

References

BAHS (Basic Animal Husbandry Statistics). 2014. Department of Animal Husbandry, Dairying and Fisheries, Govt. of India. Berkey C S. 1986. Nonlinear growth curve analysis: Estimating the population parameters. Annals of Human Biology 13: 111–28. DOI: https://doi.org/10.1080/03014468600008261

Brody S. 1945. Bioenergetics and Growth; With Special Reference to the Efficiency Complex in Domestic Animals. pp: 491–661. Hafner Press, Reinhold, New York, USA.

Das A K. 2013. ‘Microsatellite polymorphism, immunocompe- tence profile and performance evaluation in Rhode Island Red chicken and its crosses.’ Ph.D. thesis, Indian Veterinary Research Institute, Izatnagar.

Kuhi H D, Kebreab E, Lopez S and France J. 2003. An evaluation of different growth function for describing the profile of live weight with time (age) in meat and egg strains of chicken. Poultry Science 82: 1536–43. DOI: https://doi.org/10.1093/ps/82.10.1536

Laird A K. 1966. Postnatal growth of birds and mammals. Growth 30: 349–63.

Paul A K, Singh S, Kumar A, Singh O, Raman R K, Haunshi S and Verma M R . 2011. Nonlinear growth models for body growth of Vanraja poultry birds. IUP Journal of Genetics and Evolution 4 (4): 65–69.

Prasad Shiv and Singh D P. 2006.An adjustment model of Logistic form to describe the growth pattern of chickens. Indian Journal of Poultry Science 41 (3): 280–82.

Prasad Shiv, Singh D P and Singh Rajendra. 2008. Nonlinear describe growth pattern of Indian native chickens. Indian Journal of Animal Sciences 78 (6): 645–48.

Sengul T and Kiraz S. 2005. Nonlinear model for growth curve in large white turkeys. Turkish Journal of Veterinary and Animal Science 29: 331–37.

Singh Umesh, Singh R B and Gautam S S. 2014. Nonlinear stochastic model for describing growth of soybean production in Madhya Pradesh and India. International Journal of Agricultural and Statistical Sciences 10 (2): 375–79.

Downloads

Submitted

2016-05-20

Published

2016-05-20

Issue

Section

Short-Communication

How to Cite

KAUSAR, H., VERMA, M. R., KUMAR, S., SHARMA, V. B., DAS, A. K., & DILLIWAR, L. (2016). Modelling of Rhode Island Red chicken strains. The Indian Journal of Animal Sciences, 86(5), 612–615. https://doi.org/10.56093/ijans.v86i5.58536
Citation