Roberto Fritsche Neto

Bio

He 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). Then, he was an Assistant Professor in Plant Breeding at the University of Viçosa and the University of Sao Paulo, Brazil. Then, worked as a Senior Scientist in quantitative Genetics and Biometrics at the International Rice Research Institute (IRRI), Philippines. From 2022 to 2025, he was an Assistant Professor of Quantitative Genetics / Prediction-based breeding at LSU AgCenter. Currently, he is an Assistant Professor of Vegetable Molecular Breeding at NC State. He was also a visiting scientist at the University of Minnesota, Cornell University, and Queensland University. His 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 vegetables germplasm with higher resilience.

Publications

Google Scholar: https://scholar.google.com/citations?hl=en&user=mQCVtV0AAAAJ

Top Five Publications

FRITSCHE-NETO, Roberto; ALI, JAUHAR; DE ASIS, ERIK JON; ALLAHGHOLIPOUR, MEHRZAD; LABROO, MARLEE ROSE. Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance. THEORETICAL AND APPLIED GENETICS. , v.137, p.3 – , 2024.

LADHA, J. K. ; RADANIELSON, A. M. ; RUTKOSKI, J. E. ; BURESH, R. J. ; DOBERMANN, A. ; ANGELES, O. ; PABUAYON, I. LORRAINE B. ; SANTOS-MEDELLÍN, C. ; FRITSCHE-NETO, R. ; CHIVENGE, P. ; KOHLI, A. . Steady agronomic and genetic interventions are essential for sustaining productivity in intensive rice cropping. PNAS, v. 118, p. e2110807118, 2021.

COSTA NETO, G. M. F.; CROSSA, JOSE; FRITSCHE-NETO, ROBERTO. Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials. HEREDITY. , v.353, p.1 – , 2020.

FRITSCHE-NETO, ROBERTO; AKDEMIR, DENIZ; JANNINK, JEAN-LUC. Accuracy of genomic selection to predict maize single-crosses obtained through different mating designs. THEORETICAL AND APPLIED GENETICS, v. 131, p. 1, 2018.

SOUZA, MASSAINE BANDEIRA; CUEVAS, JAIME; COUTO, EVELLYN GISELLY DE OLIVEIRA; PÉREZ-RODRÍGUEZ, PAULINO; JARQUÍN, DIEGO; FRITSCHE-NETO, ROBERTO; BURGUEÑO, JUAN; CROSSA, JOSE. Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction. G3-GENES GENOMES GENETICS, v. 7, p. g3.117.042341, 2017.