Frank Technow

3.4k citations

39 papers · 2.3k indexed · 1 hit paper · h-index 20

Genetics top 1%
- Genetic Mapping and Diversity in Plants and Animals 28
- Genetic and phenotypic traits in livestock 25
Plant Science top 1%
- Genetics and Plant Breeding 28
- Wheat and Barley Genetics and Pathology 2
- Agricultural pest management studies 1
Agronomy and Crop Science top 2%
- Crop Yield and Soil Fertility 4
Ecology top 10%
Ecology, Evolution, Behavior and Systematics top 10%
Biomedical Engineering
- Biodiesel Production and Applications 3
Soil Science
- Soil Management and Crop Yield 2

Co-authors: Albrecht E. Melchinger Christian Riedelsheimer Mark Cooper Carlos D. Messina Liviu R. Totir Tobias A. Schrag Carla Gho Wolfgang Schipprack
Cited by: Genetics Plant Science Agronomy and Crop Science
Journals: Theoretical and Applied Genetics (7 papers)G3 Genes Genomes Genetics (6 papers)Crop Science (3 papers)
Partner nations: Germany United States Australia

In The Last Decade

Frank Technow

38 papers receiving 2.2k citations

Hit Papers

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Peers

Countries citing papers authored by Frank Technow

Since Specialization

Citations

This map shows the geographic impact of Frank Technow's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Frank Technow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Technow more than expected).

