Effect of five postemergence herbicides on red clover shoot and root growth in greenhouse studies
Bibliographic record
Abstract
MCPA, 2,4-DB, flumetsulam, bentazon, haloxyfop-methyl, flumetsulam/2,4-DB and bentazon/MCPA were studied in greenhouse experiments in order to evaluate their primary effects on red clover (Trifolium pratense) growth and root injury. The influence of these herbicides on root length, plant height, crown diameter, shoot and root dry weights, shoot phytotoxicity and root injury were studied at two application rates. Variable responses in the growth parameters were observed throughout the experimental period. Herbicides did not affect root length. By the end of experiment, plant height was increased by all herbicides except MCPA and bentazon/MCPA. Crown diameter was increased only with MCPA and 2,4-DB, whereas it was not affected by the other herbicides. Bentazon reduced root dry weight while the other herbicides had no effect. In general, MCPA, bentazon, and bentazon/MCPA reduced shoot dry weight. Although all herbicides caused early foliar damage, the plants recovered by the end of expe-riment comparable to the control plants. Bentazon and bentazon/MCPA produced the greatest shoot damage. Roots were injured from all herbicides, yet they usually recovered over time. However, bentazon/MCPA induced more severe root injury, up to 17% of the plants, causing seedlings died. These results suggest that some herbicides used to protect red clover against weeds may also affect red clover development, increasing its vulnerability to disease.
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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 | 0.001 |
| 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".