A Model to Estimate the Laying Curve of White Leghorn Hens in the Last Three Years in the Province of Ciego de Avila, Cuba
Resumen
A number of 15 976 egg production records from three hen batches in Ciego de Avila (2016) were used. The laying curve was characterized in similar conditions to IIA (2013), Republic of Cuba. The estimation of the laying curves made of mean productions from three stages in a year was presented. Four mathematical models were applied for curve adjustment: McNally, Wood, quadratic logarithmic, and linear hyperbolic. Different statistical criteria were used for validation: determination coefficient (R2), (R2A), residual analysis, and others. The means, standard deviation (SD), standard error (SE), and variation coefficient (VC) were made for each period. Egg production accounted for 84.35 and 60.61% of total laying, the best year was 2016. The highest values of SE and VC were observed at the end of production, as expected. Adjustment and discrimination showed a high adjustment criterion in the four models, but the best values were observed with McNally (1971), in R2 (99.60%), and adjusted R2 (99.42%). McNally reached the highest adjustment values: YM=-2233.62-18583.8*(MONTH/426)-029.0*(MONTH/426**2+780.241*log (426/MONTH)-68.1269*(log(426/MONTH))*2, and it described the best production of White Leghorn (L33) hens in Ciego de Avila.
Descargas
Citas
AGUDELO, D. A., CERÓN, M. F. yRESTREPO, L. F. (2007). Modelación de las funciones de crecimiento aplicadas a la producción animal. Revista Colombiana de Ciencias Pecuarias, 21(1), 39-58.
AGGREY, S. E. (2009). Logistic Nonlinear Mixed Effects Model for Estimating Growth Parameters. Poultry science, 88(2), 276-280.
AHMADI, H yGOLIAN, A. (2008) Neural Network Model for Egg Production Curve. Journal of Animal and Veterinary Advances 2008; 7: 1168-1170. Retrieved on August 20, 2009, from http://medwelljournals.com/fulltext/java/2008/1168-1170.pdf.
BUDIMULYATI, S.; NOOR, R. R.;SAEFUDDIN, A. yTALIB, C. (2012). Comparison on Accuracy of Logistic, Gompertz and von Bertalanffy Models in Predicting Growth of New Born Calf Until First Mating of Holstein Friesian Heifers. Journal of the Indonesian Tropical Animal Agriculture, 37(3), 151-160.
CANCA (2016).Programa de preparación de las pollonas para el comienzo de la postura. Memorias del III Congreso Nacional de Avicultura, Centro de Convenciones Plaza América,Varadero, Cuba.
GALEANO-VASCO, L. yCERÓN-MUÑOZ, M. (2013). Modelación del crecimiento de pollitas Lohmann LSL con redes neuronales y modelos de regresión no lineal. Revista MVZ Córdoba, 18(3), 3851-3860.
IIA (2013).Instructivo técnico. La Habana, Cuba: Instituto de Investigaciones Avícolas.
JOHNSON, L. (2015). Factors that affect egg production in chickens. Panhandle.Retrieved on March 13, 2016, from www.Ifs.ufl.edu/phag2015/02/27.
MCNALLY, D. H. (1971). Note: Mathematical Model for Poultry Egg Production. Biometrics, 27, (3), 735-738.
SALVADOR, E.yGUEVARA, V. (2013). Desarrollo y validación de un modelo de predicción del requerimiento óptimo de aminoácidos esenciales y del comportamiento productivo en ponedoras comerciales. Revista de Investigaciones Veterinarias del Perú, 24(3), 264-276.
SAS (2010).Statistical Analysis System(versión 9.1.3).USA: (TSMO) Cary, NC.
VAN DE BRAAK, T. (2015). Introducing the ISA Dual-ISA Focus.ISA Newsletter, (13). Retrieved on December 18, 2016, fromwww.isapoultry.com.
WOLFINGER, R.yO'CONNELL, M. (1993). Generalized Linear Mixed Models a Pseudo-Likelihood Approach. Journal of Statistical Computation and Simulation, 48(3-4), 233-243.
WOOD, P. D. P. (1967). Algebraic Model of the Lactation Curve in Cattle. Nature, 216 (2), 164-165.
Los autores de los artículos publicados en RPA retienen los derechos de autor de su trabajo, de marca y patente, y también sobre cualquier proceso o procedimiento descrito en el artículo, así como a compartir, copiar, distribuir, ejecutar y comunicar públicamente el artículo publicado en la RPA o cualquier parte de aquel siempre que indiquen la fuente de publicación (autores del trabajo, revista, volumen, número y fecha), pero están de acuerdo en que la revista publique los trabajos bajo una licencia Creative Commons.
Licencia Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
