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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). | 163,246132105318 | 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). | 164,902519523028 | 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). | 123,099670319202 | 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). | 3,87249760689538 | 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). | 47,8314101556943 | 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). | 45,3508450203295 | 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). | 3,77592925775057 | 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). | 105,844393341682 | 20220328 |