Identification of phytotoxic substances in soils following winter injury of grasses as estimated by a bioassay
Bibliographic record
Abstract
Under northern conditions, winter survival of grass species for hay production is quite uncertain because of winter stresses to plants. Damage to plants may be caused by variability in snow cover, low temperatures, ice encasement and pathogens. Compared to renovation by ploughing, direct drilling without ploughing has some beneficial aspects and may be an alternative method for renovating hay fields. However, successful establishment of grasses without ploughing has been difficult to achieve both in scientific studies and under practical conditions. The objective of this investigation was to study whether a dead grass sod, killed by different winter injuries, may leak phytotoxins into the soil, thus causing the poor results observed by direct drilling in hayfields. Experiments, including soil water extraction and the use of bioassays, were conducted in growth chambers, to study the effects of the winter stresses frost, ice encasement, and snow mould on the accumulation of potentially phytotoxic biochemical compounds in the soil. Snow mould did not kill the grasses in the experiments and no phytotoxicity was measured. Although both ice encasement and low temperatures killed the grasses, only ice encasement caused phytotoxicity. The present investigation shows that the occurrence of phytotoxic substances, especially butyrate, after ice encasement may be a cause of poor establishment of direct-drilled grass plants after winter injuries. In serious cases of ice encasement this may justify a 1-2 wk delay of sowing, which in turn may result in reduced soil water for germination and may cause increased competition from other species. Key words: Hay fields, grassland, winter injuries, phytotoxic substances, allelochemicals
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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".