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Development of models for predicting the nutritional requirements of pregnant goats

Grant number: 13/04758-5
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): June 01, 2013
Effective date (End): January 31, 2017
Field of knowledge:Agronomical Sciences - Animal Husbandry - Animal Nutrition and Feeding
Principal researcher:Izabelle Auxiliadora Molina de Almeida Teixeira
Grantee:Carla Joice Härter
Home Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
Associated research grant:08/58351-5 - Metabolism, nutritional, requirements and carcass traits of growing goats, AP.TEM
Associated scholarship(s):14/11166-0 - Modelling the energy and protein requirements of pregnant dairy goats, BE.EP.PD


The world goat herd has increased more compared to other livestock species mainly due to ease of adaptation of the goat to different environments. Thus, the nutritional requirements of these animals change according to the environment to which they are, in addition, other physiological factors can affect their nutritional requirements , such as gender, breed and reproductive stage. In this sense, researchers have focused on developing mathematical models that can better predict the nutritional requirements in order to optimize animal performance. The objective of this study is to develop a dynamic-empirical model that can better predict protein and energy requirements of pregnant goats. The database to be used to develop the models is from data generated in the Project FAPESP 2009/10125-0, 2007/58239-8 and 2006/60480-2, which involve development of fetus and pregnancy products, as well as nutritional requirements of pregnant goats. The equations will be developed using the Marquadt method in the NLIN procedure of SAS. Criteria used to select the model that best fit the characteristics are: convergence of the analysis, mean square error and coefficient of determination of the model (R2). The models will be evaluated with an independent database by regressing residual (observed minus predicted) values on the predicted values centered on their mean values.

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Scientific publications (5)
(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)
FIORENTINI, G.; SANTANA, M. O.; MESSANA, J. D.; VALENTE, A. L. S.; HARTER, C. J.; RABELO, C. H. S.; BARBERO, R. P.; LANNA, D. P. D.; REIS, R. A.; BERCHIELLI, T. T. Effect of lipid sources on fatty acid profiles of meat from pasture- and feedlot-finished Nellore bulls. LIVESTOCK SCIENCE, v. 211, p. 52-60, MAY 2018. Web of Science Citations: 0.
HARTER, C. J.; LIMA, L. D.; CASTAGNINO, D. S.; SILVA, H. O.; FIGUEIREDO, F. O. M.; ST-PIERRE, N. R.; RESENDE, K. T.; TEIXEIRA, I. A. M. A. Net mineral requirements of dairy goats during pregnancy. ANIMAL, v. 11, n. 9, p. 1513-1521, SEP 2017. Web of Science Citations: 0.
HARTER, C. J.; LIMA, L. D.; SILVA, H. G. O.; CASTAGNINO, D. S.; RIVERA, A. R.; RESENDE, K. T.; TEIXEIRA, I. A. M. A. Energy and protein requirements for maintenance of dairy goats during pregnancy and their efficiencies of use. JOURNAL OF ANIMAL SCIENCE, v. 95, n. 9, p. 4181-4193, SEP 2017. Web of Science Citations: 2.
MENDONCA, A. N.; HARTER, C. J.; SOUZA, S. F.; OLIVEIRA, D.; BOAVENTURA NETO, O.; BIAGIOLI, B.; RESENDE, K. T.; TEIXEIRA, I. A. M. A. Net mineral requirements for growth of Saanen goat kids in early life are similar among genders. JOURNAL OF ANIMAL PHYSIOLOGY AND ANIMAL NUTRITION, v. 101, n. 1, p. 113-120, FEB 2017. Web of Science Citations: 5.
HAERTER, CARLA J.; SILVA, HERYMA G. O.; LIMA, LISIANE D.; CASTAGNINO, DOUGLAS S.; RIVERA, ASTRID R.; BOAVENTURA NETO, OSCAR; GOMES, RAFAEL A.; CANOLA, JULIO C.; RESENDE, KLEBER T.; TEIXEIRA, IZABELLE A. M. A. Ultrasonographic measurements of kidney fat thickness and Longissimus muscle area in predicting body composition of pregnant goats. ANIMAL PRODUCTION SCIENCE, v. 54, n. 9, p. 1481-1485, 2014. Web of Science Citations: 1.

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