Bibliographic citations
Huaringa, D., (2021). Validación y desarrollo de ecuaciones de predicción de calidad de huevo de gallinas con diferentes tiempos de almacenamiento [Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/5085
Huaringa, D., Validación y desarrollo de ecuaciones de predicción de calidad de huevo de gallinas con diferentes tiempos de almacenamiento []. PE: Universidad Nacional Agraria La Molina; 2021. https://hdl.handle.net/20.500.12996/5085
@mastersthesis{sunedu/3045608,
title = "Validación y desarrollo de ecuaciones de predicción de calidad de huevo de gallinas con diferentes tiempos de almacenamiento",
author = "Huaringa Esteban, Daniel Jhonathan",
publisher = "Universidad Nacional Agraria La Molina",
year = "2021"
}
The present study investigated the storage time on the egg quality of laying hens, and aimed to validate and develop prediction equations that allow determining the external and internal quality parameters of eggs stored up to fourteen days. 720 eggs from Hy-Line Brown hens in the second production phase were worked. The hens were fed a corn-soybean diet, with a daily consumption of 120 grams and water ad libitum. The eggs were divided into three groups of 240 and stored to later measure their internal and external characteristics. Measurements were made at one, seven and fourteen days of storage. The variables egg weight (EW), egg length (EL), egg diameter (ED), shell weight (SW), yolk height (YH), yolk weight (YW), albumen diameter (AD), albumen height (AH), albumen weight (AW), shell thickness (ST), egg surface area (ESA) and egg shape index (ESI) were used. Statistical analysis indicates significant differences (p<0.05) in most of the egg characteristics at different storage times. With the data collected, four prediction equations taken from a previous trial can be validated: yolk height (YW = 2.908 + 0.261ED; R2 = 46.50), yolk weight (YW = 3.358 + 0.214EW; R2 = 20.25), area egg surface (ESA = 6.254 + 1.387EW; R 2 = 99.40) and egg shape index (ESI = 0.79 + 0.0307ED - 0.02423EL; R 2 = 98.80); the validation was carried out with an error level of less than 12%. Six prediction equations were developed using the linear regression model for the variables albumen diameter (AD = 39.136 + 0.797EL; R2 = 1.13), albumen diameter (AD = 35.509 + 0.650EL; R2 = 2.24), albumen height (AH = 12.017 - 0.076ED; R2 = 31.44), albumen weight (AW = -2.918 + 0.683EW; R2 = 83.34), shell weight (SW = -0.315 + 0.099EW; R2 = 30.05) and Shell thickness (ST = 0.215 + 0.039SW; R2 = 56.93).
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