Effects of different timing and rate of glyphosate application on the residue level, grain quality, and processing performance of two Canadian malting barley varieties
Bibliographic record
Abstract
Abstract Background and Objectives A preharvest application of glyphosate on malting barley can assist in the management of perennial weed growth before harvest and serves as a harvest aid by drying down the crop. The main objective of this study was to assess the effects of preharvest glyphosate application at two glyphosate rates (900 or 1125 g ae/ha) and three application timings based on the maturity and seed moisture level (soft dough, hard dough, or mature). Findings The levels of glyphosate residue in barley grain were highly variable among locations and years ranging from 0 to 95 mg/kg. Glyphosate application at both rates at the soft dough stage significantly decreased the kernel weight of barley grain. Barley grain with up to 40 mg/kg of glyphosate residue exhibited adequate germination energy required for malting purposes; however, the residue negatively affected the growth of roots during the malting process. The levels of α‐amylase in malt decreased with increasing levels of glyphosate residue in barley. Other malt and wort parameters were generally not affected by the glyphosate application on barley. Conclusions Too early application of glyphosate at the soft dough stage of barley grain development reduced the kernel weight and size, interfered with roots production, affected synthesis of α‐amylase, and reduced the malt extract in several cases. Significance and Novelty Results indicated that in the majority of environments, when glyphosate was applied at the recommended stage and rate, neither the maximum residue limit was exceeded nor were the germination and malting quality of barley impaired. In real farming conditions, it might be hard to achieve similar results despite adherence to the recommended timing of glyphosate application because of the nonuniform level of crop maturity in the field and/or uncontrollable environmental effects.
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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 | 0.000 | 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 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".