Modeling Cumulative Egg Production Curves of MiaHens using Nonlinear Functions

Received: 17-04-2023

Accepted: 29-08-2023

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CHĂN NUÔI – THÚ Y – THỦY SẢN

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Bo, H., Tuan, H., Dang, P., Thinh, N., Doan, B., & Luc, D. (2024). Modeling Cumulative Egg Production Curves of MiaHens using Nonlinear Functions. Vietnam Journal of Agricultural Sciences, 21(9), 1111–1118. http://testtapchi.vnua.edu.vn/index.php/vjasvn/article/view/1183

Modeling Cumulative Egg Production Curves of MiaHens using Nonlinear Functions

Ha Xuan Bo (*) 1 , Hoang Anh Tuan 2 , Pham Kim Dang 2 , Nguyen Hoang Thinh 2 , Bui Huu Doan 2 , Do Duc Luc 2

  • 1 Khoa Chăn nuôi và Nuôi trồng thủy sản, Học viện Nông nghiệp Việt Nam
  • 2 Khoa Chăn nuôi, Học viện Nông nghiệp Việt Nam
  • Keywords

    Nonlinear models, egg production curve, local chicken, Mia hens

    Abstract


    This study was conducted to describe the cumulative egg production curves and determine the best model to estimate the cumulative egg production of Mia hens raised at Hadinco livestock farm, Son Tay Town, Hanoi from June 2021 to May 2022. The cumulative egg production was recorded from 23 weeks (the zero-week egglaying) to 74 weeks of age (51 weeks of the egglaying) from 300 Mia hens. Nine nonlinear models were used to be fitted the data of cumulative egg production of Mia hens. The upper asymptotic cumulative egg production at 52 weeks of egglaying was 85.98 eggs. The number of eggs produced (NEPt) reached the maximum at the 9th week of egglaying (2.57 eggs per hen per week). Lopez function appeared best to describe cumulative egg production of Mia hens with the highest coefficient of determination (99.91%) and the lowest AIC (377.74), BIC (392.99), and SER (0.45). These results suggest that Lopez functions can be applied to estimate the cumulative egg production, number of eggs per hen per week of other local chicken breeds that similar egg production as the Mia hens.

    References

    Akilli A. & Gorgulu O. (2019). Comparison of Different Back-Propagation Algorithms and Nonlinear Regression Models for Egg Production Curve Fitting. Cappadocia, Turkey.178.

    Akilli A. & Gorgulu O. (2020). Comparative assessments of multivariate nonlinear fuzzy regression techniques for egg production curve. Tropical Animal Health and Production.52(4): 2119-2127.

    Anang A. & Indrijani H. (2006). Mathematical models to describe egg production in laying hens. J. Ilmu Ternak.6: 91-95.

    Bindya L., Murthy H., Jayashankar M., Govindaiah & Mg (2010). Mathematical models for egg production in an Indian colored broiler dam line. International Journal of Poultry Science.9(9): 916-919.

    Bridges T.C., Turner L.W., Stahly T.S., Usry J.L. & Loewer O.J. (1992). Modeling the physiological growth of swine part I: Model logic and growth concepts. Transactions of the ASAE.35(3): 1019-1028.

    Darmani K.H. & France J. (2019). Modelling cumulative egg production in laying hens and parent stocks of broiler chickens using classical growth functions. British Poultry Science.60(5): 564-569.

    Duc N.V. & Long T. (2008). Poultry production systems in Vietnam.Rome: Food and agriculture organization.

    Đỗ Kim Chung & Nguyễn Xuân Trạch (2022). Hiệu quả sử dụng đầu vào trong nông nghiệp: Quan điểm của nhà kỹ thuật, nhà kinh tế và một số kiến nghị. Tạp chí Khoa Học Nông nghiệp Việt Nam. 20(8): 1134-1144.

    Elzhov T.V., Mullen K.M., Spiess A., Bolker B., Mullen M.M. & Suggests M. (2016). Package ‘minpack. lm’. Title R Interface to the Levenberg-Marquardt Nonlinear Least-Squares Algorithm Found in MINPACK, Plus Support for Bounds’. Retrieved from https://cran.rproject.org/web/ packages/minpack.lm/minpack.lm.pdfon Mar 31, 2023.

