Meta-Analysis of Commercial-Scale Trials as a Means to Improve Decision-Making Processes in the Poultry Industry: A Phytogenic Feed Additive Case Study
DOI:
https://doi.org/10.3923/ijps.2020.513.523Keywords:
Commercial trial, hytogenic feed additive, meta-analysis, poultry industry, statistical powerAbstract
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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