Year 2020, Volume 23 , Issue 5, Pages 1373 - 1778 2020-10-31

Yumurtacı Tavuklarda Yumurta Verim Eğrilerinin Modellenmesi
Modelıng of Egg Productıon Curves in Poultry

Emin YALÇINÖZ [1] , Mustafa ŞAHİN [2]


Bu çalışmada yumurtacı tavuklarda yumurta verim eğrilerinin modellenmesinde kullanılan bazı modeller karşılaştırmalı olarak incelenmiştir. Bu amaçla Nick Brown ve Leghorn ırkı tavukların 18. haftadan 59. haftaya kadar olan haftalık yumurta verimleri kullanılmıştır. Modelleme çalışmasında yaygın olarak kullanılan iki farklı kubik parçalı regresyon (iki ve üç boğumlu), lojistik, MMF, gamma, McNally, modifiye compartmental ve kuadratik parçalı regresyon modelleri ele alınmıştır. Modellerin karşılaştırılmasında ise hata kareler ortalamaları, belirleme katsayısı, düzeltilmiş belirleme katsayısı, akaike bilgi kriteri ve durbin-watson otokorelasyon değerleri kullanılmıştır. Çalışma sonucunda her iki ırktada en iyi sonuçlar modifiye compartmental modelinden elde edilmiştir (Nick Brown; HKO=0.000007, R2=0.9999, R ̅^2=0.9998, AIC=-392.966, DW=1.345: Leghorn; HKO=0.0001, R2=0.9998, R ̅^2=0.9997, AIC=-373.225, DW=1.845). Kuadratik parçalı regresyonun ise incelenen modeller içerisinde en kötü sonuçlara sahip olduğu belirlenmiştir (Nick Brown; HKO=0.0007, R2=0.9486, R ̅^2=0.9412 AIC=-298.257, DW=2.341: Leghorn; HKO=0.0002, R2=0.9787, R ̅^2=0.9776, AIC=-340.824, DW=2.171).

In this study, some models used in the modeling of egg yield curves in laying hens were examined comparatively. For this purpose, the weekly egg yields of Nick Brown and Leghorn chickens from 18th to 59th weeks were used. In the modeling study, two widely used cubic segment regression (two and three node), logistic, MMF, gamma, McNally, modified compartmental and quadratic segment regression models were discussed. In the comparison of the models, mean square error, coefficient of determination, corrected coefficient of determination, acoustic information criterion and durbin-watson autocorrelation values were used. As a result of the study, the best results were obtained from the modified compartmental model in both races (Nick Brown; HKO=0.000007, R2=0.9999, R ̅^2=0.9998, AIC=-392.966, DW=1.345: Leghorn; HKO=0.0001, R2=0.9998, R ̅^2=0.9997, AIC=-373.225, DW=1.845). The quadratic segment regression has the worst results among the examined models (Nick Brown; HKO=0.0007, R2=0.9486, R ̅^2=0.9412 AIC=-298.257, DW=2.341: Leghorn; HKO=0.0002, R2=0.9787, R ̅^2=0.9776, AIC=-340.824, DW=2.171).

