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The Scientific World Journal
Volume 2012 (2012), Article ID 785187, 10 pages
Research Article

PreZon: Prediction by Zone and Its Application to Egg Productivity in Chickens

1Department of Computer Science, National Tsing Hua University, Hsinchu City 30013, Taiwan
2Department of Medical Laboratory Science and Biotechnology, Yuanpei University, Hsin-chu City 30015, Taiwan
3Division of Biotechnology, Animal Technology Institute Taiwan, Miaoli 35053, Taiwan
4Department of Computer Science & Information Engineering, Providence University, Taichung City 43301, Taiwan

Received 6 December 2011; Accepted 1 February 2012

Academic Editors: M. E. Callebaut and D. S. Gardner

Copyright © 2012 Yen-Jen Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Taiwan red-feathered country chickens (TRFCCs) are one of the main meat resources in Taiwan. Due to the lack of any systematic breeding programs to improve egg productivity, the egg production rate of this breed has gradually decreased. The prediction by zone (PreZone) program was developed to select the chickens with low egg productivity so as to improve the egg productivity of TRFCCs before they reach maturity. Three groups ( 𝐴 , 𝐵 , and 𝐶 ) of chickens were used in this study. Two approaches were used to identify chickens with low egg productivity. The first approach used predictions based on a single dataset, and the second approach used predictions based on the union of two datasets. The levels of four serum proteins, including apolipoprotein A-I, vitellogenin, X protein (an IGF-I-like protein), and apo VLDL-II, were measured in chickens that were 8, 14, 22, or 24 weeks old. Total egg numbers were recorded for each individual bird during the egg production period. PreZone analysis was performed using the four serum protein levels as selection parameters, and the results were compared to those obtained using a first-order multiple linear regression method with the same parameters. The PreZone program provides another prediction method that can be used to validate datasets with a low correlation between response and predictors. It can be used to find low and improve egg productivity in TRFCCs by selecting the best chickens before they reach maturity.