CV Lattes
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Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Faculdade de Ciências Agrárias e Veterinárias (FCAV) (Institutional affiliation from the last research proposal) Birthplace: Brazil
graduation at Zootecnia from Universidade Federal de Lavras (1998), master's at Zoothecny from Universidade Estadual Paulista Júlio de Mesquita Filho (2000), doctorate at Zoothecny from Universidade Estadual Paulista Júlio de Mesquita Filho (2004) and doctorate at Doutorado Sanduíche from University of Guelph (2003). Has experience in Zoothecny, focusing on Genetics and Improvement of Domestic Animals, acting on the following subjects: bovinos de corte, avaliação genética, critérios de seleção, beef cattle breeding and gwas. (Source: Lattes Curriculum)
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Genome-wide association (GWA) and functional analyses were conducted aiming to identify important genes and pathways associated with heifer rebreeding (HR) and with the number of calvings at 53 months of age (NC53) in Nellore cows. A total of 142,878 and 244,311 phenotypes for HR and NC53, respectively, and 2,925 animals genotyped with the Illumina Bovine HD panel (Illumina®, San Diego, C…
Stayability, which can be defined as the probability of a cow calving at a ( certain age when given the opportunity, is an important reproductive trait in beef ( cattle because it is directly related to herd profitability. The objective of this (study was to estimate genetic parameters and to identify possible genomic ( regions associated with the phenotypic expression of stayability in N…
Feet and leg conformation scores are important traits in beef cattle because they encompass a wide range of locomotion disorders that can lead to productive and reproductive losses. Thus, the study of feet and legs in beef cattle is essential for evaluating possible responses to selection focusing on minimizing economic losses caused by the occurrence of feet and leg problems. The aim of …
(Only some records are available in English at this moment)
Principal component analysis is a multivariate statistical technique that allows to evaluate the magnitude of variability and inter-relationships between traits of interest. The aim of this study was to evaluate genetic principal components of growth traits and visual score at weaning and yearling in Nelore cattle, in order to identify the inter-relationship between these traits and possi…
Objective is to develop a computer program for mate selection in aquaculture species. This program will be applied to real and simulated dataset using different scenarios of population structure and parameters to be optimized data that will be compared for rates of inbreeding and genetic gain. The real dataset will consist in information of 6,722 Nile tilapias, of which 522 animals make u…
Reproductive traits are closely associated with the success of the production system of cattle, because females that calve early have more chance to leave more offspring throughout its productive life than late females. The inclusion of genomic information by DNA markers can improve the accuracy of breeding values for reproductive traits. Furthermore, when distributed throughout the genom…
(Only some records are available in English at this moment)
The genotype environment interaction for beef cattle is routinely investigated by using the reaction norm models in order to predict the breeding values in the different environmental conditions, as well as to assess environmental sensitivity. The inclusion of molecular markers in the estimation of reaction norms allows the identification of candidate genes along the environmental gradien…
The main objective of this project is to unravel the genetic sensitivity of Nellore cattle to environmental variation. For this, phenotypic and genotypic data from Nellore cattle raised under diverse environmental conditions will be studied. Sensitivity to environmental variation will be assessed for several growth and reproduction traits. Data from commercial breeding programs will be us…
Principal component analysis (PCA) is used to extract important information from multivariate data which is expressed as a set of new variables called principal components (PCs). The PCs can show associations with a biological meaning among the traits, usually not observed in the original data. Genome-wide association studies (GWAS) can be used as an important tool to identify genomic reg…
(Only some records are available in English at this moment)