  • Anang A, Indrijani H2006. Mathematical Models to Describe Egg Production in Laying Hens (Review) (Model Matematik untuk Menggambarkan Kurva Produksi Telur pada Ayam Petelur (Review). Jurnal Ilmu Ternak, Desember, 6(2): 91 – 95.
  • Bindya LA, Murthy HNN, Jayashankar MR, Govindaiah MG 2010. Mathematical Models for Egg Production in an Indian Colored Broiler Dam Line. International Journal of Poultry Science, 9 (9): 916-919.
  • Cason JA, Ware GO 1990. Analysis of flock egg production curves using generalized growth functions. Poultry Science, 69: 1064-1069.
  • Çadırcı Ş, Koncagül S 2013. Effects of initial body weight and feed intake on individual weekly egg production curve of laying hens. Agric. Fac. HR.U., 17(1): 15-23.
  • Demir O, Macit M, Çelebi Ş, Esenbuğa N, Kaya H 2017. Yumurtacı Tavuk Rasyonlarına Değişik Oranlarda Katılan Humat’ın Yumurta Verimine Etkisinin Gamma ve Mcnally Modelleri ile Analizi. Alınteri Journal of Agricultural Sciences, 32(2): 81-86.
  • Gavora JS, Parker RJ, Mcmillan I 1971. Mathematical model of egg production. Poultry Science. 50: 1306-1315.
  • Grossman M, Koops WJ 2001. A model for individual egg production in chickens. Poultry Science, 80: 859-867.
  • Grossman M, Gossman TN, Koops WJ 2000. A model for persistency of egg production. Poultry Science, 79: 1715-1724.
  • Koops WJ, Grossman M 1992. Characterization of poultry egg production using a multiphasic approach. Poultry Science, 71: 399-405.
  • Mcmillan I 1981. Compartmental model analysis of poultry egg production curves. Poultry Science, 60: 1549-1551.
  • Miyoshi S, Luc MK, Kuchida K, Mitsumoto T 1996. Application of Nonlinear Models to Egg Production Curves in Chickens. Jpn. Poultry Science, 33: 178-184.
  • Narinç D, Üçkardeş F, Aslan E 2014. Egg production curve analyses in poultry science. World's Poultry Science Journal, 70(04): 817-828.
  • Narushin VG, Takma C 2003. Sigmoid model for the evaluation of growth and production curves in laying hens. Biosystems Engineering, 84: 343-348.
  • SAS Institute (2011) SAS/STAT User Guide. Version 9.3 edition. SAS Institute Inc.
  • Savegnago RP, Cruz VA, Ramos SB, Caetano SL, Schmidt GS, Ledur MC, El Faro L, Munari DP 2012. Egg production curve fitting using nonlinear models for selected and nonselected lines of White Leghorn hens. Poultry Science, 91: 2977-2987.
  • Yalçınöz E, 2020. Yumurtacı Tavuklarda Yumurta Verim Eğrilerinin Modellenmesi. Kahramanmaraş Sütçü İmam Üniversitesi, Fen Bilimleri Enstitüsü, 46s.
  • Yang N, Wu C, Mcmillan L 1989. A new mathematical model for poultry egg production. Poultry Science, 68: 476-481.
Primary Language tr
Subjects Agriculture
Journal Section RESEARCH ARTICLE
Authors

Orcid: 0000-0002-9195-7793
Author: Emin YALÇINÖZ
Institution: KAHRAMANMARAŞ SÜTÇÜ İMAM ÜNİVERSİTESİ, ZİRAAT FAKÜLTESİ, ZOOTEKNİ BÖLÜMÜ
Country: Turkey


Orcid: 0000-0003-3622-4543
Author: Mustafa ŞAHİN (Primary Author)
Institution: KAHRAMANMARAŞ SÜTÇÜ İMAM ÜNİVERSİTESİ, ZİRAAT FAKÜLTESİ, ZOOTEKNİ BÖLÜMÜ
Country: Turkey


Thanks Emin Yalçınöz’ün "Yumurtacı Tavuklarda Yumurta Verim Eğrilerinin Modellenmesi" isimli yüksek lisans tez çalışmasından özetlenmiştir.
Dates

Application Date : February 19, 2020
Acceptance Date : April 9, 2020
Publication Date : October 31, 2020

APA Yalçınöz, E , Şahi̇n, M . (2020). Yumurtacı Tavuklarda Yumurta Verim Eğrilerinin Modellenmesi . Kahramanmaraş Sütçü İmam Üniversitesi Tarım ve Doğa Dergisi , 23 (5) , 1373-1778 . DOI: 10.18016/ksutarimdoga.vi.691069