Effect of post-emergence herbicide injury and planting date on yield of narrow-row soybean (<i>Glycine max</i>)
Bibliographic record
Abstract
Some herbicides used post-emergence (POST) in soybean production cause foliar injury; however, new growth is normal and the crop does not appear to be further affected. Experiments were conducted to determine the effect of different levels of foliar injury caused by POST herbicides on yield of soybean cv. Maple Glen when planted early and late in a weed-free environment. Level of foliar injury was variable from year to year. Aciflurofen and imazethapyr caused foliar injury of 7 to 35% whereas, thifensulfuron and bentazon gave foliar injury ranging from 0 to 20% at 15 d after treatment (DAT). Foliar injury was short lived, and by 30 DAT had disappeared in 1994 and 1997, but still was visible at 11% for aciflurofen and 17% with imazethapyr on late-planted soybean in 1995. Aciflurofen- and imazethapyr-treated soybeans were still stunted at 30 and 60 DAT. Only imazethapyr reduced yields on both early- and late-planted soybean, in the 3 yr of the study. Yield of Maple Glen soybean was higher with early-planted soybean than with late-planted soybean in all years. Maximum yields were obtained in control plots kept weed free all season by a pre-emergence application of metribuzin. Key words: Aciflurofen; bentazon; imazethapyr; metribuzin; thifensulfuron; stunting; delayed maturity; foliar injury
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".