Evaluation of growth, yield, and fruit size of chokecherry, pincherry, highbush cranberry, and black currant cultivars in Saskatchewan
Bibliographic record
Abstract
The objective of this study was to quantitatively characterize the growth, yield and fruit size of cultivars of chokecherry (Prunus virginiana L.), pincherry (Prunus pensylvanica L.f.), highbush cranberry (Viburnum trilobum Marsh.), and black currant (Ribes nigrum L.). Cultivars were evaluated in replicated trials at two sites (Saskatoon and Outlook) in Saskatchewan over 2–5 yr. Espenant, Garrington, Lee Red, and Boughen Yellow were among the highest yielding of the chokecherry cultivars (mean yield = 7.2 kg plant-1 at Saskatoon); of these, Lee Red had the largest fruit. The pincherry cultivar Lee #4 (mean yield = 3.1 kg plant-1) yielded at least twice as much as Mary Liss or Jumping Pound. Highbush cranberry cultivars Alaska, Espenant, Garry Pink, Manitou, and Wentworth averaged yields of 2.0 kg plant-1 at Saskatoon. Of these, Manitou had the largest fruit. Two black currant trials were established; the cultivars included in the second trial were not available at the time of establishment of the first trial. Black currant yields ranged from 0.2 kg plant-1 for Willoughby to 1.0 kg plant-1 for Consort in the first trial, and from 0.2 kg plant-1 for the selection 4-24-29 to 2.0 kg plant-1 for McGinnis Black in the second trial. Black currant cultivars with the largest fruit size included Wellington, Topsy, and three numbered selections from the University of Saskatchewan (mean = 225 fruit/cup) in the first trial, and Ben Sarek, McGinnis Black, and Ben Alder (mean = 156 fruit/cup) in the second trial. Data from the current study provide a basis on which to evaluate the performance of currently available cultivars, and any new cultivars or future selections that may be developed. Key words: Prunus virginiana, Prunus pensylvanica, Viburnum trilobum, Ribes nigrum, fruit size, shoot growth, cultivar evaluation
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".