Validation with the Dynamic Prediction Model of Protein and Amino Acid Requirements for Growth Performance and Health in Layer Chicks

利用动态预测模型验证蛋鸡生长性能和健康所需的蛋白质和氨基酸需求。

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Abstract

This study evaluated an established dynamic prediction model for protein and amino acid nutritional requirements on growth performance and health in layer chicks. A total of 288 one-day-old healthy Jing Tint 6 chicks were randomly divided into four treatment groups with 6 replicates of 12 chicks each. The chicks in the four groups were fed a basal diet (BD) according to the feeding standards and a model diet (MD) based on the dynamic prediction model for protein and amino acid values at 90%, 100%, or 110% for 6 weeks. The results showed that, compared to the BD, the 110% MD increased (p < 0.05) the FI and the 100% MD had no effect (p > 0.05) on FI, BWG, and FCR of chicks throughout the entire feeding phase. The 90% MD, however, significantly reduced (p < 0.05) FI and BWG, while also increasing (p < 0.05) FCR during the 3-6- and 0-6-week periods. Additionally, compared to the BD, the 100% MD had a lower (p < 0.05) intake of crude protein, methionine, lysine, and threonine than that of the BD. Both the 100% and 110% MDs increased (p < 0.05) bursa weight and its index at the 2nd week, while the 90% MD reduced (p < 0.05) the weights of the liver, spleen, and pancreas at the 6th week when compared to the BD. Moreover, the 100% MD increased (p < 0.05) the weights of the duodenum and jejunum, while the 90% MD decreased (p < 0.05) jejunum and ileum length at the 2nd or 6th week. Furthermore, no differences (p > 0.05) were found in serum ALT, AST, BUN, and UA between the 100% MD and BD groups. In conclusion, the dynamic prediction model can minimize protein waste while supporting healthy growth and development in layer chicks.

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