Author

Dean Podlich

Corteva (United States)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:simulation· 3 Research Focus:benchmarking· 2 Research Focus:software / tool· 2 Organism:plant (other)· 1 Approach:statistical model· 1

Frequent Co-Authors

Frank TechnowiD· 3 shared Mark CooperiD· 3 shared Carla GhoiD· 1 shared Carlos D. MessinaiD· 1 shared Christine Anne BeveridgeiD· 1 shared Daniel Ortíz-BarrientosiD· 1 shared Graeme HammeriD· 1 shared Kai P. Voss‐FelsiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersGenetics

Frank TechnowORCID

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3 papers

Recent·Most cited

Back to the future 2: the implications of germplasm structure on thebalance between short and long-term genetic gain in a changingtarget population of environments

Frank Technow, Dean Podlich, Mark Cooper

The paper investigates how environmental changes affect genetic gain in plant breeding by simulating germplasm structure and selection strategies.

G3 Genes Genomes Genetics · Feb 19, 2026Peer-reviewedGenetics

Back to the future: Implications of genetic complexity for hybrid breeding strategies

Frank Technow, Dean Podlich, Mark Cooper

This study uses simulations to show that constraining genetic space and reducing population size in hybrid breeding improves heritable gains, explaining the success of traditional breeding strategies.

G3 Genes Genomes Genetics · May 5, 2021Peer-reviewedGenetics

Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions

Mark Cooper, Owen M. Powell, Kai P. Voss‐Fels, Carlos D. Messina, Carla Gho, Dean Podlich, Frank Technow, Scott Cameron Chapman, Christine Anne Beveridge, Daniel Ortíz-Barrientos, Graeme Hammer

The paper explores using crop models as gene-to-phenotype link functions to optimize selection in plant breeding programs by integrating quantitative genetic theory and trait modeling.

in silico Plants · Dec 28, 2020Peer-reviewedGenetics