Response of the Illinois Soil Nitrogen Test to liquid and composted dairy manure applications in a corn agroecosystem
Bibliographic record
Abstract
Dairy manure is important for corn (Zea mays L.) production in New York. Optimizing corn yield while minimizing environmental loss with manure nutrients is often a challenge. A potential tool for improving N management is the Illinois Soil Nitrogen Test (ISNT), which estimates amino sugar N, a pool of potentially mineralizable N for corn uptake. The objectives of this study were to determine (1) the short-term effects of manure applications on ISNT-N, and (2) the longer-term impacts of annual additions of composted and liquid dairy manure on ISNT-N. A 6-wk incubation study showed that NH 4 -N from manure temporarily (< 2 wk) increased ISNT results. A 4-yr field study was conducted with annual spring applications of two rates of composted dairy manure (45 and 77 Mg ha -1 ) and two liquid dairy manure rates (63.5 and 180 kL ha -1 ). Results showed that ISNT-N slightly decreased over time in check plots (no manure or fertilizer additions) and that increases in ISNT-N over time in compost and liquid manure amended plots were consistent with changes in N credits currently given to manures in New York. Our results suggest that the ISNT accounts for N in previously applied compost and manure amendments, but that samples should not be taken within 2-wk following manure addition. Key words: Amino sugar, compost, Illinois Soil Nitrogen Test, nitrogen, manure, nutrient management
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".