Evaluation of apple cultivars (Malus x domestica Borkh.) for resistance to apple blotch disease (Diplocarpon coronariae) and genomic analysis of the pathogen
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".