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Systematic review and meta-analysis with adjustment of mathematical models for nonlinear formulation for broilers and laying hens


This project will aim to develop systematic reviews and meta-analysis with adjustment of mathematical models to estimate the nutritional requirements (metabolizable energy, crude protein, methionine, lysine, threonine, tryptophan, valine, calcium, available phosphorus and sodium) for broilers and laying hens. These models will be used to formulate diets for nonlinear procedures (maximum profit ration instead of minimum cost ration). For the systematic review will be adopted the methodology proposed by CASTRO et al. (2002) and for the collected data will be adjusted response surface models (FREUND & LITTELL, 2000). In these models will be adopted as independent variables the nutrients aforementioned, and age, environmental temperature, stocking density and sex. The dependent variables will be those used to calculate the profit, such as feed intake, body weight, egg production, feed conversion, among others. A nonlinear program for diet formulation in Excel ® program with the help of Solver ® supplement and the equations generated by the study will be elaborated. This program formulation will determine the nutritional levels and the ration of maximum profit for different market scenarios. For preparation of this program the principles used by GUEVARA (2004) will be applied. This program will be available for free to interested parties. Two experiments will be conducted to compare the nonlinear diet formulation (maximum profit) with the linear formulation (minimal cost), being one for broilers and other for laying hens. (AU)

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(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
TW ALMEIDA; AL SILVA; AP SACCOMANI; JA MUÑOZ; RT SILVA; NV FRANCA; DE FARIA; DE FARIA FILHO. Performance and Egg Quality of Commercial Laying Hens Fed Diets Formulated Using Non-Linear Programming. Brazilian Journal of Poultry Science, v. 21, n. 3, . (14/01573-7)

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