| Grant number: | 14/14734-9 |
| Support Opportunities: | Regular Research Grants |
| Start date: | November 01, 2014 |
| End date: | June 30, 2017 |
| Field of knowledge: | Agronomical Sciences - Animal Husbandry - Animal Nutrition and Feeding |
| Principal Investigator: | Izabelle Auxiliadora Molina de Almeida Teixeira |
| Grantee: | Izabelle Auxiliadora Molina de Almeida Teixeira |
| Host Institution: | Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil |
| Associated researchers: | Kléber Tomás de Resende |
| Associated research grant(s): | 15/50444-8 - Improving our understanding of nutritional requirements to reduce environmental impact of livestock, AP.R SPRINT |
Abstract
Knowledge of the nutritional requirements is essential for optimal animal production. Considering its importance, several studies were conducted in order to determine the nutrient requirements for goats on Brazilian conditions. Despite this effort, it is still possible to verify the need for a comprehensive study on the requirements of growing goats, especially considering the influence of factors such as gender, stage of growth and productive aptitude. Another factor to be considered for estimating nutrient requirements is the prediction of dry matter intake (DMI), because it has been done with low accuracy and precision, based on data collected in different environment conditions or even extrapolated from other species. Thus the aim of this study is to develop models to estimate dry matter intake and the requirements of energy, protein and macro minerals for growing goats. For this, it will be used a database comprising individual data of 564 animals from studies conducted in Brazil between 1989 and 2014. For developing the models it will be evaluate the variables that show the best fit to estimate DMI. The energy requirements for maintenance will be estimated from the heat production when the metabolizable energy intake is equal to zero. The mineral and protein requirements for maintenance will be considered as their retentions to zero intake level. The energy, protein and mineral requirements for growth will be estimated by linear and non-linear allometric model, and their bias will be evaluated. For the development of linear models will be used PROC MIXED and for nonlinear model the PROC NLINMIX of SAS. The sensibility of the models will be analyzed using the MCMC technique. Moreover, the models will be evaluated using criteria such as R2, coefficient of concordance correlation, the prediction meansquare error and its decomposition into mean bias and linear bias. (AU)
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