Volume 8, Issue 17 (1-2018)                   rap 2018, 8(17): 175-183 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Babajani S, Alijani S, Olyayee M, Javanmard A. Principal Component Analysis of Internal Egg Quality and some Performance Traits of Azarbayjan Native Chickens. rap. 2018; 8 (17) :175-183
URL: http://rap.sanru.ac.ir/article-1-855-en.html
Abstract:   (2290 Views)
   One of the main problems of multiple-trait genetic evaluation in poultry breeding is high computing costs. Principal components analysis (PCA) is a method for reducing the number of traits in correlated trait analysis. The aim of the present study was to determine the most effective principal components (PCs) of internal egg quality and some performance traits of Azarbayjan native chickens. Records were measured from 1500 native hens, including body weight at sexual maturity (BWSM), age at first egg production (ASM), egg volume (EV), yolk percent (YP), yolk width (YWI), yolk weight (YW), yolk Index (YI), yolk dry matter (YDM), yolk depth (YD), yolk pH (YPH), yolk coefficient (YC), the ratio of yolk weight to albumen weight (RYA), albumen percent (AP), Hough Unit (HU), albumen pH (APH), albumen height (AH), albumen dry matter (ADM), albumen weight (AW). Descriptive statistics, phenotypic Pearson coefficients and principal components analysis were evaluated using SAS software. The results showed that the range of Pearson correlation coefficients for phenotypic traits varied from zero to 0.98. The correlation coefficients more than 0.6 between HU and AH, YP and RYA, YW and YC, YP and YWI, YP and YW, YP and YDM, YP and YC، YWI and YW, YWI and YDM, YWI and RYA, YW and RYA, YI and YD, YDM and YC, YDM and RYA, YC and RYA, AP and AW, and ADM and AW were evaluated. The PCA analysis showed that the eight first principal components explained about 90.21% of the total variation of internal egg quality traits. Using PCA in internal egg quality, BWSM and ASM showed that YW, YDM, YC, YP, RYA, YWI, AP, AH, AW and HU have great impact on the total phenotypic variance. So, this method can be used for internal egg quality and performance trait analysis of native hens and can reduce computing costs and time of genetic evaluation of multiple traits.
Full-Text [PDF 3305 kb]   (1257 Downloads)    
Type of Study: Research | Subject: Special
Received: 2018/01/10 | Accepted: 2018/01/10 | Published: 2018/01/10

