Validation of Prediction Equations of the Egg Characteristics in Laying Hens

Document Type : Original Paper

Authors

1 Department of Nutrition, Universidad Nacional Agraria La Molina, Lima, Peru

2 Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR 72701, USA

Abstract

Poultry researchers have used mathematical models to explain some laying bird responses. There are many equations of the egg characteristics, but their validity has not yet been confirmed. Therefore, the aim of the current study was to assess the accuracy of the equations proposed to predict egg characteristics in laying hens. A total of one hundred forty-eight prediction equations of egg characteristics were collected from different studies. A total of 781 eggs from 75-week-old Hy-Line laying hens were gathered to measure egg quality characteristics, and other egg characteristics were calculated using these measurements. The residuals of the difference of observed and predicted values were used to calculate accuracy measurements like mean absolute deviation (MAD), mean squared error of prediction (MSEP), mean absolute percentage error (MAPE) and root mean squared error of prediction (RMSEP). RMSEP was used to estimate the error of the model (EM) with a 12% as the maximum level of validation of the egg characteristics prediction equation and 1.2% only for specific gravity. Nine egg characteristic prediction equations were validated with great accuracy because validated equations showed a value of MAD, MSEP, MAPE and RMSEP very low and EM less than 12%. Equations validated for external egg characteristic used easy-to-measure traits (i.e., egg weight, egg length, and egg width) as predictor variables. Fifteen egg characteristic prediction equations were validated with considerable accuracy. These equations might shorten the process of egg quality determination, reduce the waste of eggs, and thereby saving time and money.

