Assessment of a Nitrate Meter for Nitrogen Tests in Mineral and Organic Soils
Bibliographic record
Abstract
Nutrient management legislation in Ontario, Canada, has prompted an evaluation of alternative nitrogen (N) management techniques. Rapid, accurate methods of assessing soil nitrogen are required to assist in N management. A portable nitrate (NO3 − meter (Cardy) was evaluated for use in testing soil N for vegetable crops grown on organic and mineral soils. Cabbage, carrots, and onions were grown on both soils in Ontario, Canada, in 2000 and 2001. Nitrogen was applied at five rates to cabbage and carrots, and three rates to onions ranging from 0 to 200% of current provincial recommended N rates. At three growth stages throughout the growing season, soil samples were collected and subdivided. One subsample was used for Cardy meter analysis, and the other for laboratory analysis of NO3-N. Cardy NO3-N readings overestimated laboratory results in most instances on mineral soil, but consistently underestimated laboratory results on organic soil. A conversion factor would be required for both soil types, and 10 or more samples should be analyzed from a particular field to reduce variability. Soil NO3-N readings were variable among years and crops. Compared with laboratory analysis, Cardy soil test results are available in a fraction of the time required for laboratory results and are less expensive when analyzing over 100 samples. Yield was assessed at harvest. Yields were generally unaffected by N rate, except in cabbage in 2000, suggesting that adequate N was present in most treatments. The Cardy meter is effective in determining N sufficiency or deficiency in the field. The Cardy NO3 − meter has potential as a field soil N test to supplement a nutrient management system for vegetable crops as long as region-specific recommendations are established.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".