Review: Improving nitrogen use efficiency of potted chrysanthemum: Strategies and benefits
Bibliographic record
Abstract
MacDonald, W. N., Blom, T. J., Tsujita, M. J. and Shelp, B. J. 2013. Review: Improving nitrogen use efficiency of potted chrysanthemum: Strategies and benefits. Can. J. Plant Sci. 93: 1009–1016. Floricultural greenhouse operations can pose significant environmental risk due to the leaching and runoff of nutrients such as [Formula: see text]. To face this challenge, Ontario growers have adopted recirculating systems, such as the subirrigated “ebb and flow” system, on benches, troughs and concrete floors. Chrysanthemum (Chrysanthemum morifolium Ramat.) is the most commonly grown floricultural greenhouse crop species in the world and the potted type is well adapted to subirrigation. Reduction of N fertilization towards the end of the crop cycle is generally recommended to improve the shelf life of cut and potted plants, but it is uncertain how this practice influences the N status of the plant and the electrical conductivity of the growing medium. In this review, we discuss N use efficiency and strategies for managing the [Formula: see text] status of plants, and then propose that this knowledge can help to improve the N use efficiency of potted chrysanthemum grown with subirrigation under greenhouse conditions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".