Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-27T08:18:23.189Z Has data issue: false hasContentIssue false
  • English
  • Français

Comparison of nonlinear models to describe the feather growth and development curve in yellow-feathered chickens

Published online by Cambridge University Press:  06 January 2020

W. Y. Xie ,
N. X. Pan ,
H. R. Zeng ,
H. C. Yan ,
X. Q. Wang  and
C. Q. Gao
W. Y. Xie
Affiliation:
College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture/Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding/South China Collaborative Innovation Center for Poultry Disease Control and Product Safety, Guangzhou510642, China
N. X. Pan
Affiliation:
College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture/Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding/South China Collaborative Innovation Center for Poultry Disease Control and Product Safety, Guangzhou510642, China
H. R. Zeng
Affiliation:
College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture/Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding/South China Collaborative Innovation Center for Poultry Disease Control and Product Safety, Guangzhou510642, China
H. C. Yan
Affiliation:
College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture/Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding/South China Collaborative Innovation Center for Poultry Disease Control and Product Safety, Guangzhou510642, China
X. Q. Wang
Affiliation:
College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture/Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding/South China Collaborative Innovation Center for Poultry Disease Control and Product Safety, Guangzhou510642, China
C. Q. Gao*
Affiliation:
College of Animal Science, South China Agricultural University/Guangdong Provincial Key Laboratory of Animal Nutrition Control/Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture/Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding/South China Collaborative Innovation Center for Poultry Disease Control and Product Safety, Guangzhou510642, China
*
†E-mail: cqgao@scau.edu.cn
Get access

Abstract

Feathers play a critical role in thermoregulation and directly influence poultry production. Poor feathering adversely affects living appearance and carcass quality, thus reducing profits. However, producers tend to ignore the importance of feather development and do not know the laws of feather growth and development. The objective of this study was to fit growth curves to describe the growth and development of feathers in yellow-feathered broilers during the embryonic and posthatching periods using different nonlinear functions (Gompertz, logistic and Bertalanffy). Feather mass and length were determined during the embryonic development and posthatching stages to identify which growth model most accurately described the feather growth pattern. The results showed that chick embryos began to grow feathers at approximately embryonic (E) day 10, and the feathers grew rapidly from E13 to E17. There was little change from E17 to the day of hatching (DOH). During the embryonic period, the Gompertz function (Y = 798.48e−203 431exp(−0.87t), Akaike’s information criterion (AIC) = −0.950 × 103, Bayesian information criterion (BIC) = −0.711 × 103 and mean square error (MSE) = 559.308) provided the best fit for the feather growth curve compared with the other two functions. After hatching, feather mass and length changed little from the DOH to day (D) 14, increased rapidly from D21 to D91 and then grew slowly after D91. The first stage of feather molting occurred from 2 to 3 weeks of age when the down feathers were mostly shed and replaced with juvenile feathers, and the second stage occurred at approximately 13 to 15 weeks of age. The three nonlinear functions could overall fit the feather growth curve well, but the Bertalanffy model (Y = 116.88 × (1−0.86e−0.02t)3, AIC = 1.065 × 105, BIC = 1.077 × 105 and MSE = 11.308) showed the highest degree of fit among the models. Therefore, the Gompertz model exhibited the best goodness of fit for the feather growth curve during the embryonic development, while the Bertalanffy model was the most suitable model due to its accurate ability to predict the growth and development of feathers during the growth period, which is an important commercial characteristic of yellow-feathered chickens.

