Evaluation of apple cultivars (Malus x domestica Borkh.) for resistance to apple blotch disease (Diplocarpon coronariae) and genomic analysis of the pathogen
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Apple blotch, caused by the fungus Diplocarpon coronariae (Ellis & Davis) Wöhner & Rossmann, is becoming an increasingly important disease in organic and extensive apple cultivation in Europe. The infection primarily affects the leaves, leading to chlorosis, necrosis, and, as it progresses, to premature leaf abscission before the end of the growing season. This can significantly reduce both yield and fruit quality. While fungicides are commonly used in commercial cultivation, a more sustainable approach is the cultivation of robust apple cultivars. This reduces the amount of fungicide needed, the extent of damage caused by infections, as well as slowing down the spread of the fungus. However, many cultivars grown in Germany are highly susceptible, and comprehensive studies on cultivar susceptibility are lacking. Therefore, the first part of this study evaluated 780 apple cultivars from the German Fruit Genebank (GFG) and the Julius Kühn Institute's cultivar collection. To assess the susceptibility to D. coronariae, inoculation trials were performed on detached leaves under controlled laboratory conditions. Symptoms were scored after 7, 9, and 13 days using a symptom progression score (SPS), and both the number of acervuli and the necrotic area were quantified. Selected cultivars were further tested in greenhouse trials to confirm results and evaluate the leaf abscission. No cultivar exhibited complete resistance, but eight cultivars were identified with significantly reduced symptom expression and delayed leaf abscission. These could be used in future breeding programs or planted as robust cultivars in low-input cultivation, such as in meadow orchards. The pictures of infected leaves were also used to develop a digital phenotyping approach using a pre-trained YOLOv5s model. Training the model using the images of disease symptoms resulted in a detection model with 95% accuracy, allowing an efficient and objective symptom assessment. Phenotypic data from the laboratory experiments was then used in a genome-wide association study (GWAS) to identify genetic markers associated with delayed symptoms. Significant marker-trait associations were identified on chromosome 12, as well as on chromosomes 3, 13, and 16. The high heritability of the observed traits, as well as the calculation of associations with several susceptibility traits, highlights the potential of marker-assisted selection in apple breeding. Finally, a European isolate of D. coronariae (DC1_JKI) was sequenced using short-read and long-read sequencing technologies. The genome was used to better understand the reproduction mechanism as sexual reproduction increases the evolutionary potential. However, to date, the sexual form has not been documented in Europe. The heterothallic D. coronariae requires two mating type idiomorphs (MAT1-1 and MAT1-2), but only MAT1-2 was identified in DC1_JKI and 48 additional European and Canadian samples. Conversely, both mating types are present in Asian samples. The absence of MAT1-1 in Europe provides a possible explanation for the lack of sexual reproduction and suggests a reduced potential to adapt to resistance in apples. Overall, this thesis provides important insights into resistance evaluation, digital phenotyping and genetic resistance regions in apple. This knowledge enables targeted cultivar recommendations for cultivation with reduced fungicide use and contribute to the development of sustainable breeding strategies for D. coronariae-resistant apple cultivars. In addition, insights into the biology of the fungus enable a risk assessment of the pathogen.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle