Assessing soil nitrogen availability in contrasting cropping systems at the end of transition to organic production
Bibliographic record
Abstract
Liu, K., Hammermeister, A. M., Warman, P. R., Drury, C. F. and Martin, R. C. 2011. Assessing soil nitrogen availability in contrasting cropping systems at the end of transition to organic production. Can. J. Soil Sci. 91: 493–501. Quantifying soil nitrogen (N) availability at the end of a transition period for converting conventional fields to organic fields could enhance N management during the subsequent organic crop production phase. Soil total N (Ntot), KCl extractable N (KCl N) and potentially mineralizable N (No) were determined at the end of a 3-yr transition period. A complementary greenhouse ryegrass N bioassay was conducted using soils collected from the treated field plots. The field experiment consisted of six cropping systems comprising two N inputs (legume-based vs. manure-based) and three forage cropping treatments (0, 1 or 2 yr of forage in 4-yr rotations). The N input treatments consisted of alfalfa meal in the legume-based cropping system (LBCS) and composted beef manure in the manure-based cropping system (MBCS). Orthogonal contrasts suggested no differences in Ntot or KCl N either between LBCS and MBCS or between no-forage and forage cropping systems. However, in the greenhouse study, high cumulative N inputs in the MBCS resulted in significantly higher ryegrass N uptake and potentially mineralizable soil N than in the LBCS. Ryegrass N uptake ranged from 101 to 139 kg ha−1, which should be an adequate N supply for the succeeding potato crop. In the greenhouse, a ryegrass N bioassay effectively identified the differences in soil N availability. Ryegrass N uptake was linearly related to cumulative soil amendment N inputs but had no apparent relationship with N o. A systems approach provided a good assessment of N availability at the end of the transition period to organic production.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 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".