Soil and weather conditions associated with plant damage from post-emergent metribuzin in lentil (Lens culinaris) in southern Australia
Why this work is in the frame
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Bibliographic record
Abstract
Multiple field experiments and a controlled-environment temperature study were conducted to investigate soil and weather conditions responsible for herbicide phytotoxicity in lentil (Lens culinaris Medik.) from post-emergent application of metribuzin. A linear relationship was observed between plant injury (% necrosis) and metribuzin rate in all 12 environments, but in only 11 environments for anthesis dry weight and nine environments for both plant density and grain yield. Grain-yield reduction from label metribuzin rates of 135 g a.i. ha–1 for sand and 285 g a.i. ha–1 for clay ranged from 0% to 32% and 0% to 67%, respectively, across all environments. Principal component analysis of soil and weather factors around the time of herbicide application suggested that metribuzin-induced plant damage in lentil was due to a combination of multiple soil and weather factors. However, heavy rainfall within 10 days of herbicide application, particularly on light-textured soils or where soil moisture was low, was most strongly linked to plant damage. Experiments targeting the impact of reductions in temperature post-metribuzin application showed no effect, and of light intensities pre- and post-metribuzin application showed low effects on plant-damage measures. Because rainfall in the 10 days after application is a major determinant of metribuzin damage in winter-grown lentil in southern Australia, a higher level of selective tolerance to metribuzin than that present in commercial cultivars is needed for its safe post-emergent use. Early and late measures of plant damage will be required to assess accurately plant tolerance to post-emergent metribuzin application in lentil.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it