[HTML][HTML] Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.)

HJ Auinger, M Schönleben, C Lehermeier… - Theoretical and applied …, 2016 - Springer
Key message Genomic prediction accuracy can be significantly increased by model
calibration across multiple breeding cycles as long as selection cycles are connected by …

[PDF][PDF] Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.)

HJ Auinger, M Schönleben, C Lehermeier, M Schmidt… - 2016 - cyberleninka.org
Model training across multiple breeding cycles significantly improves genomic prediction
accuracy in rye (Secale cereale L.) Page 1 1 3 Theor Appl Genet DOI 10.1007/s00122-016-2756-5 …

Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.)

HJ Auinger, M Schönleben, C Lehermeier… - Theoretical and Applied …, 2016 - infona.pl
Key message Genomic prediction accuracy can be significantly increased by model
calibration across multiple breeding cycles as long as selection cycles are connected by …

[PDF][PDF] Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.)

HJ Auinger, M Schönleben… - Theoretical and …, 2016 - mediatum.ub.tum.de
Model training across multiple breeding cycles significantly improves genomic prediction
accuracy in rye (Secale cereale L.) Page 1 1 3 Theor Appl Genet (2016) 129:2043–2053 DOI …

Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.)

H Auinger, M Schönleben… - Theoretical and …, 2016 - search.proquest.com
In hybrid rye breeding, application of genome-based prediction is expected to increase
selection gain because of long selection cycles in population improvement and …

Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

HJ Auinger, M Schönleben… - … & Applied Genetics, 2016 - search.ebscohost.com
Key message: Genomic prediction accuracy can be significantly increased by model
calibration across multiple breeding cycles as long as selection cycles are connected by …

Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

HJ Auinger, M Schönleben, C Lehermeier, M Schmidt… - 2016 - cabidigitallibrary.org
In hybrid rye breeding, application of genome-based prediction is expected to increase
selection gain because of long selection cycles in population improvement and …

[HTML][HTML] Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.)

HJ Auinger, M Schönleben, C Lehermeier… - TAG. Theoretical and …, 2016 - ncbi.nlm.nih.gov
In hybrid rye breeding, application of genome-based prediction is expected to increase
selection gain because of long selection cycles in population improvement and …

Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.)

HJ Auinger, M Schönleben… - TAG. Theoretical …, 2016 - pubmed.ncbi.nlm.nih.gov
Genomic prediction accuracy can be significantly increased by model calibration across
multiple breeding cycles as long as selection cycles are connected by common ancestors. In …

[引用][C] Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.)

HJ Auinger, M Schönleben, C Lehermeier, M Schmidt… - 2016