Field‐Scale Application of Oily Food Waste and Nitrogen Fertilizer Requirements of Corn at Different Landscape Positions
Bibliographic record
Abstract
Oily food waste (FOG; fat + oil + greases) containing high concentrations of fat, oil and grease is produced by the food service, production, and processing industries. It has a high C to N ratio (90:1) and can recycle soil available N through immobilization and remineralization during its decomposition. Experiments were conducted at a farm (Hillsburg fine sandy loam; Typic Hapludalf) having rolling topography (5 and 9% slope) during 1995 and 1996. Objectives of this study were to (i) examine the variability of available N and corn (Zea mays L.) grain yield at different landscape positions of FOG-amended fields and (ii) determine whether N fertilizer management could be improved by considering the spatial variability of soil NO(3)-N at different landscape positions in FOG-amended fields. A spatial and temporal variability in soil NO(3)-N was observed during both years. Corn grain yields at all N fertilizer application rates were affected by slope position and followed the pattern: lower > upper > or = middle. Nitrogen fertilizer requirements for corn production in conjunction with FOG management were also affected by slope position. Essentially no additional fertilizer N was required for corn production at the lower landscape position. It was estimated that site-specific fertilizer N management on FOG-amended fields could result in an average savings of 51 and 63 kg N ha(-1) (with a potential economical savings of US 42 dollars and US 52 dollars ha(-1)) during 1995 and 1996, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".