Winter cereal responses to dose and application timing of trinexapac‐ethyl
Bibliographic record
Abstract
Abstract Trinexapac‐ethyl (TE) is a plant growth regulator commonly used in cereal production systems. It retards plant growth by inhibiting gibberellin (GA) biosynthesis, thereby reducing the risk of stem lodging. Lodging at the latter stages of crop development can compromise grain yield and quality. Thus, application of TE may protect yield and quality in winter cereals. A field study was conducted from 2014 to 2017 across the Canadian Prairies to determine the effects of TE dose and application timings on lodging, canopy architecture, grain yield, and quality of winter cereals. Trinexapac‐ethyl treatments consisted of 0.6× (60 g a.i. ha −1 ) and 1× (100 g a.i. ha −1 ), which were applied to two winter wheat ( Triticum aestivum L.) cultivars, 'Flourish’ and ‘Moats’, and a fall rye ( Secale cereale L.) cultivar ‘Hazlet’, at Feekes 5 and 7 growth stages. Compared with the control, TE application increased grain yield by 3–8%, reduced plant height by 5–10%, and shortened internode length. Plant height reductions were most notable when TE was applied at the 1× rate at Feekes 7. The most responsive crop was fall rye, which could be expected given its tall stature relative to the wheat cultivars. Most of the tested environments, including irrigation, did not induce heavy stem lodging; therefore, observations of positive yield responses in the absence of lodging were unexpected. Our findings suggest that there is a role for TE in winter cereal production systems, provided the magnitude of crop responses justifies the added input costs.
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 | 0.000 | 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".