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Record W2173522426 · doi:10.1614/wt-04-152r.1

Effect of Herbicides on Field Violet (<i>Viola arvensis</i>) in Direct-Seeded Spring Wheat

2005· article· en· W2173522426 on OpenAlexafffundabout
Rory F. Degenhardt, Dean Spaner, K. Neil Harker, W.R. McGregor, Linda M. Hall

Bibliographic record

VenueWeed Technology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsAgriculture Food and Rural DevelopmentAgriculture and Agri-Food CanadaUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDicambaMetribuzinGlyphosateAgronomyWeed controlWeedMCPAMecopropOryzalinBiologyCropEnvironmental scienceHorticulture

Abstract

fetched live from OpenAlex

The agrestal field violet, a pervasive weed in Europe, has been identified in reduced-tillage cereal fields in Alberta. The efficacy of herbicides in direct-seeded spring wheat was assessed on natural field violet infestations in Alberta in 2002 and 2003. Only fluroxypyr + 2,4-D, applied postemergence, provided control of field violet in 2002 when rainfall was limiting. Over both years, this herbicide combination reduced biomass by 59 to 69% and plant density by 83 to 91%, relative to nontreated plots. The herbicides metsulfuron, sulfosulfuron, and thifensulfuron + tribenuron only suppressed weed growth under drought conditions in 2002 but controlled the weed in 2003 when rainfall was greater, reducing plant density by 82 to 92% and rendering remaining plants sterile. Suppression was also observed with MCPA + mecoprop + dicamba in 2002 and 2003 and with metribuzin only in 2003. Effective control of field violet was conferred by a pre–crop emergence application of glyphosate at 445 g ae/ha in 2003, the only year that this treatment was evaluated. Activity of herbicides on three- to four-leaf seedlings was also evaluated in a greenhouse dose– response assay. All herbicides had greater efficacy in the greenhouse, and those that provided control in situ reduced field violet dry weight by 85% at less than the recommended rate used in field experiments. Management of field violet is possible with herbicides registered for use on spring wheat in Alberta. However, the weed does not appear to cause significant crop production losses; hence, herbicide selection should be based on knowledge of all weed species present within the field.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.218
Teacher spread0.213 · 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

Citations6
Published2005
Admission routes3
Has abstractyes

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