Comparison of Artificial Neural Network and Multiple Linear Models in Estimation of Fat-tail weight on Fat-tailed Breeds and their Crosses

Document Type : Research Paper

Authors

1 Department of Animal Science, Golestan Agricultural and Natural Resources Research and Education, AREEO, Gorgan, Iran

2 Agricultural and Natural Resources Research and Education Center ShahrKord

3 Department of Animal Science, Abureyhan College of Agriculture, Tehran University, Tehran, Iran

4 Department of Animal and Poultry Sciences, College of Aboureihan, University of Tehran, Tehran, Iran

5 Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman(SBUK), Iran

6 Member of scientific board of agricultural and natural researsh and education center of golestan province

Abstract

All breeds of Irannians sheep except Zel has a fat tail, and despite their lower carcass fat percentage, male lambs have higher fat-tail weight. Using within breed genetic variation requires accurate and precise measuring of fat tail weight on candidates of selection. The aime of this study was comparision of artificial neural network (ANN) modeling and linear modeling methods to prediction of fat tail weight, using body weight and different tail dimensions. 32 lambs of Chal and Zandi breeds,crosses of Zandi×Chal,Zel×Zandi and Zel×Chal hybrids were used for modeling to an estimation of fat-tail weight. Inputs of the model was birth type, sex, breed, upper width , mid width and lower width of fat tail,fat tail height and body weight, output of the model was fat tail weight. body weight, genotype, and fat tail mid-width had the largest positive correlations with fat-tail weight,0.83,-0.82 and0.80,respectively. The adequacy parameters of the best artificial neural network model had a coefficient determination of 0.99 and a mean squared error(RMSE)of 70.3g. The values of these estimated parameters by the multiple linear model were 0.891 and 263.86, respectively. The results of the extension of the original study showed the complexity of the interactions between the model inputs. Present research approved to accurate and unbiased estimation of tail weight of different breeds and crosses using artificial neural network. Furthermore, present study showed that ANN model can be used for accurate and presise estimation of fat tail weight using measured traits on sheep,than linear model.

Keywords

References

  1. Agamy, R., Abdel-Moneim, A.Y., Abd-Alla, M.S., Abdel-Mageed I.I. and Ashmawi G.M. (2013). Use of fat tail dimensions for prediction of fat in tail and carcass in Egyptian ram lambs. Egyptian Journal of Animal Production. 50(3):144 -156.
  2. Atti, N., Bocquier, F. and Khaldi, G.(2004). Performance of the fat-tailed Barbarine sheep in its environment: adaptive capacity to alternation of underfeeding and re-feeding periods. Animal Research. 53(3):165-176.
  3. Bedhiaf Romdhani, S., Soumri, N. and Djemali, M. (2004). Use of fat tail and body scores to estimate lamb weights in fat tailed meat sheep. In: Proceedings of the 34th Biennial Session of ICAR, Sousse, Tunisia, p. 71-81.
  4. Esmailizadeh, A.K., Miraei-Ashtiani, S.R., Mokhtari, M.S. and Asadi-Fozi, M. (2011). Growth performance of crossbred lambs and productivity of kurdi ewes as affected by the sire breed under extensive production system. Journal of Agricultural Science and Technology. 13:701-708.
  5. Farid, A. (1991). Slaughter and carcass characteristics of three fat-tailed sheep breed and their crosses with Corriedal and Targhee rams. Small Ruminant Research. 5(3):255–271.
  6. Ghazanfari, S., Nobari, K. and Tahmoorespur, M. (2011). Prediction of Egg Production Using Artificial Neural Network. Iranian Journal of Animal Science. 1(1):11-16.
  7. Khaltabadi Farahani, H., Moradi Shahrbabak, H., Moradi Shahrbabak, M. and Mehrabani Yeganeh, M. (2010). Relationship of fat-tail and body measurements with some economic important traits in fat-tail Makoei breed of Iranian sheep. African Journal of Biotechnology. 9(36):5989-5992.
  8. Kashan, N.E.J., Manafi-Azar, G.H., Afzalzadeh, A. and Salehi, A. (2005). Growth performance and carcass quality of fattening lambs from fat-tailed and tailed sheep breeds. Small Ruminant Research. 60:267-271.
  9. Lavvaf, A. and Farahvash, T. (2012). Body measurements recording as an alternative to determine live weight and carcass performance of Macoei and Afshari sheep. Indian Journal of Animal Research. 46(3):263-267.
  10. Moradi, M.H., Nejati-Javaremi, A., Moradi-Shahrbabak, M., Dodds, K.G. and McEwan, J.C. (2012). Genomic scan of selective sweeps in thin and fat tail sheep breeds for identifying of candidate regions associated with fat deposition. BMC Genetics. 13:10-12.
  11. Norouzian, M.A. and Vakili-Alavijeh, M. (2016). Comparison of Artificial Neural Network and Multiple Regression Analysis for Prediction of Fat Tail Weight of Sheep. Iranian Journal of Applied Animal Science. 6(4):895-900.
  12. Safdarian, , Zamiri, M.J., Hashemi, M. and Noorolahi, H. (2008). Relationships of fat-tail dimensions with fat-tail weight and carcass characteristics at different slaughter weights of Torki-Ghashghaii sheep. Meat Science. 80(3):686-689.
  13. Vatankhah, M. and Talebi, M.A. (2008). Heritability estimates and correlations between production and reproductive traits inLori-Bakhtiari sheep in Iran. South African Journal of Animal Science. 38(2):110-118.
  14. Vatankhah, M., Moradi-Shahre Babak, M., Nejati-Javaremi, A., Mirayi-Ashtiani, S. and Vaez-Torshizi, R. (2004). Relation between body measurements with live weight, warm carcass, warm carcarr without fat-tail in Lori Bakhtiari sheep. Animl Science Journal, 65:7-15.
  15. Wright, D. (2015). The Genetic Architecture of Domestication in animals. Bioinformatics and Biology Insight. 9(4):11-20.
  16. Zamiri, M.J. and Izadifard, J. (1997). Relationships of fat-tail weight with fat-tail measurements and carcass characteristics of Mehraban and Ghezel rams. Small Ruminant Research. 15:261-266.
  17. , M.J. and Izadifard, J. (1997). Relationsheeps of fat-tail weight with fattail Measurements and carcass characteristics of Mehraban and Ghezel rams. Small Rumin. Res. 26:261-266.
Animal Sciences Journal
Volume 33, Issue 129
March 2021
Pages 167-182

Files

Share

How to cite

Statistics