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Record W2012119088 · doi:10.4236/ajps.2014.59139

Tolerance of Winter Wheat (<i>Triticum aestivum</i> L.) and Under Seeded Red Clover (<i>Trifolium pretense</i> L.) to Fall Applied Post-Emergent Broadleaf Herbicides

2014· article· en· W2012119088 on OpenAlexaffabout
Kristen E. McNaughton, Lynette R. Brown, Peter H. Sikkema

Bibliographic record

VenueAmerican Journal of Plant Sciences · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMCPADicambaBromoxynilWinter wheatAgronomyClopyralidGlyphosateMecopropRed CloverBiologySowingPerennial plantAvenaWeed control

Abstract

fetched live from OpenAlex

The fall application of post-emergent (POST) herbicides on winter wheat provided effective control of emerged winter annual, biennial, and perennial broadleaf weeds. In recent years, wheat producers have seen a shift to these weeds, due in part, to the adoption of reduced-and no-tillage practices and the use of non-residual herbicides such as glyphosate in the preceding soybean and corn crops. The tolerance of winter wheat to ten herbicides, applied POST in the fall, was evaluated between 2008 and 2011 at Exeter and Ridgetown, Ontario. Winter wheat yield was not reduced by applications of MCPA ester, dicamba/ MCPA/ mecoprop, clopyralid, bromoxynil/ MCPA, thifensulfuron /tribenuron +MCPA ester, fluroxypyr +MCPA ester, and pyrasulfotole/ bromoxynil. In contrast, 2,4-D ester and dichlorprop/2,4-D, caused visible injury in June and July of the following year and consistently decreased winter wheat yield by at least 10%. Applications of 100 g a.i. ha-1 saflufenacil also decreased winter wheat yield in two of the four harvest years examined. None of the herbicide options examined were safe on red clover when it was under seeded the spring following winter wheat planting. All herbicides significantly decreased red clover dry biomass one month after wheat harvest.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.003
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.025
GPT teacher head0.244
Teacher spread0.219 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2014
Admission routes2
Has abstractyes

Explore more

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