Potential use of leachate from composted fruit and vegetable waste as fertilizer for corn
Bibliographic record
Abstract
Composting fruit and vegetable waste from grocery stores on farms is a challenge due to the large quantity of liquid that leaches out. This leachate needs to be characterized for its effects on plant growth and soil. It was acidic with high conductivity; the plant mineral nutrient contents derived from the leachate (in decreasing order) were K, N mainly as ammonium-N, Ca, Mg, Na, and P; the trace elements were quite low. The germination and rootlet growth of cress and corn increased with the dilution of the compost leachate. In greenhouse assays, the compost leachate exhibited phytotoxicity to corn when used at high application rates. The corn leaf area, shoot and root biomass, plant concentrations and uptake of N, P and K were similar among the 20 mM N-fertilized control and the 30-40 m 3 /ha leachate treatments. In a field study on sandy loam, corn yields and plant uptake of P and K were similar among the mineral fertilized control and splitapplication leachate treatments applied to meet the P or K requirements of corn. After harvest, the soil pH, conductivity, and total N, P, and K contents were not affected by the leachate treatments. These results demonstrate the opportunity of recycling plant nutrients from compost leachate of fruit and vegetable waste as
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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".