(219) Nitrogen Relationships to Yield and Quality of Carrots Grown on Mineral and Organic Soil in Ontario
Bibliographic record
Abstract
In previous work with carrots ( Daucus carota L.), little effect of nitrogen could be found on yield, but low nitrogen increased foliar disease. To determine if residual soil nitrate supplies sufficient nitrogen for carrots, plots were located on the same site for 3 years. Two sites were selected, one sand (pH 8.1, 2.6% OM), one organic (pH 6.0, 75% OM). Treatments consisted of 0%, 50%, 100%, 150%, and 200% of recommended levels (kg·ha -1 ) for organic (60) and mineral soils (110), plots were spilt in half with one fertilized every year, one in 2002 and were arranged in a split plot design with four replications. Foliar and soil samples were taken for nitrate analysis plus levels of Alternariadauci and Cercospora carotae foliar blight were recorded each year. Applied nitrogen had no effect on yield on muck soils. Over 3 years on mineral soils, total yield ranged from 36 to 48 t·ha -1 with no applied N. On mineral soils, yield was maximized at (kg·ha -1 ) 110, over 165, and 55-165 in 2002, 2003, and 2004, respectively. Stands on mineral soils were reduced at or above recommended rates in 2004. It is possible that carrots obtained considerable nitrogen perhaps deep in the soil profile. As in previous studies, applied nitrogen reduced foliar blights. Thus, nitrogen application is required for pest management purposes even if there is almost sufficient residual nitrogen for yield.
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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 | 0.000 |
| 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 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".