| human | Q5 |
| P6178 | Dimensions author ID | 011250155441.92 |
| P227 | GND ID | 1030375615 |
| P269 | IdRef ID | 180056204 |
| P244 | Library of Congress authority ID | no2012036982 |
| P8189 | National Library of Israel J9U ID | 987007335872705171 |
| P691 | NL CR AUT ID | xx0220654 |
| P1207 | NUKAT ID | n2013062817 |
| P496 | ORCID iD | 0000-0003-4310-0047 |
| P1153 | Scopus author ID | 25924253600 |
| P214 | VIAF ID | 233453092 |
| P10832 | WorldCat Entities ID | E39PBJwhyVdtKq9fBbHvQDVwG3 |
| P69 | educated at | Federal University of Pelotas | Q7894376 |
| Luiz de Queiroz College of Agriculture | Q5397345 | ||
| Federal University of Viçosa | Q5814528 | ||
| P108 | employer | University of Minnesota | Q238101 |
| Cornell University | Q49115 | ||
| International Rice Research Institute | Q1204921 | ||
| Luiz de Queiroz College of Agriculture | Q5397345 | ||
| Federal University of Viçosa | Q5814528 | ||
| P734 | family name | Fritsche | Q21494138 |
| Fritsche | Q21494138 | ||
| Fritsche | Q21494138 | ||
| Neto | Q36915388 | ||
| Neto | Q36915388 | ||
| Neto | Q36915388 | ||
| P101 | field of work | molecular genetics | Q210506 |
| abiotic component | Q461335 | ||
| cultivation | Q488798 | ||
| P735 | given name | Roberto | Q15905580 |
| Roberto | Q15905580 | ||
| P1412 | languages spoken, written or signed | English | Q1860 |
| P106 | occupation | university teacher | Q1622272 |
| agronomist | Q1781198 | ||
| botanist | Q2374149 | ||
| P21 | sex or gender | male | Q6581097 |
| Q49994134 | Accuracy of genomic selection to predict maize single-crosses obtained through different mating designs. |
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| Q90519718 | BGGE: A New Package for Genomic-Enabled Prediction Incorporating Genotype × Environment Interaction Models |
| Q59473312 | Correction to: Accuracy of genomic selection to predict maize single-crosses obtained through different mating designs |
| Q125475951 | Deep purple - an open-pollinated variety to induce haploids in tropical maize |
| Q39031101 | Effects of using phenotypic means and genotypic values in GGE biplot analyses on genotype by environment studies on tropical maize (Zea mays). |
| Q125466232 | Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize |
| Q36174137 | Genetic Vulnerability and the Relationship of Commercial Germplasms of Maize in Brazil with the Nested Association Mapping Parents |
| Q52373698 | Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials. |
| Q38813502 | Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction. |
| Q91826564 | Multi-objective optimized genomic breeding strategies for sustainable food improvement |
| Q98778679 | Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials |
| Q123116888 | On the accuracy of threshold genomic prediction models for leaf miner and leaf rust resistance in arabica coffee |
| Q125455827 | Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations |
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