1. Abbasi, M.A., H. Emamgholi and S. Ghorbani. 2017. Estimation of (Co) Variance Components of Egg Quality Traits for Fars Native Fowls. Research on Animal Production, 8: 195-200 (In Persian). [DOI:10.29252/rap.8.15.195]
2. Alipanah, M., J. Deljo., M. Rokouie and R. Mohammadnia. 2013. Heritabilities and genetic and phenotypic correlations of egg quality traits in Khazak layers. Trakia Journal of Sciences, 11: 175-180.
3. Applied Multivariate Statistical Analysis: Principal Components Analysis (PCA). https://onlinecourses.science.psu.edu/stat505/node/49.
4. Bakhtiyarizadeh, M.R., M. Moradi-Shahrbabak and A. Pakdel. 2012. Use of Principal Components Analysis to Prediction Fat-tail Weight Trait in Lori-Bakhtiari Sheep Iranian Journal of Animal Science, 43: 103-111 (In Persian).
5. Boorman, K.N., J.G. Volynchook and C.G. Belyavin. 1989. Egg shell formation and quality. Recent Developments in Poultry Nutrition, 261-275. [DOI:10.1016/B978-0-407-01513-5.50021-4]
6. Butcher, G.D. and R.D. Miles. 2003. Factors causing poor pigmentation of brown shelled eggs. University of Florida. http://edis.ifas.ufl.edu/pdffiles/VM/VM04700.pdf
7. Coutts, J.A. and G.C. Wilson. 1990. Egg quality handbook. Queensland Department of Primary Industries, Information series, 45 pp.
8. De Ketelaere, B., F. Bamelis., B. Kemps., E. Decuypere and De J. Baerdemaeker. 2004. Non-destructive measurements of the egg quality. World's Poultry Science Journal, 60: 289-302. [DOI:10.1079/WPS200417]
9. Dunteman, G.H. 1989. Principal components analysis (Quantitative Applications in the Social Sciences). First Edn., A Sage University Paper, 51 pp. [DOI:10.4135/9781412985475]
10. Fakhry, M. 2010. Principal component and factor analysis, case study: assets price evaluation and inflation impacts. Economic Research and Policy Department Central Bank of the Islamic Republic of Iran, 23 pp.
11. Hammer, L.B., D.M. Truxillo, T. Bodner, J. Rineer, A.C. Pytlovany and A. Richman. 2015. Effects of a workplace intervention targeting psychosocial risk factors on safety and health outcomes. BioMed Research International: 1-12. [DOI:10.1155/2015/836967]
12. Haque, M.M., A. Rahman, D. Hagare and G. Kibria. 2013. Principal component regression analysis in water demand forecasting: An application to the Blue Mountains, NSW, Australia. Journal of Hydrology and Environment Research, 1: 49-59.
13. Hosseini, V.M., A.R. Mirayi, A. Pakdel and H. Morady-Shahr Babak. 1993. Selection and evaluation parameters in the principal component regression and multiple linear regressions to predict Tail weight. Animal sciences, 104(27): 91-100.
14. Johnson, R.A. and D.W. Wichern. 2007. Applied multivariate statistical analysis. 6th edn., Englewood Cliffs, NJ: Prentice Hall.
15. Koelkebeck, K.W. 1999. What is egg quality and conserving it? University of Illinois Extension Publications.13 pp.
16. Lin, H., K. Mertens, B. Kemps, T. Govaerts, B. De Ketelaere, J. De Baerdemaeker, and Buyse, J. 2004. New approach of testing the effect of heat stress on eggshell quality: mechanical and material properties of eggshell and membrane. British poultry science, 45: 476-482. [DOI:10.1080/00071660400001173]
17. Mc Ferran J.B. 2003. Adenovirus Infections or Group 1 Adenovirus Infections; Egg Drop Syndrome. In: B.W. Calnek, H.J. Barnes, C.W. Beard, L.R. McDonald and Y.M. Saif (Eds.) Diseases of Poultry. Iowa State University Press, Ames, Iowa, pp: 618-642.
18. Pinto, L.F.B., I.U. Packer, C.M.R. De Melo, M.C. Ledur and L.L. Coutinho. 2006. Principal components analysis applied to performance and carcass traits in the chicken. Animal Research, 55: 419-425. [DOI:10.1051/animres:2006022]
19. Pires, J.C.M., F.G. Martins, S.I.V. Sousa, M.C.M. Alvim-Ferraz and M.C. Pereira. 2008. Selection and validation of parameters in multiple linear and principal component regressions. Environmental Modelling and Software, 23: 50-55. [DOI:10.1016/j.envsoft.2007.04.012]
20. Sarica, M., S. Boga and U.S. Yamak. 2008. The effects of space allowance on egg yield, egg quality and plumage condition of laying hens in battery cages. Czech Journal of Animal Science, 53: 346-353. [DOI:10.17221/349-CJAS]
21. Sarica, M., H. Onder and U.S. Yamak. 2012. Determining the most effective variables for egg quality traits of five hen genotypes. International Journal of Agriculture Biology, 14: 235-240.
22. SAS, 2002. SAS User's guide V. 9.1: Statistics. SAS Institute, Inc, Cary, NC.
23. Shahri, L., S. Alijani, H. Janmohammadi, H. Daghighkia, P. Bestanchi and E. Alizadeh. 2013. Estimation genetic and phenotype parameters of internal egg quality traits of native chickens in Azarbayjan. Journal of investigations of livestock and poultry, 1(3): 49-55 (In Persian).
24. Solomon, S.E. 1991. Egg and eggshell quality. Wolf publishing Ltd, London, England.
25. Stadelman, W.J. and O.J. Cotterill. 1995. Egg science and technology. 4th ed. Food Product Press in Haworth Press, Inc. London. UK.
26. Xue, D.B., S.J. Zhou, Z.J. Bing, G.W. Li, W Yun, C.X. Ying. 2013.Principal components analysis on egg quality characteristics of native duck breed in china. Journal of Animal and Veterinary Advances. 12: 1286-1288.
27. Yousefi, Z.A., S. Alijani and H. JanMohammadi. 2013. Estimation of genetic parameters for production and reproduction traits of Iranian native chickens using Bayesian method via Gibbs sampling. Research on Animal Production, 8(4): 91-99 (In Persian).

Add your comments about this article : Your username or Email:

© 2020 All Rights Reserved | Research On Animal Production(Scientific and Research)

Designed & Developed by : Yektaweb