Rodrigo Pelicioni Savegnago

CV Lattes ResearcherID

Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Faculdade de Ciências Agrárias e Veterinárias (FCAV) (Institutional affiliation from the last research proposal)
Birthplace: Brazil

Rodrigo Pelicioni Savegnago has bachelor degree in Biological Science at Universidade Estadual Paulista (2007), professional master degree in Sugarcane Technology Administration at Universidade Federal de São Carlos (2010), academic master degree (2010) and doctoral degree (2013) in Animal Breeding and Genetics at Universidade Estadual Paulista. He is actually a postdoctoral research fellow at the Department of Mathematics and Statistics, Universidade Estadual Paulista, Jaboticabal-SP, Brazil. Rodrigo has experience in data analysis and statistical modeling applied to Animal Breeding and Genetics and his research is centered on statistical analysis in quantitative genetics, multivariate analysis, neural networks and uses of genomic information in animal breeding. (Source: Lattes Curriculum)

News published in Agência FAPESP Newsletter about the researcher

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Scholarships in Brazil

Completed (most recent)

Abstract
Generally only few animals from a reference population are genotyped due to the high costs of genotyping. The aim of this research will be to evaluate which animals must be genotyped in order to get the best predictions of the genetic merit using genome-enabled prediction models. The public data from a heterogeneous population of mice will be used in this study. Public data sets of genoty…
Prediction of breeding values in a experimental mice population using selective genotyping, BP.PD
Application of neural networks and random regression models for predict the breeding value of milk production in Holstein cows, BP.DR

Scholarships abroad

Completed (most recent)

Abstract
The aim of this study is to evaluate the potential of the use of the artificial neural networks to predict the milk production and the estimates of breeding values of this trait in Holstein cows. It will be evaluated about 30,000 monthly dairy milk controls of approximately 3,500 cows in the first lactation. It will be used a random regression model to estimate the genetic parameters of t…
Application of neural networks and random regression models for predict the breeding value of milk production in Holstein cows, BE.EP.DR

Virtual Library in numbers * Updated data on August 09, 2025

Total / Available in English

2 / 2	Completed scholarships in Brazil
1 / 1	Completed scholarships abroad
3 / 3	All Scholarships

Associated processes

Most frequent collaborators in research granted by FAPESP

Danísio Prado Munari

Keywords used by the researcher

Agronomical Sciences Animal Husbandry

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Abstract

Abstract