Selected Publications

  1. Bernardo, R. 2020. Reinventing quantitative genetics for plant breeding: something old, something new, something borrowed, something BLUE. Heredity 125: 375-385. [PDF]
  2. Brandariz, S.P., and R. Bernardo. 2019. Predicted genetic gains from targeted recombination in elite biparental maize populations. Plant Genome 12, doi: 10.3835/plantgenome2018.08.0062. [PDF]
  3. Bernardo, R. 2017. Prospective targeted recombination and genetics gains for quantitative traits in maize. Plant Genome doi: 10.3835/plantgenome2016.11.0118. [PDF]
  4. Bernardo, R. 2016. Bandwagons I, too, have known. Theor. Appl. Genet. 129: 2323-2332. [PDF]
  5. Lian, L., A. Jacobson, S. Zhong, and R. Bernardo. 2014. Genomewide prediction accuracy within 969 maize biparental populations. Crop Sci. 54: 1514–1522. [PDF]
  6. Jacobson, A., L. Lian, S. Zhong, and R. Bernardo. 2014. General combining ability model for genomewide selection in a biparental population. Crop Sci. 54: 895–905. [PDF]
  7. Bernardo, R. 2014. Genomewide selection when major genes are known. Crop Sci. 54: 68–75. [PDF]
  8. Bernardo, R. 2013. Genomewide markers for controlling background variation in association mapping. Plant Genome doi: 10.3835/plantgenome2012.11.0028. [PDF]
  9. Massman, J.M., H.-J.G. Jung, and R. Bernardo. 2013. Genomewide selection versus marker-assisted recurrent selection to improve grain yield and stover-quality traits for cellulosic ethanol in maize. Crop Sci. 53: 58-66. [PDF]
  10. Bernardo, R. 2008. Molecular markers and selection for complex traits: Learning from the last 20 years. Crop Sci. 48: 1649-1664. [PDF]
  11. Bernardo, R., and J. Yu. 2007. Prospects for genomewide selection for quantitative traits in maize. Crop Sci. 47:1082-1090. [PDF]
  12. Bernardo, R. 1994. Prediction of maize single-cross performance using RFLPs and information from related hybrids. Crop Sci. 34: 20-25. [PDF] (The GBLUP procedure, and therefore genomewide selection as a whole, was invented in this paper.)