Short-term effect of soil disturbance by mechanical weeding on plant available nutrients in an organic vs conventional rotations experiment
Bibliographic record
Abstract
The question whether soil disturbance from mechanical weeding in organic systems affects nutrient release from organic matter in compost-amended soil was examined in a long-term organic-versus-conventional rotational cropping system experiment over three years. The experimental design included continuous snap beans, and a fully phased snap beans/fall rye crop rotation sequence. Treatments were combinations of yearly applied fertiliser (synthetic fertiliser, 1× compost, 3× compost) and weed control (herbicide, mechanical weeding). The 1× compost rate was calculated to deliver the equivalent of 50 kg N ha-1: equal to the rate ofN in the synthetic fertiliser treatments. Ion exchange membranes were buried for 24 hours following mechanical weeding in bean plots. Adsorbed ions were then eluted and quantified. Available ammonium-nitrogen was not affected byweeding treatment, but nitrate-nitrogen was consistently less in mechanically weeded plots than in plots treated with herbicide. Principal component analysis of NH4-N, NO3-N, P, K, Ca and Mg availabilities showed distinct groupings of treatments according to fertility treatment rather than weeding treatment. The effect of cropping sequence on available nutrients was pronounced (P ≤ 0.001) only in plots amended with synthetic fertilisers.
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 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) | 0.000 | 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) | 0.001 | 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".