Wool and Hair Waste as Nutrient Source for High-value Crops
Bibliographic record
Abstract
Container and field experiments were conducted to evaluate sheep wool wastes and human hair wastes as soil amendments and nutrient sources for high-value crops. Overall, wool-waste or hair-waste additions to soil increased yields from basil, garden sage, peppermint, valerian, thorn apple, marigold, foxglove, and swiss chard; increased the amount of secondary metabolites (such as essential oils and alkaloids); increased NH 4 -N and NO 3 -N in the soil; and increased total N (and protein) content in plant tissue. The wool-waste or hair-waste additions did not affect soil microbial biomass, but decreased mycorrhizae colonization of plant roots. Scanning electron microscopy (SEM) and Energy Dispersive X-ray (EDX) analyses indicated that some of the wool and hair in soil from the container and field experiments (after two field seasons and several harvests) retained its original structure, a significant amount of S, some N, and was not fully decomposed. Results from this study suggest that wool and hair wastes can be used as soil amendment and nutrient source for high-value container or field crops.
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".