Broccoli growth in response to increasing rates of pre-plant nitrogen. I. Yield and quality
Bibliographic record
Abstract
Nitrogen management is critical to the production of broccoli (Brassica oleracea L. italica Plenck). Field trials were conducted in 2001 and 2002 to determine the rate of pre-plant nitrogen required to optimize broccoli yield and quality. Seven rates of nitrogen (0, 50, 100, 150, 200, 300, 400 kg N ha -1 ) as ammonium nitrate were broadcast and incorporated before transplanting two broccoli cultivars, Captain and Decathlon. Maturity of the heads was delayed by 5 d at 0 kg N ha -1 compared with the other rates of applied N. Marketable yield was maximized at 243 to 272 kg N ha -1 for yield expressed in t ha -1 and 171 to 187 kg N ha -1 for yield expressed as cases ha -1 . Averaged over cultivar and year the most economical rate of nitrogen (MERN) ranged from 298 to 309 kg ha -1 , 50 kg higher than estimates for the maximum marketable yield derived from quadratic plateau models. The incidence of misshapen heads decreased and floret color improved as nitrogen rate increased, but hollow stem and head rot also increased with high rates of nitrogen. Floret NO 3 - -N concentration increased and vitamin C concentration decreased at high nitrogen rates. Applying the rates of nitrogen required to maximize yield may have negative economic and environmental consequences. However, restricting nitrogen also jeopardizes both yield and quality. Hence, the optimum amount of pre-plant nitrogen to apply to broccoli that balances yield, quality, economics and environmental concerns remains a complex issue. Key words: Brassica oleracea L. italica Plenck, color, postharvest, nutrition, hollow stem, vitamin C
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".