Response of chickpea cultivars to pre- and post-emergence herbicide applications
Bibliographic record
Abstract
Taran, B., Holm, F. and Banniza, S. 2013. Response of chickpea cultivars to pre- and post-emergence herbicide applications. Can. J. Plant Sci. 93: 279-286. Weed control is one of the major constraints of chickpea (Cicer arietinum L.) production in western Canada. There are no highly selective herbicides registered for broadleaf weed control in this crop in western Canada, consequently herbicide injury to the crop is an issue in many situations. Experiments were conducted at Saskatoon and Elrose, SK, to examine the effects of herbicide treatments on ascochyta blight severity, days to flowering, days to maturity, plant height and yield of several chickpea cultivars. Results in 2008 and 2009 showed that sulfentrazone was the safest option evaluated for broadleaf weed control in chickpea. The results also showed that although a pre-emergence application of low-rate imazethapyr caused minor levels of injury to the plants and slightly increased ascochyta blight severity, it had only minor effects on plant development and yield compared with sulfentrazone. In contrast, post-emergence applications of imazethapyr, imazamox and metribuzin increased ascochyta blight severity significantly, delayed flowering and maturity and reduced yield. The extent of the effects of pre- and post-emergence herbicide applications varied with cultivars.
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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 | 0.001 | 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".