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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). | 160,130876285469 | 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). | 153,68092589386 | 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). | 103,76264173559 | 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). | 4,88894022885443 | 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). | 48,157695136512 | 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). | 48,3395413058899 | 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). | 5,78277042567846 | 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). | 80,2980128818806 | 20220328 |