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Veterinary world
Aug, 2016;9 (8): 806-10.

Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis.

Mohamed H Khalil, Mostafa K Shebl, Mohamed A Kosba, Karim El-Sabrout, Nesma Zaki
Author Information
  1. Mohamed H Khalil: Department of Poultry Production, Faculty of Agriculture, Aflaton St., El-Shatby, University of Alexandria, Alexandria, Egypt.
  2. Mostafa K Shebl: Department of Poultry Production, Faculty of Agriculture, Aflaton St., El-Shatby, University of Alexandria, Alexandria, Egypt.
  3. Mohamed A Kosba: Department of Poultry Production, Faculty of Agriculture, Aflaton St., El-Shatby, University of Alexandria, Alexandria, Egypt.
  4. Karim El-Sabrout: Department of Poultry Production, Faculty of Agriculture, Aflaton St., El-Shatby, University of Alexandria, Alexandria, Egypt.
  5. Nesma Zaki: Department of Poultry Production, Faculty of Agriculture, Aflaton St., El-Shatby, University of Alexandria, Alexandria, Egypt.
PMID: 27651666 DOI: 10.14202/vetworld.2016.806-810

Abstract

AIM: This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens' eggs.
MATERIALS AND METHODS: Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability.
RESULTS: The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss.
CONCLUSION: A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens.

Keywords

chickens hatchability multiple regression path coefficient prediction

References

  1. Poult Sci. 2004 Aug;83(8):1253-9 [PMID: 15338998]
  2. Poult Sci. 2007 Aug;86(8):1784-92 [PMID: 17626825]
  3. Poult Sci. 2008 Sep;87(9):1913-8 [PMID: 18753462]
Journal Article

Word Cloud

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