Nitrogen Assimilation Ability of Three Cauliflower Cultivars in Relation to Reduced Post-Transplanting Nitrogen Supply
Bibliographic record
Abstract
It is not known how cauliflower (Brassica oleracea var. botrytis), a cool-weather, high nutritional-value vegetable, achieves its high nutritional levels, the hearty structure and fresh appearance. A study of cauliflower plant and nitrogen nutrition relations was conducted in a commercial production field in Annapolis Valley, Nova Scotia. The objectives were to determine the effects of nitrogen nutrition on cauliflower plant development and to quantify cauliflower plant N uptake ability among different varieties. The treatments consisted of three cauliflower varieties (‘Minuteman’, ‘Sevilla’ and ‘Whistler’) and three post-transplanting rates of N (0, 45 and 90 kg ha-1), arranged in a split-block design in the field. Results showed that the N uptake ability of cauliflower plants varied between 6.2 and 9.0 g plant-1, depending on varieties. The cauliflower varieties ‘Sevilla’ and ‘Minuteman’ had a significantly higher ability of N uptake than the cultivar ‘Whistler’ (P < 0.05). All three varieties responded significantly to the reduced post-transplanting input (45 kg N ha-1). There was a significant correlation between cauliflower head yield and whole plant N uptake (R2 = 0.64, P < 0.05). It was suggested that increasing N assimilation in whole plant could stimulate cauliflower head development, which could also lead to a reduction of 50% post-transplanting inputs. Future studies will be focused on quantification and regulation of N temporal reserves in leaves that could enhance N transfer to sinks (heads) and that could promote cauliflower plant head development.
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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 | 0.000 |
| 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 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".