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| Vorhergesagte Blütezeit (genomische Vorhersage) | Predicted flowering time given in days after January 1st. The genomic prediciton was performed with a GSA-RRBLUP model involvig admixture as described in Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model (Berkner et al., DOI:10.1007/s00122-022-04227-4). | 157,481660167551 | 20220328 |
| Vorhergesagte Blütezeit (genomische Vorhersage) | Predicted flowering time given in days after January 1st. The genomic prediciton was performed with a GSA-RRBLUP model involvig admixture as described in Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model (Berkner et al., DOI:10.1007/s00122-022-04227-4). | 157,459171624428 | 20220328 |
| Vorhergesagte Pflanzenhöhe (genomische Vorhersage) | Predicted plant height given given in cm. The genomic predicition was performed with an EG-BLUP model as described in Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model (Berkner et al., DOI:10.1007/s00122-022-04227-4). | 119,495325324247 | 20220328 |
| Vorhergesagte Gelbrostresistenz (genomische Vorhersage) | Predicted yellow rust resistance given as a score ranging from 1 to 9. The genomic predicition was performed with an EG-BLUP model as described in Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model (Berkner et al., DOI:10.1007/s00122-022-04227-4). | 6,57063678341539 | 20220328 |
| Vorhergesagtes Tausendkorngewicht (genomische Vorhersage) | Predicted thousand grain weight given in g. The genomic predicition was performed with an EG-BLUP model as described in Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model (Berkner et al., DOI:10.1007/s00122-022-04227-4). | 43,8487591308391 | 20220328 |
| Vorhergesagtes Tausendkorngewicht (genomische Vorhersage) | Predicted thousand grain weight given in g. The genomic predicition was performed with an EG-BLUP model as described in Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model (Berkner et al., DOI:10.1007/s00122-022-04227-4). | 45,820406659441 | 20220328 |
| Vorhergesagte Gelbrostresistenz (genomische Vorhersage) | Predicted yellow rust resistance given as a score ranging from 1 to 9. The genomic predicition was performed with an EG-BLUP model as described in Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model (Berkner et al., DOI:10.1007/s00122-022-04227-4). | 6,59094532340881 | 20220328 |
| Vorhergesagte Pflanzenhöhe (genomische Vorhersage) | Predicted plant height given given in cm. The genomic predicition was performed with an EG-BLUP model as described in Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model (Berkner et al., DOI:10.1007/s00122-022-04227-4). | 118,052569910536 | 20220328 |