The response of late storage cabbage and broccoli to applications of sulphur and calcium
Bibliographic record
Abstract
Sulphur may become deficient in intensive vegetable production systems that rely on chemical fertilizers. Yield of cole crops in response to sulphur fertilization has not been evaluated under Ontario conditions. Since calcium is linked to clubroot disease and tipburn, the sulphur fertilizer source is an important consideration. Rates of sulphur and calcium were compared for effects on yield using Novacal (a prilled calcium sulphate product), calcium nitrate and potassium sulphate for 3 yr for cabbage and 2 yr for broccoli on both sand and loam soils. There appeared to be no difference in yield from fertilizer source of sulphur or calcium. Applications of sulphur increased yield of Huron late storage cabbage averaged over years and soil with a mathematical maximum occurring at 55 kg S ha-1. Soil tests indicated levels of approximately 13–19 µg g-1 for sulphur prior to treatment. Yield of cabbage increased proportionately to calcium application averaged over 3 yr. No effect of treatment was observed on broccoli. Thus, soil levels of sulphur were probably limiting for late cabbage but not for broccoli. Sulphur shortage or deficiency appears to exist for late storage cabbage grown in Ontario. Lack of response of broccoli and no calibrated soil test for either element suggest that crops have to be evaluated individually under field conditions for sulphur fertilizer requirements. Key words: Cabbage, broccoli, calcium, sulphur, nutrition, yield
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 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) | 0.002 | 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".