Interspecific hybridization – an important source for sweet and sour cherry breeding
Bibliographic record
Abstract
The limited of genetic diversity in cherry cultivars has reduced the adaptability to changing growing and climatic conditions of these species. Interspecific hybridizations have been used in many fruit breeding programs to increase the genetic diversity and to introduce new traits in fruit crops. In sour cherry, Prunus cerasus, the first interspecific crosses with P. maackii and P. fruticosa were released by I. V. Michurin in Russia and L. Kerr in Canada in the first half of the 20th century to increase the winter hardness of sour cherries. Various interspecific crosses and backcrosses have been carried out in the cherry breeding program at Dresden-Pillnitz during the last 20 years. In sweet cherry, P. avium, crosses with P. canescens, P. armeniaca, and P. tomentosa have been made, and in sour cherry with P. maackii, P. padus, P. serotina, and P. spinosa. The objectives of this breeding program are obtain of genotypes with new fruit and tree characteristics and with a higher level of resistance to biotic and abiotic stresses. The diploid Prunus species P. canescens, the tetraploid species P. maackii, and P. serotina are promising resistance donors for cherry breeding. For F1 progenies from crosses between sweet cherry and apricot showed a high tolerance of flowers to spring frost was observed and they had interesting fruit characteristics such as size, firmness and shelf-life in the first growing years. The material will be characterized in further studies. Interesting genotypes will be used for breeding process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".