Meta-Analysis of Commercial-Scale Trials as a Means to Improve Decision-Making Processes in the Poultry Industry: A Phytogenic Feed Additive Case Study

Diego A. Martine, Carol L. Ponce-de-L, C. Vílchez
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引用次数: 7

Abstract

Background and Objective: In the current study, we sought to determine the value of a meta-analysis to improve decision-making processes related to nutrition in the poultry industry. To this end, nine commercial size experiments were conducted to test the effect of a phytogenic feed additive and three approaches were applied to the data. Materials and Methods: In all experiments, 1-day-old male Cobb 500 chicks were used and fed corn-soybean meal diets. Two dietary treatments were tested: T1, control diet and T2, control diet + feed additive at a 0.05% inclusion rate. The experimental units were broiler houses (7 experiments), floor pens (1 experiment) and cages (1 experiment). The response variables were final body weight, feed intake, feed conversion ratio, mortality and production efficiency. Analyses of variance of data from each and all the experiments were performed using SAS under completely randomized non-blocked or blocked designs, respectively. The meta-analyses were performed in R programming language. Results: No statistically significant effects were found in the evaluated variables in any of the independent experiments (p>0.12), nor following the application of a block design (p>0.08). The meta-analyses showed no statistically significant global effects in terms of final body weight (p>0.19), feed intake (p>0.23), mortality (p>0.09), or European Production Efficiency Factor (p>0.08); however, a positive global effect was found with respect to feed conversion ratio (p<0.046). Conclusion: This meta-analysis demonstrated that the phytogenic feed additive improved the efficiency of birds to convert feed to body weight (35 g less feed per 1 kg of body weight obtained). Thus, the use of meta-analyses in commercial-scale poultry trials can increase statistical power and as a result, help to detect statistical differences if they exist.
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商业规模试验作为改善家禽业决策过程的手段的荟萃分析:植物性饲料添加剂案例研究
背景和目的:在当前的研究中,我们试图确定一项荟萃分析对改善家禽业营养相关决策过程的价值。为此,进行了9项商业规模试验,以测试植物性饲料添加剂的效果,并对数据采用了三种方法。材料与方法:所有试验均选用1日龄Cobb 500雄性雏鸡,饲喂玉米-豆粕型饲粮。试验两种饲粮处理:T1为对照饲粮,T2为对照饲粮+饲料添加剂,添加率为0.05%。试验单位为鸡舍(7个)、落地栏(1个)和笼(1个)。应答变量为末重、采食量、饲料系数、死亡率和生产效率。每个和所有实验数据的方差分析分别在完全随机、非阻塞或阻塞设计下使用SAS进行。meta分析采用R编程语言进行。结果:在独立实验中,评估变量均未发现统计学上显著的影响(p>0.12),也未采用区组设计(p>0.08)。荟萃分析显示,在末重(p>0.19)、采食量(p>0.23)、死亡率(p>0.09)或欧洲生产效率因子(p>0.08)方面,全球影响无统计学意义;但整体上对饲料系数有正影响(p<0.046)。结论:本荟萃分析表明,植物性饲料添加剂提高了鸟类饲料与体重的转化效率(每获得1公斤体重可减少35克饲料)。因此,在商业规模的家禽试验中使用荟萃分析可以提高统计能力,从而有助于发现存在的统计差异。
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