Nutrient supply from organic amendments applied to unvegetated soil, lettuce and orchardgrass
Bibliographic record
Abstract
Organic sources of nutrients are increasingly being used in horticultural and certified organic production. The nutrient-supplying potentials of poultry manure compost (PM), feather meal (FM), alfalfa meal (AA) and vermicastings (VC) and an unamended control were measured in a growth room experiment. The amendments were applied at rates equivalent to 200, 400 and 800 kg total N ha-1 to a soil of low fertility. Nitrogen supply rates and concentrations were measured over 6 mo in unvegetated pots using PRS™ probes and KCl extraction, respectively. Biomass of lettuce (Lactuca sativa L.) and orchardgrass (Dactylis glomerata L.) and N uptake of orchardgrass were measured. Repeated measures analysis revealed significant amendment × rate × time interaction effects for N supply rate and concentration. Of total N applied, available N was 50 to 70% in the FM and PM treatments, 10 to 40% in the AA treatments, and 10% in the VC treatments. High rates of FM and PM were toxic to lettuce but produced good orchard grass yields. VC was safe for lettuce but low N availability limited long-term orchardgrass growth. Higher application rates did not result in corresponding increases in nutrient supply. Consideration should be given to balancing the ratio of available nutrients in amendments with plant requirements. Key words: Apparent nitrogen recovery, plant N uptake, feather meal, alfalfa meal, vermicastings, poultry manure compost
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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) | 0.001 | 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) | 0.001 | 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".