Evaluation of Efficacy of New and Existing Desiccants in Lentil (Lens culinaris Medik)
Bibliographic record
Abstract
In western Canada, weeds resistant to acetolactate synthase (ALS) inhibitors have created an extensive challenge for many lentil (Lens culinaris L.) producers, particularly producers growing imidazolinone (IMI) resistant lentil. These resistant weed biotypes may not always impact the yield of the current lentil crop, but the resulting seedbank additions and subsequent spread of these resistant biotypes can have a long-lasting impact in successive growing seasons. An effective weed seedbank management program is important to reduce the impact of problem weeds and is vital for farming operations to remain profitable and sustainable in future seasons. This 3-year study at Saskatoon and Scott, Saskatchewan (2012-2014) evaluated the impact of several pre-harvest herbicides on juncea canola (Brassica juncea L.) and kochia (Kochia scoparia L.) dry-down, weed seed production, and the viability and vigour of the weed seeds. The field study examined the effects of different contact herbicides, tank mixed with two different rates of glyphosate (450 g a.i. ha-1 and 900 g a.i. ha-1), on weed dry-down, weed seed production and the viability and vigour of developing weed seeds. Five contact herbicides were evaluated: pyraflufen, flumioxazin, saflufenacil, glufosinate, and diquat. Diquat (415 g a.i. g ha-1) and glufosinate (600 g a.i. ha-1) applied alone or tank mixed with glyphosate provided greater dry-down of kochia and juncea compared to flumioxazin, pyraflufen, and saflufenacil. No herbicide treatment was able to significantly reduce seed production of either weed species. Although several treatments reduced the thousand seed weight (TSW) of kochia, only a high rate of glyphosate was effective at reducing juncea TSW. Growth cabinet studies showed that glyphosate and glufosinate applied alone or in a tank mix together significantly reduced kochia seedling vigour. The number of viable juncea seeds was reduced significantly when glyphosate or diquat was applied alone. Overall, glyphosate applied alone was just as effective at reducing seed germination and seedling vigour as tank-mixes with diquat or glufosinate. However, a tank mix of glufosinate and glyphosate as a pre-harvest herbicide treatment in lentil would be the best option to delay the development of glyphosate resistance in kochia and wild mustard. This tank mix would also reduce the viability and vigour of kochia seed additions into the seedbank, as well as provide plant dry-down of lentil and weedy material prior to harvest. \n
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".