Fields of papers citing papers by Frank Technow

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frank Technow. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Frank Technow. The network helps show where Frank Technow may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Frank Technow, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Frank Technow Line = papers co-authored together Frank Technow links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Back to the future 2: the implications of germplasm structure on the balance between short- and long-term genetic gain in a changing target population of environments G3 Genes Genomes Genetics ·Frank Technow,Dean Podlich,Zhen Sui	2026	0
2	Statistical sampling of missing environmental variables improves biophysical genomic prediction in wheat Theoretical and Applied Genetics ·Abdulqader Jighly,Thabo Thayalakumaran,Surya Kant,Joe Panozzo,Rajat Aggarwal,이광재,Kerrie Forrest,Frank Technow,Takako Umemoto,Michael E. Goddard,J.E. Pryce,Matthew Hayden,Jesse Munkvold,Garry J. O’Leary	2024	1
3	Crop Improvement for Circular Bioeconomy Systems Journal of the ASABE ·Carlos D. Messina,Fred van Eeuwijk,Tom Tang,Sandra K. Truong,Ryan F. McCormick,Frank Technow,Owen Powell,Rocío Moldes,Neal Gutterson,James W. Jones,Graeme Hammer,Mark Cooper	2022	23
4	Back to the future: implications of genetic complexity for the structure of hybrid breeding programs G3 Genes Genomes Genetics ·Frank Technow,Dean Podlich,Mark Cooper	2021	18
5	Modelling selection response in plant-breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions Mark Cooper,Owen Powell,Kai P. Voss‐Fels,Carlos D. Messina,Carla Gho,D. Podlich,Frank Technow,Scott Chapman,Christine A. Beveridge,Daniel Ortíz-Barrientos,Graeme Hammer	2020	37
6	Use of F2 Bulks in Training Sets for Genomic Prediction of Combining Ability and Hybrid Performance G3 Genes Genomes Genetics ·Frank Technow	2019	8
7	Leveraging biological insight and environmental variation to improve phenotypic prediction: Integrating crop growth models (CGM) with whole genome prediction (WGP) European Journal of Agronomy ·Carlos D. Messina,Frank Technow,Tom Tang,B Mccoy Anne,Carla Gho,Mark Cooper	2018	139
8	Parent-progeny imputation from pooled samples for cost-efficient genotyping in plant breeding PLoS ONE ·Frank Technow,Justin Gerke	2017	16
9	Accuracy of Genomic Prediction in Synthetic Populations Depending on the Number of Parents, Relatedness, and Ancestral Linkage Disequilibrium Genetics ·A.V. Medzigov,Dominik Müller,Frank Technow,Albrecht E. Melchinger	2016	50
10	Using Bayesian Multilevel Whole Genome Regression Models for Partial Pooling of Training Sets in Genomic Prediction G3 Genes Genomes Genetics ·Frank Technow,Liviu R. Totir	2015	13
11	Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation PLoS ONE ·Frank Technow,Carlos D. Messina,Liviu R. Totir,Mark Cooper	2015	166
12	Shrinkage estimation of the genomic relationship matrix can improve genomic estimated breeding values in the training set Theoretical and Applied Genetics ·Dominik Müller,Frank Technow,Albrecht E. Melchinger	2015	14
13	Optimizing Resource Allocation for Multistage Selection in Plant Breeding with R Package Selectiongain Crop Science ·Xuefei Mi,H. Friedrich Utz,Frank Technow,Albrecht E. Melchinger	2014	20
14	Genomic prediction of dichotomous traits with Bayesian logistic models Theoretical and Applied Genetics ·Frank Technow,Albrecht E. Melchinger	2013	13
15	QTL mapping of stalk bending strength in a recombinant inbred line maize population Theoretical and Applied Genetics ·Haixiao Hu,Wenxin Liu,H. Aounallah-Skhiri,出永原,Frank Technow,Hongwu Wang,Fatima-Zahra Atlane,Martha Elena Valverde,Albrecht E. Melchinger,Shaojiang Chen	2013	57
16	Seed quality diversity, trait associations and grouping of accessions in Jatropha curcas L. Industrial Crops and Products ·Juan M. Montes,Frank Technow,PU Zh,Karsten Becker	2013	13
17	Rapid and accurate identification of in vivo-induced haploid seeds based on oil content in maize Scientific Reports ·Albrecht E. Melchinger,Wolfgang Schipprack,Tobias Würschum,Shaojiang Chen,Frank Technow	2013	93
18	Comparison of whole-genome prediction models for traits with contrasting genetic architecture in a diversity panel of maize inbred lines BMC Genomics ·Christian Riedelsheimer,Frank Technow,Albrecht E. Melchinger	2012	74
19	Genomic prediction of hybrid performance in maize with models incorporating dominance and population specific marker effects Theoretical and Applied Genetics ·Frank Technow,Christian Riedelsheimer,Tobias A. Schrag,Albrecht E. Melchinger	2012	132
20	Efficient Computation of Ridge‐Regression Best Linear Unbiased Prediction in Genomic Selection in Plant Breeding Crop Science ·Hans‐Peter Piepho,Joseph O. Ogutu,Torben Schulz‐Streeck,Jens Hammer,Andrés Gordillo,Frank Technow	2012	43

About Frank Technow

Frank Technow is a scholar working on Genetics, Plant Science and Agronomy and Crop Science, having authored 39 papers that have together received 2.3k indexed citations. Recurring topics across this work include Genetics and Plant Breeding (28 papers), Genetic Mapping and Diversity in Plants and Animals (28 papers), Genetic and phenotypic traits in livestock (25 papers), Crop Yield and Soil Fertility (4 papers), Biodiesel Production and Applications (3 papers), Soil Management and Crop Yield (2 papers), Wheat and Barley Genetics and Pathology (2 papers) and Agricultural pest management studies (1 paper). The work is most often cited by research in Genetics (1.6k citations), Plant Science (2.0k citations) and Agronomy and Crop Science (310 citations). Frank Technow has collaborated with scholars based in Germany, United States and Australia. Frequent co-authors include Albrecht E. Melchinger, Christian Riedelsheimer, Mark Cooper, Carlos D. Messina, Liviu R. Totir, Tobias A. Schrag, Carla Gho, Wolfgang Schipprack, Ronan Sulpice and Thomas Altmann. Their work appears in journals such as Theoretical and Applied Genetics, G3 Genes Genomes Genetics, Crop Science, Journal of Experimental Botany and Industrial Crops and Products.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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