Nitrogen Fertilizer Recommendations for Corn Grown on Soils Amended with Oily Food Waste
Bibliographic record
Abstract
Soil and plant indices of soil fertility status have traditionally been developed using conventional soil and crop management practices. Data on managing N fertilizer for corn (Zea mays L.) produced on soils amended with C-rich organic materials, such as oily food waste (OFW) is scarce. Identification of a reliable method for making N fertilizer recommendations under these conditions is imperative. The objective of this research was to evaluate soil NO(3)-N (0- to 30-cm depth) at preplant and presidedress (PSNT) times of sampling for predicting N requirements for corn grown on fields receiving OFW. Experiments were conducted at two locations in Ontario, Canada over 3 yr (1995-1997) where OFW was applied at different rates (0, 10, and 20 Mg ha(-1)), times (fall and spring), and slope positions (upper, mid, and lower) within the same field. Presidedress soil NO(3)-N contents were higher compared with preplant time of sampling under all OFW management conditions. Corn grain yields were significantly affected by OFW management and N fertilizer application rates. Maximum economic rate of N application (MERN) varied depending on OFW management conditions. Presidedress soil NO(3)-N contents had a higher inverse relationship with MERN (r = -0.88) compared with soil NO(3)-N at preplant (r = -0.74) time of sampling. A linear regression model (Y = 180.1 - 8.22 NO(3)-N at PSNT) is proposed for making N fertilizer recommendations to corn grown on soils amended with OFW in this geographical region.
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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 | 0.000 | 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) | 0.000 | 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".