I graduated in Agronomy from the Federal University of Pelotas (Brazil) Master's in Genetics and Plant Breeding from the University of Sao Paulo (USP) and a Ph.D. in Genetics and Breeding from the Federal University of Viçosa (UFV). Also, I was a visiting scientist at the University of Minnesota, Cornell University, and Queensland University. For nine years, I?ve been an Assistant Professor of Plant Breeding at UFV and USP/ESALQ. From January 2021 to July 2022, I worked as a Senior Scientist Quantitative Genetics and Biometrics at the International Rice Research Institute (IRRI), Philippines. Currently, I am an Assistant Professor of Quantitative Genetics / Prediction-based breeding at LSU AgCenter. My work strives i) to make the current generation of breeders able to implement key tools (such as molecular markers, omics, imagery, and weather data) and modern statistical genetic approaches in the development of new products, ii) to develop new breeding schemes and statistical genetic models via stochastic simulations and empirical data, iii) understand the genetics and develop crop germplasm with higher resilience. (Source: Lattes Curriculum)
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Genomic prediction (GS) studies using diversity panels are essential to identify genetic variations associated with traits of interest in maize. Unfortunately, most of these studies have been conducted on temperate germplasm and on a global germplasm collection in which tropical genotypes are under-represented. Nonetheless, a continuous effort has been directed to improving the accuracy o…
To meet the global demand for food a significant portion of maize crops will occur in environmental conditions that restrict the full development of culture. In Brazil, this is already happening on a large scale, where which much of our crop production migrated to the season called "safrinha" and for areas of the Cerrado. In these areas it is common the low availability of nutrients in th…
Phenotyping can be performed at different phenological crop stages, which allows the understanding of the relationships between yield and physiological traits, as well as their dynamics throughout the growth and development process. However, the traditional evaluation is a labor-intensive, poorly automated, highly sensitive to environmental features, and, in some cases, subjective. On the…
One of the assumptions of diallel analysis is to assume parents as unrelated, which in practice does not occur and can lead to biased results. In addition, another critical factor in a hybrid breeding program is the genomic prediction being performed based on the same allelic substitution effects for two complementary heterotic groups. This may lead to a convergent selection of parents an…
Due to high demand of nitrogen for maize crop, plant breeding projects with the aid of modern technologies, such as genome wide selection (GWS), aiming to obtain cultivars more efficient in nitrogen use, are fundamental for sustainable agriculture in Brazil. Thus, the aim of this work is to evaluate the accuracy and predictive ability of non-additive models of GWS for nitrogen use efficie…
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One of the assumptions of diallel analysis is to accept parents as unrelated, what in practice does not occur and can lead to biased results. Moreover, a critical factor in a hybrid breeding program is the genomic prediction being performed based on the same allelic substitution effects for two complementary heterotic groups. It may lead to a convergent selection of parents and, consequen…
The greatest difficulty in maize breeding is to generate and evaluate all possible hybrid combinations (complete diallel). To reduce this difficulty, several genetic mating designs have been proposed, such as the partial diallel, circulant diallel, and testcross. These designs can cause wide differences in the estimates of variance components and of the value of the best parents, mainly d…
Genomic selection (GS) is a method to predict the genetic value of selection candidates based on the genomic estimated breeding value (GEBV) predicted from high-density markers positioned throughout the genome. The accuracy of prediction of hybrid performance by GS has been examined in maize. However, there are many challenges in GS to increase the accuracy of the estimation of GEBV. For …
| 3 / 2 | Completed research grants |
| 4 / 4 | Completed scholarships in Brazil |
| 3 / 3 | Completed scholarships abroad |
| 10 / 9 | All research grants and scholarships |
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