Keywords

References

Abanikannda OT & Leigh AO. 2007. Allometric relationships between composition and size of chicken table eggs. International Journal of Poultry Science 6: 211-217. DOI: 10.3923/ijps.2007.211.217
Achen CH. 1982. Interpreting and using regression. Sage publications, California. USA. Pages, 56-67.
Alipanah M, Deljio J, Rokouie M & Mohammadnia, R. 2013. Heritability and genetic and phenotypic correlation of egg quality traits in Khazak layers. Trakia Journal of Sciences, 2: 175–180.
Alkan S, Karabag K, Galic A & Balcioglu MS. 2008. Predicting yolk height, yolk width, albumen length, eggshell weight, egg shape index, eggshell thickness, egg surface area of Japanese quails using various eggs traits as regressors. International Journal of Poultry Science, 7: 85–88. DOI: 10.3923/ijps.2008.85.88
Alkan S, Mendes M, Karabag K & Karsli T. 2009. Effects of selection on allometric relationships between egg components and egg weight in Japanese quails of different lines. Archiv Fur Geflugelkunde, 74: 121-125.
Callejo Ramos A, Cardoso Maciel W, Daza Andrada A, Siqueira de Castro Teixeira R & Buxade Carbo C. 2010. Effect of bird age and storage system on physical properties of eggs from brown laying hens. PUBVET, Publicaçoes em Medicina veterinaria e Zootecnia, 4: 961-71.
Chandler J & Hopewell S. 2013. Cochrane Methods - twenty years experience in developing systematic review methods. Systematic Reviews, 2: 76. DOI: 10.1186/2046-4053-2-76
Çiçek TR, Uckardes F, Narinc D & Aksoy T. 2013. Comparison of principal component regression with the least square method in prediction of internal egg quality characteristics in Japanese quails. Kafkas Universitesi Veteriner Fakultesi Dergisi, 17: 687-692.
Debnath BC & Ghosh TK. 2015. Phenotypic correlations between some external and internal egg quality traits in Gramapriya layers. Exploratory Animal and Medical Research, 5: 78-85.
Dermanović V & Mitrović S. 2013. Phenotype variability of external quality traits of fertile eggs of partridge Italian bread in semi extensive breeding system. Biotechnology in Animal Husbandry, 29: 477–482. DOI: 10.2298/BAH1303477D
Fajemilehin SO. 2008. Predicting post-broken traits using the pre-broken traits as regressors in the eggs of helmeted guinea fowl. African Journal of Agricultural Research, 3: 578-580.
Fajemilehin SOK, Odubola OO, Fagbuaro SS & Akinyemi MO. 2009. Phenotypic correlations between some external and internal egg quality traits in the Nigerian helmeted guinea fowl, Numida meleagris galeata pallas. Applied Tropical Agriculture, 14: 102-108.
Goldberger AS. 1991. A course in econometrics. Cambridge. Massachusettes: Harvard University Press. 432 Pages.
Harms RH, Rossi AF, Sloan DR, Miles RD & Christmas RB. 1990. A method for estimating shell weight and correcting specific gravity for egg weight in eggshell quality studies. Poultry Science, 69: 48–52. DOI: 10.3382/ps.0690048
Hernández AJ. 1993. Uso y abuso del coeficiente de determinación. ESIC market, 79: 77–92.
Hillston J. 2003. Model validation and verification. Edinburgh: University of Edinburgh.
Hisasaga C, Shinn SE & Tarrant KJ. 2020. Survey of egg quality in commercially available table eggs. Poultry Science, 99: 7202-7206. DOI: 10.1016/j.psj.2020.09.049
Iposu SO, Onwuka CF & Eruvbetine D. 1993. The relationship between selected egg quality traits and egg size. Nigerian Journal of Animal Production 21: 156-160. DOI: 10.51791/njapv21i1.1175
Inca JS. 2016. Validación de ecuaciones de predicción de las características de la calidad de huevo en gallinas de última fase de producción. Master thesis. Universidad Nacional Agraria La Molina, Lima, Peru. 295 Pages.
Inca JS, Martinez DA & Vilchez C. 2020. Phenotypic correlation between external and internal egg quality characteristics in 85-week-old laying hens. International Journal of Poultry Science, 19: 346-355. DOI: 10.3923/ijps.2020.346.355
Khurshid A, Farooq M, Durrani F, Sarbiland K & Chand N. 2003. Predicting egg weight, Shell weight, Shell thickness and hatching chick weight of Japanese quails using various egg traits as regressors. International Journal of Poultry Science, 2: 164-167. DOI: 10.3923/ijps.2003.164.167
Kul S & Seker I. 2004. Phenotypic correlation between some external and internal egg quality traits in the Japanese quail (Coturnix coturnix Japonica). International Journal of Poultry Science, 3: 400–405. DOI: 10.3923/ijps.2004.400.405
Martínez E. 2005. Errores frecuentes en la interpretación del coeficiente de determinación lineal. Anuario Jurídico y Económico Escurialense, 38: 315–332.
Matthews WA & Summer DA. 2015. Effects of housing system on the costs of commercial egg production. Poultry Science, 94: 552-557. DOI: 10.3382/ps/peu011
Mube HK, Kana JR, Tadondjou CD, Yemdjie DD, Manjeli Y & Teguia A. 2014. Laying performances and egg quality of local barred hens under improved conditions in Cameroon. Journal of Applied Biosciences, 74: 6157–6163. DOI: 10.4314/jab.v74i1.8
Narushin VG. 2005. Egg geometry calculation using the measurements of length and Breadth. Poultry Science, 84: 482-484. DOI: 10.1093/ps/84.3.482
Nordstrom JO & Ousterhout LE. 1982. Estimation of shell weight and shell thickness from egg specific gravity and egg weight. Poultry Science, 61: 1991–1995. DOI: 10.3382/ps.0611991
Ojedapo LO. 2013. Phenotypic correlation between the external and internal egg quality traits of pharaoh quail reared in derived savanna zone of Nigeria. Journal of Biology, Agriculture and Healthcare, 3: 80-84.
Olawumi SO & Ogunlade JT. 2008. Phenotypic correlations between some external and internal egg quality traits in the exotic Isa Brown layer breeders. Asian Journal of Poultry Science, 2: 30–35. DOI: 10.3923/ajpsaj.2008.30.35
Onunkwo DN & Okoro IC. 2015. Predicting egg quality and egg production traits using egg weight and body weight respectively in three varieties of helmeted guinea fowls in humid tropics. International Journal of Livestock Research, 5: 111-121. DOI: 10.5455/ijlr.20150329124016
Roberts JR, Chousalkar K & Samiullah S. 2013. Egg quality and age of laying hens: implications for product safety. Animal Production Science, 53: 1291–1297. DOI: 10.1071/AN12345
RStudio Team. 2016. RStudio: Integrated Development for R. Boston, USA.
Salvador E & Guevara V. 2013. Development and validation of a model to predict the optimum requirement of essential amino acids and performance in commercial laying hens. Departamento de producción animal, facultad de medicina veterinaria y zootecnia. Universidad Nacional San Luis Gonzaga, Ica. Perú. Revista de Investigaciones Veterinarias del Perú, 24: 264–276. DOI: 10.15381/rivep.v24i3.2574
Seker I. 2004. Prediction of albumen weight, yolk weight, and shell weight as egg weight in Japanese quail eggs. Uludag University Journal of the Faculty of Veterinary Medicine, 23: 87-92.
Sotherland PR & Rahn H. 1987. On the composition of bird eggs. Condor, 89: 48-65. DOI: 10.2307/1368759
Tedeschi LO. 2006. Assessment of the adequacy of mathematical models. Agricultural Systems, 89: 225–247. DOI: 10.1016/j.agsy.2005.11.004
Tedeschi LO & Menendez HM. 2020. Mathematical modeling in animal production. In: Animal Agriculture: Sustainability, Challenges and Innovations.  Elsevier Publisher. USA. Pages, 431-453. DOI: 10.1016/B978-0-12-817052-6.00025-2
USDA U.S. Department of Agriculture. 2018. World agricultural supply and demand estimates. WASDE 574. USDA, Washington, D.C.
USDA. 2020. America’s Farmers: Resilient Throughout the COVID Pandemic. Available: https://www.usda.gov/media/
Vandeput, N. 2020. Data science for supply chain forecasting. Second Edition. De Gruyter. 282 pages. DOI: 10.1515/9783110671124-201
Willems E, Wang Y, Willemsepn H, Lesuisse J, Franssens L, Guo X, Koppenol A, Buyse J, Decuypere E & Everaert N. 2013. Partial albumen removal early during embryonic development of layer-type chickens has negative consequences on laying performance in adult life. Poultry Science, 92: 1905-1915. DOI: 10.3382/ps.2012-03003
Yakubu A, Ogah DM & Barde RE. 2008. Productivity and egg quality characteristics of free range naked neck and normal feathered Nigerian indigenous chickens. International Journal of Poultry Science, 7: 579-585. DOI: 10.3923/ijps.2008.579.585
Zhang C, Ning H, Xu Y, Hou C & Yang N. 2005. Heritabilities and Genetic and Phenotypic Correlations of Egg Quality Traits in Brown-Egg Dwarf Layers. Poultry Science, 84: 1209–1213. DOI: 10.1093/ps/84.8.1209
Zhang B, Weil J, Guerra AB, Maharjan P, Hilton K, Suesuttajit N, Martinez D & Coon CN. 2020. Egg shell quality and bone status as affected by environmental temperature, Ca and non-phytate O intake and in vitro limestone solubility in Single-Comb White Leghorn hens. International Journal of Poultry Science, 19: 219-231. DOI: 10.3923/ijps.2020.219.23
Poultry Science Journal
Volume 10, Issue 1
August 2022
Pages 71-82

Files

Share

How to cite

Statistics