The influence of nitrogen and calcium fertilizers on septoria late blight and yield of celery
Bibliographic record
Abstract
Tesfaendrias, M. T., Trueman, C. L., Gossen, B. D., McKeown, A. W. and McDonald, M. R. 2014. The influence of nitrogen and calcium fertilizers on septoria late blight and yield of celery. Can. J. Plant Sci. 94: 1391–1399. Late blight (Septoria apiicola) reduces both yield and quality of fresh market and processing celery. Field trials were conducted over 4 site-years to evaluate the effect of nitrogen (N) rate and foliar calcium (Ca) fertilization on the development of late blight and yield on celery grown on muck soils, which have a high organic matter (OM) content. A treatment with the protectant fungicide chlorothalonil was included to determine if fertilizer could replace fungicide application in celery production. There was a cultivar×site-year interaction for each of the disease and yield variables. Repeated application of chlorothalonil fungicide reduced late blight and generally increased plant height, weight and marketable yield. The rate of N applied had a small effect on late blight, which varied among site-years. Area under the disease progress curve decreased with increasing rate of N at both sites in 2008. Similarly, an increasing rate of N resulted in an increase in yield in one of four site-years. Application of Ca did not affect late blight severity and increased yield in only 1 site-year. There was a negative correlation between late blight severity and yield. Tissue N concentrations varied among the treatments at sites with a relatively low OM content, but not at the high OM sites. The treatments had no effect on Ca tissue concentrations. Application of N and Ca alone did not adequately control late blight, but there was a slight reduction in late blight severity with increasing rates of N. Application of both N and Ca can improve yield and also contribute indirectly to improved late blight management in combination with fungicides and other integrated crop management practices.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".