Cold Acclimation Attributes of Two Asparagus Cultivars with Varying Patterns of Fern Senescence
Bibliographic record
Abstract
Adequate winterhardiness is crucial for yield stability of asparagus ( Asparagus officinalis ) cultivars in southern Ontario, Canada, and could be influenced by pattern of the fall fern senescence. Fern of cultivar Guelph Millennium (GM) turns yellow or senesces by mid-October, before that of cultivar Jersey Giant (JG), which often remains green until a killing frost. Early fern senescence could be a signal for cold acclimation competency and consequently winterhardiness, explaining the superior stand longevity and yield observed for GM compared with JG. A field experiment was conducted from mid-August to November to measure physiological parameters related to cold acclimation in fern, rhizome, and storage roots. During fall, fern chlorophyll concentration, rhizome nitrogen concentration, percent water of the crown, and storage root LT 50 (temperature at which 50% cell death occurs) decreased. Cultivars did not differ for storage root percent water; however, values were smaller (greater dehydration) for GM than JG in the rhizome. At the end of the sampling period, GM had higher and lower concentrations of rhizome low-molecular-weight, non-structural carbohydrates and sucrose, respectively, than JG, which could support a hypothesis of greater winterhardiness in GM. Storage root LT 50 values of –19 °C and the lack of cultivar differences for this trait, in conjunction with differences between GM and JG for rhizome traits thought to be important for freezing tolerance, suggest characteristics of the rhizome in conjunction with timing of fern senescence may be important in cold acclimation of asparagus.
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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 | 0.001 | 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 | 0.001 |
| 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".