    Ganesan R., Dhanavanthan P., Sreenivasaiah P. & Ponnuvel P. (2011). Comparative study of non-linear models for describing poultry egg production in Puducherry. Current Biotica.5(3): 289-298.

    García-Muñiz J.G., Ramírez-Valverde R., Núñez-Domínguez R. & Hidalgo-Moreno J.A. (2019). Dataset on growth curves of Boer goats fitted by ten non-linear functions. Data Brief.23: 103672.

    Gompertz B. (1825). XXIV. On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. In a letter to Francis Baily, Esq. FRS &c. Philosophical transactions of the Royal Society of London.(115): 513-583.

    Hà Xuân Bộ, Lê Việt Phương & Đỗ Đức Lực (2022). Mô tả năng suất trứng cộng dồn của gà D310 và Isa Brown bằng một số hàm sinh trưởng. Tạp chí Khoa học kỹ thuật chăn nuôi.278(6.22): 15-20.

    Hoàng Anh Tuấn (2023). Chọn lọc nâng cao năng suất sinh tưởng của gà Mía bằng chỉ thị phân tử. Luận án tiến sĩ, Học viện Nông nghiệp Việt Nam. 128tr.

    Lan Phuong T.N., Dong Xuan K.D.T. & Szalay I. (2015). Traditions and local use of native Vietnamese chicken breeds in sustainable rural farming. World's Poultry Science Journal.71(2): 385-396.

    López S., France J., Gerrits W.J., Dhanoa M.S., Humphries D.J. & Dijkstra J. (2000). A generalized Michaelis-Menten equation for the analysis of growth. Journal of Animal Science.78(7): 1816-28.

    Minh L.K., Miyoshi S. & Mitsumoto T. (1995). Multiphasic model of egg production in laying hens. Japanese poultry science.32(3): 161-168.

    Murthy D.P., Xie M. & Jiang R. (2004). Weibull models.(505). John Wiley & Sons. pp. 1-17.

    Narinc D., Üçkardeş F. & Aslan E. (2014). Egg production curve analyses in poultry science. World's Poultry Science Journal.70(4): 817-828.

    Nguyen Hoang T., Do H.T.T., Bui D.H., Pham D.K., Hoang T.A. & Do D.N. (2021). Evaluation of non‐linear growth curve models in the Vietnamese indigenous Mia chicken. Animal Science Journal. 92(1): e13483.

    Otwinowska-Mindur A., Gumulka M. & Kania-Gierdziewicz J. (2016). Mathematical models for egg production in broiler breeder hens. Annals of Animal Science.16(4): 1185.

    Pearl R. (1977). The biology of population growth.Ayer Publishing.

    R Core Team (2022). R: A language and environment for statistical computing. R foundation for statistical computing Vienna, Austria.

    Richards O.W. & Kavanagh A.J. (1945). The analysis of growing form. Oxford: Oxford Univ.

    Savegnago R.P., Cruz V.A.R., Ramos S.B., Caetano S.L., Schmidt G.S., Ledur M.C., El Faro L. & Munari D.P. (2012). Egg production curve fitting using nonlinear models for selected and nonselected lines of White Leghorn hens. Poultry Science.91(11): 2977-2987.

    Savegnago R.P., Nunes B.N., Caetano S.L., Ferraudo A.S., Schmidt G.S., Ledur M.C. & Munari D.P. (2011). Comparison of logistic and neural network models to fit to the egg production curve of White Leghorn hens. Poultry Science.90(3): 705-711.

    Von Bertalanffy L. (1957). Quantitative laws for metabolism and growth. The quarterly review of biology.32(3): 217-231.

    Wolc A., Arango J., Rubinoff I. & Dekkers J.C. (2020). A biphasic curve for modeling, classifying, and predicting egg production in single cycle and molted flocks. Poultry Science.99(4): 2007-2010.