Keywords

feather massfeather lengthfeather growth curvemathematical modelyellow-feathered chicken
Type
Research Article
Information
animal , Volume 14 , Issue 5 , May 2020 , pp. 1005 - 1013
Copyright
© The Animal Consortium 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aggrey, SE 2002. Comparison of three nonlinear and spline regression models for describing chicken growth curves. Poultry Science 81, 1782–1788.CrossRefGoogle ScholarPubMed
Alves, WJ, Malheiros, EB, Sakomura, NK, Da Silva, EP, Gabriel, DSV, Matheus, DPR, Camila, AG and Rafael, MS 2019. In vivo description of body growth and chemical components of egg-laying pullets. Livestock Science 220, 221–229.CrossRefGoogle Scholar
Chen, CF, Foley, J, Tang, P, Li, CA, Jiang, T, Wu, XP, Widelitz, RB and Cheng, MC 2015a. Development, regeneration, and evolution of feathers. Annual Review of Animal Biosciences 3, 169–195.CrossRefGoogle ScholarPubMed
Chen, JL, Zhao, GP, Zheng, MQ, Wen, J and Yang, N 2008. Estimation of genetic parameters for contents of intramuscular fat and inosine-5'-monophosphate and carcass traits in Chinese Beijing-You chickens. Poultry Science 87, 1098–1104.CrossRefGoogle ScholarPubMed
Chuong, CM, Randall, VA, Widelitz, RB, Wu, P and Jiang, TX 2012. Physiological regeneration of skin appendages and implications for regenerative medicine. Physiology 27, 61–72.CrossRefGoogle ScholarPubMed
DesRochers, DW, Silbernagle, MD, Nadig, A and Reed, JM 2010. Body size, growth, and feather mass of the Endangered Hawaiian Moorhen (Gallinula Chloropus Sandvicensis). Pacific Science 64, 327–333.CrossRefGoogle Scholar
Duncan, TE and Duncan, SC 2004. An introduction to latent growth curve modeling. Behavior Therapy 35, 333–363.CrossRefGoogle Scholar
Gao, CQ, Yang, JX, Chen, MX, Yan, HC and Wang, XQ 2016. Growth curves and age-related changes in carcass characteristics, organs, serum parameters, and intestinal transporter gene expression in domestic pigeon (Columba livia). Poultry Science 95, 867–877.CrossRefGoogle Scholar
Gong, H, Wang, H, Wang, YX, Xue, B, Liu, B, He, JF, Wu, JH, Qi, WM and Zhang, WG 2018. Skin transcriptome reveals the dynamic changes in the Wnt pathway during integument morphogenesis of chick embryos. PLoS ONE 13, e0190933.CrossRefGoogle ScholarPubMed
Hancock, CE, Bradford, GD, Emmans, GC and Gous, RM 1995. The evaluation of the growth parameters of six strains of commercial broiler chickens. British Poultry Science 36, 247–264.CrossRefGoogle ScholarPubMed
Kjaer, J and Bessei, W 2013. The interrelationships of nutrition and feather pecking in the domestic fowl-a review. European Poultry Science 77, 1–9.Google Scholar
Leeson, S and Walsh, T 2004. Feathering in commercial poultry. ii. Factors influencing feather growth and feather loss. World′s Poultry Science Journal 60, 52–63.CrossRefGoogle Scholar
Li, XG, Chen, XL and Wang, XQ 2013. Changes in relative organ weights and intestinal transporter gene expression in embryos from White Plymouth Rock and WENS Yellow Feather Chickens. Comparative Biochemistry Physiology A-Molecular Integrative Physiology 164, 368–375.CrossRefGoogle ScholarPubMed
Lin, SJ, Wideliz, RB, Yue, Z, Li, A, Wu, X, Jiang, TX, Wu, P and Chuong, CM 2013. Feather regeneration as a model for organogenesis. Development Growth and Differentiation 55, 139–148.CrossRefGoogle ScholarPubMed
Lopez-Coello, C 2003. Potential causes of broiler feathering problems. Feathering manual, pp. 1–46. Novus International, St. Louis, MO, USA.Google Scholar
Meyer, W and Baumgartner, G 2010. Embryonal feather growth in the chicken. Journal of Anatomy 193, 611–616.CrossRefGoogle Scholar
Ministry of Agriculture of the People’s Republic of China 2004. Nutrient requirements of Chinese color-feather chicken. Feeding Standard of Chicken. 2nd edition. China Agricultural Press, Beijing, China. (In Chinese)Google Scholar
Musser, JM, Wagner, GP and Prum, RO 2015. Nuclear β-catenin localization supports homology of feathers, avian scutate scales, and alligator scales in early development. Evolution and Development 17, 185–194.CrossRefGoogle ScholarPubMed
Narinc, D, Aksoy, T, Karaman, E and Curek, DI 2010. Analysis of fitting growth models in medium growing chicken raised indoor system. Trends in Animal and Veterinary Sciences 1, 12–18.Google Scholar
Narinc, D, Karaman, E, Aksoy, T and Firat, MZ 2013. Investigation of nonlinear models to describe long-term egg production in Japanese quail. Poultry Science 92, 1676–1682.CrossRefGoogle ScholarPubMed
Scott, JM, Costa, JD and Oviedorondon, EO 2015. Incubation temperature profiles affect broiler feathering. Journal of Applied Poultry Research 24, 49–57.CrossRefGoogle Scholar
Statistical Analysis Systems (SAS ) 2002–2003. SAS version 9.1. Statistical Analysis Systems Institute Inc., Cary, NC, USA.Google Scholar
Stepinska, M, Mroz, E and Jankowski, J 2012. The effect of dietary selenium source on embryonic development in Turkeys. Folia Biologica 60, 235–241.CrossRefGoogle ScholarPubMed
Tedeschi, LO 2006. Assessment of the adequacy of mathematical models. Agricultural Systems 89, 225–247.CrossRefGoogle Scholar
Tompic, T, Dobsa, J, Legen, S, Tompic, N and Medic, H 2011. Modeling the growth pattern of in-season and off-season Ross 308 broiler breeder flocks. Poultry Science 90, 2879–2887.CrossRefGoogle ScholarPubMed
Vitezica, ZG, Marie-Etancelin, C, Bernadet, MD, Fernandez, X and Robert-Granie, C 2010. Comparison of nonlinear and spline regression models for describing mule duck growth curves. Poultry Science 89, 1778–1784.CrossRefGoogle ScholarPubMed
Wattanachant, S, Benjakul, S and Ledward, DA 2005. Microstructure and thermal characteristics of Thai indigenous and broiler chicken muscles. Poultry Science 84, 328–336.CrossRefGoogle ScholarPubMed
Wylie, LM, Robertson, GW and Hocking, PM 2003. Effects of dietary protein concentration and specific amino acids on body weight, body composition and feather growth in young turkeys. British Poultry Science 44, 75–87.CrossRefGoogle ScholarPubMed
Zach, R and Mayoh, KR 2011. Weight and feather growth of nestling tree swallows. Canadian Journal of Zoology 60, 1080–1090.CrossRefGoogle Scholar
Zheng, MQ, Gong, GF, Gao, HJ, Yao, WY, Lv, SY, Tian, LJ and Wen, J 2016. Report of Chinese broiler industry development in 2015. China Poultry 38, 67–70. (In Chinese)Google Scholar
Supplementary material: File

Xie et al. supplementary material

Xie et al. supplementary material

Download Xie et al. supplementary material(File)
File 17.1 KB