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Record W1990494924 · doi:10.1614/wt-d-10-00147.1

Efficacy of Saflufenacil plus Dimethenamid-P for Weed Control in Corn

2011· article· en· W1990494924 on OpenAlexaffabout
Meghan Moran, Peter H. Sikkema, Clarence J. Swanton

Bibliographic record

VenueWeed Technology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsLambsquartersGlyphosateWeed controlAgronomyWeedBiologyRagweedDry weightField cornZea maysChenopodium

Abstract

fetched live from OpenAlex

A new, prepackaged mixture of saflufenacil + dimethenamid-P has been introduced for PRE control of grass and broadleaf weeds in corn. Field experiments with this new herbicide combination were conducted in 2008 and 2009 at four locations in southern Ontario, Canada. The objective of this study was to determine the dose of saflufenacil + dimethenamid-P required for overall weed control and species-specific weed control, as well as the dose required for early season weed control when followed with glyphosate at the six- to eight-leaf corn stage. Based on weed dry weight, the GR 95 across locations ranged from 126 to 675 g ha −1 . The 95% growth reduction (GR 95 ) for common ragweed, common lambsquarters, pigweed, and wild mustard were 933, 325, 186, and 115 g ha −1 , respectively. Highest corn yields were achieved with saflufenacil + dimethenamid-P applied alone at doses ranging from 368 to 1470 g ha −1 . When followed by glyphosate, the dose range of saflufenacil + dimethenamid-P required to achieve the greatest corn yields was 46 to 1,470 g ha −1 . A minimum dose of 184 g ha −1 of saflufenacil + dimethenamid-P followed by glyphosate was required for the yield to exceed that of the single treatment of glyphosate applied alone.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.225
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2011
Admission routes2
Has abstractyes

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