Direct-Seeded Broccoli Responses to Reduced Nitrogen Application at Shoot-Tip Straightened Stage
Bibliographic record
Abstract
Broccoli (Brassica oleracea var. italica) is an important high-nutritional-value vegetable yet broccoli plant and nitrogen nutrition relations are not well understood. We conducted a study of broccoli plant response to nitrogen nutrient treatments in a commercial production field in Nova Scotia. The objectives were to quantify the effects of nitrogen nutrition on direct-seeded broccoli development and plant nitrogen uptake in different soils. The nitrogen treatments consisted of the rates of 0, 25, 50, 75 and 100 kg ha-1, arranged with four replicates in a split-block design with soil type as the main plot. The two soil types were the well-drained Kentville (Kt) loam and the imperfectly-drained Woodville (Wd) loam. The N treatments were applied to the 60-day cultivar âEverestâ at shoot-tip straightened stage. Results showed that the direct-seeded broccoli N uptake ability was significantly higher (6.2 g plant-1) in the Wd soil, where the soil was near neural (pH 6.2) and contained more water (12% soil water content, SWC), compared to the Kt soil where the soil was acidic (pH 5.2) and drier (8% SWC). Broccoli plants responded significantly up to the lower N rate (50 kg ha-1) in the Wd soil but to the higher rate (75 kg ha-1) in the Kt soil. There was a significant correlation between head yield and leaf-stem N reserves (R2 = 0.56, P < 0.01). It was suggested that increasing N uptake could stimulate broccoli heading. Soil pH (6.2) and SWC (12%) conditions could promote broccoli plant N assimilation. Further quantification of regulating N temporal reserves in leaves and stems could enhance N transfer to sinks (heads), which would be the mechanism of promoting broccoli plant floret development.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".