Weed management in irrigated fenugreek grown for forage in rotation with other annual crops
Bibliographic record
Abstract
Fenugreek (Trigonella foenum-graecom L.) is an annual legume that has potential as a forage crop on the Canadian Prairies. Experiments were established to determine the tolerance of fenugreek to several herbicides and their efficacy on various weeds. Potentially, fenugreek could be grown in conservation tillage systems in rotation with other annual crops. Therefore, additional multi-factor experiments were conducted to determine the effect of herbicides, seeding method, and 11 previous crops on fenugreek yield. Without herbicide application, weeds contributed 37 to 86% to total dry matter production. When imazamox/imazethapyr, or combinations of imazamoz/imazethapyr or imazethapyr with ethalfluralin was applied, weed contents were about 5% of the total dry matter and the herbicides did not reduce fenugreek yield compared to the hand-weeded check. Total forage samples with a low weed content had lower fibre content and higher protein and digestible dry matter content than forages with a high weed content. When imazamox/imazethapyr was used for weed control, fenugreek yields and weed biomass were similar after direct seeding and after cultivation plus seeding. In addition, the effect of previous crop and the previous crop by seeding method interaction was not significant for fenugreek yield and weed biomass. Therefore, irrigated fenugreek can be successfully grown in conservation tillage systems in rotation with several crops provided an effective herbicide is used for weed control. Key words: Conventional tillage, crop rotation, redroot pigweed, wild oat, zero tillage
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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) | 0.000 | 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 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".