Response of conventional and imidazolinone-resistant chickpea (<i>Cicer arietinum</i> L.) cultivars to imazamox and/or imazethapyr applied post-emergence
Bibliographic record
Abstract
Chickpea (Cicer arietinum L.) production in the Northern Great Plains is limited by very few broadleaf weed control options. Field experiments were conducted at two locations in 2012 and at three locations in 2013 in Saskatchewan, Canada, to examine the performance of the conventional and the imidazolinone (IMI) resistant chickpea cultivars to post-emergence application of imazamox or imazethapyr applied alone or in tank-mix. Treatments included imazamox (20 and 40 g a.i. ha−1), imazethapyr (50 and 100 g a.i. ha−1), and a tank-mixture of imazamox (35%) + imazethapyr (35%) (30 and 60 g a.i. ha−1). Conventional cultivars, CDC Luna and CDC Corinne, showed moderate to severe injury compared with resistant cultivars, CDC Alma and CDC Cory, which showed minimal to no injury. Plant height was arrested and node development slowed for conventional cultivars treated with IMI herbicides. This susceptibility to IMI herbicides was also noted with a delay in flowering and maturity. Despite a significant negative response, CDC Luna and CDC Corinne were able to recover throughout the growing season resulting in no yield loss from IMI treatments at all locations, except one. Resistant cultivars, CDC Alma and CDC Cory, demonstrated no significant injury from IMI herbicide compared with the untreated controls. These results show the potential to use IMI herbicides in the resistant chickpea cultivars, expanding the currently limited options for broadleaf weed control in chickpea cultivation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".