Performance of 'Montmorency' Sour Cherry (Prunus CerasusL.) on Size-Controlling Rootstocksat Six NC-140 Trial Locations in North America
Bibliographic record
Abstract
‘Montmorency’ sour (aka tart) cherry ( Prunus cerasusL.) was budded to 11 potentially size-controlling clonal rootstocks plus the standard Mahaleb seedling rootstock at a commercial nursery, grown for one year, then planted in 1998 at six locations in North America under the auspices of the NC-140 Regional Research project. Eight replicate trees on each rootstock were planted at each site (Michigan, New York, Ontario, Pennsylvania, Utah, and Wisconsin). The planting in Pennsylvania was terminated in 2002. The remaining sites continued to collect data through 2007. Significant differences between rootstocks were found for their effects on tree mortality, tree size, root suckering, cumulative yield, cumulative yield efficiency and fruit size within and among the various trial sites. Trees on P. cerasus rootstock genotypes varied in scion vigor, ranging from some of the smallest (Edabriz, W.53) to some of the largest (W.10, W.13). Trees on interspecific hybrid rootstocks ranged from dwarfing (Gi.3) to semi-vigorous (Gi.195/20, Gi.6). No rootstock genotype conferred the best performance across all measured characteristics and all locations. Overall, the highest cumulative yields were on Mahaleb, W.10 and Gi.6. The highest mortality was on W.53, followed by Gi.195/20 and G.7, all of which have been found to be sensitive to pollen-borne viruses such as Prune Dwarf and Prunus Necrotic Ringspot. This high mortality should eliminate further commercial consideration of these rootstocks. Extensive root suckering was noted with W.13, W.10 and G.7 at several sites, suggesting that their potential for commercial production should be considered carefully in those sites, especially if mechanized harvest will be with newer over-the-row equipment rather than traditional trunk-shaking machinery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".